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Oct

Key roles and responsibilities of a Scrum Master explained!

iCert Global Agile and Scrum 0 2021-10-01 2882

In this blog we cover the typical tasks, responsibilities, skills, problems, qualities, and benefits of the Scrum Master role in Scrum.

What is a scrum master?

Scrum Master is often the term used for this role, even by teams that do not explicitly follow Scrum. Other terms that are rarely used are iteration manager, agile coach, or team coach. The Scrum Master cleverly removes obstacles and distractions that could prevent the team from achieving its goals. This person is the connection between the Scrum Team and the people or teams outside of the Scrum Team. The Scrum Master is a service leader for the Scrum Team who helps the Scrum Team and its environment work together and interact to maximize the value delivered by the Scrum Team. Article - Scrum master roles and responsibilities will give you a brief knowledge about how Scrum Master works. Scrum Master is also responsible for helping people to understand Scrum theory, its practices, rules and values.

Imagesource - https://www.lucidchart.com/blog/scrum-master-skills-and-responsibilities

Skills defined for scrum master -

While there are no officially defined skill levels for Scrum Masters, there are different levels of experience in practice:

Rotating scrum master - Members of a team rotate Scrum Master responsibilities (primarily administrative) among themselves on a sprint-by-sprint basis.
Part time scrum master - In addition to other tasks on the same team, one person on the team assumes the Scrum Master tasks.
Full time scrum master - The sole responsibility of an individual is to be a Scrum Master at one time or another. This model is the best for a team that is learning agilely.
Full time scrum master with more than one team - This model is often used when a person's only responsibility is to be a Scrum Master, but they are working with more than one team.
Agile Coach - A person does not have a specially assigned team, but works with several teams and only on certain needs.

Benefits as a scrum master

The overall benefit one expects from a Scrum Master in a team is to provide a self-organizing team with constant access to someone who has used Agile and especially Scrum in a different environment and can help the team find the best way to apply it. in your situation.

Another expected benefit is that the Scrum Master is someone who can address distractions, interruptions, and obstacles so that the rest of the team can focus on work to produce results that produce the desired result.

Common problems as a scrum master

While there are several advantages to being a Scrum Master, several problems arise from improper use of the role. These problems include:

Suppose you can only slide project managers that are used to command and control the guide guide guide in a scrum Master role and expect it to be effective.
Asking someone to fill the role of Scrum Master with no experience in an agile environment.
Expect a Scrum Master's workload to be the same across teams, regardless of how long they have worked as a team, how they understand Agile values and principles, and what domain expertise they have.
A well-functioning team will likely need much less training from a Scrum Master than a team that is new to working with Agile values and principles.

7 Key scrum master’s responsibilities

Despite the word "Master" in the title, the Scrum Master is not responsible for the project or the development team. Instead, a scrum masterpiece works with the product owner and the scrum team to refine and improve processes where it makes sense.

A Scrum Master role may include, but is not limited to, the following responsibilities.

Teach Scrum practices and principles - To ensure that the work does not decrease the speed, an important role of Scrum Master is a mentor and a teacher to provide new employees and new team members. As a teacher, Scrum Manager helps new team members understand the scope and vision of a product and ensures that team members understand Scrum theory and adhere to Scrum rules and practices. The Scrum Master teaches the team to organize and stay focused.

Scrum Master qualifications do not include personnel management. Furthermore, the Scrum Master is not individually responsible for the results of the project; Instead, the scrum team as a whole is responsible for the results. The Scrum Master has the authority to ensure that the team implements and adheres to the Scrum values, principles, and practices. Whenever they are lacking as a teacher, the Scrum Master will help them understand the scope and vision and adhere to Scrum rules and practices.

Host daily stand-up meetings - Daily scrum or standup meetings last no more than 15 minutes and allow each team member to answer these questions:

What will you do today?
What is hindering your progress?
What did you do yesterday?

Team members can be asked to estimate how long they will need to complete certain tasks. The Scrum Master moderates this meeting, tracks the team's progress, and takes note of obstacles that could prevent the team from completing tasks.

The Scrum Master ensures that all team members, including those who work remotely, can attend and participate in the daily meeting. They also make sure the meeting stays focused and ends on time.

Remove roadblocks - To help the team focus on the tasks that need to be accomplished during each iteration, the Scrum Master looks for distractions and obstacles that may hinder progress. For example, if team members are involved in too many unimportant meetings, the Scrum Master can work with the meeting organizers to determine who should attend the meetings.

Or if a team member is drawn in too many directions and tasks are assigned to multiple teams, the Scrum Master can work with Product Owners and other stakeholders to redistribute the workload.

Again, there could be internal disagreements in the team about their individual work styles or disagreements about the Scrum process itself. The Scrum Master can have a one-on-one interaction with members of the development team to understand the same and resolve such conflicts before they turn into full-blown disagreements.

Coach team members - The Scrum Master ensures that team members are well trained and understand agile processes. The Scrum Master also ensures that team members know their respective roles, that they have a sense of responsibility for the project, that processes are followed, and that teams are self-managed.
Assist the product owner with the product backlog - The product owner is responsible for creating and maintaining the product backlog. The Product Backlog is a list of the work that the team must do. The Scrum Master helps the Product Owner to refine and maintain the Product Backlog with information from daily meetings. The product backlog is a live document that changes based on current status and development needs. The Scrum Master can help with the Product Backlog by planning meetings and writing user stories.
Keep all parties on track and informed:- The Scrum Master conducts daily team meetings to learn about the project's progress, resolve potential obstacles, and make sure the project is on track. They also hold regular meetings to share with product stakeholders about the project's progress (or not). Ultimately, it is the job of a Scrum Master to make sure the team is on schedule with the desired outcome.
Protect the team from outside interference - The Scrum Master acts as a protector and assists the team by shielding it from outside interference that gets in the way of realizing business value during each sprint.

Interference can come from many sources; for example, by managers who want to divert team members in the middle of a sprint. Regardless of the source of the interruption, the Scrum Master acts as an interceptor and solves the problem amicably.

This role includes more scrum master’s responsibilities like:-

Overcoming obstacles
Protect the team from external disturbances and distractions.
Ensuring a good relationship between the team and the product owner and others outside the team.
Create an environment in which the team can be effective.
Dynamic team management.

Do you want to pursue your career as a scrum master?

Typically, most Scrum Masters skill job descriptions require applicants to have at least a bachelor's degree in computer science or a related field to become a Scrum Master. Also, you need some experience as an agile software developer. One of the most important Scrum Master skills you will need is communication.

As part of your Scrum Master roles, you will be the primary communicator between project owners and other key stakeholders.

If you do not have good oral and written communication skills, or if you feel uncomfortable interacting with One-on-One or in groups, this may not be the job for you.

Earning a Scrum Master’s certification can increase your chances of landing a higher paying job as it confirms that you have the right skills.

Scrum master’s certification programme

There are also a number of other Scrum certification programs that may interest you, including:

Scrum Developer
Scrum Coach
Scrum Trainer
Scrum Professional
Scrum Product owner

A Scrum Masters certification in any of these disciplines can boost your career and mean significant salary increases. The possibilities are open.

Qualities of a scrum master

Observant:- The Scrum Master is not a manager, but a team member and a moderator. They must be good listeners and be aware of the challenges the project team faces at every step. The Scrum Master must also be alert and aware of the daily activities of the team to have a clear view of the roles and contributions of the members in the sprint sessions.
Collaborative - The Scrum Master forms an essential link between the product owner and the project team. While the Product Owner drives the overall initiative, the Scrum Master maintains the team. An effective collaboration between Scrum Master and Product Owner ultimately leads to successful products that meet the organization's requirements. A good Scrum Master should be able to find creative ways to increase organization, collaboration, and productivity to deliver the product that the business unit owner has requested.
Influential - A Scrum Master leads different teams working on a project to achieve certain milestones and results. He must be able to motivate multiple groups and stakeholders at the organizational level and maximize the potential of everyone involved. As a team leader, the Scrum Master must bridge the gap between the project concept and the steps required to complete it. The Scrum Master must have strong organizational and leadership skills.
Knowledgeable - In addition to solving problems and problems that arise, the Scrum Master must also proactively prevent potential problems. This requires a thorough knowledge of the product and the process. The Scrum Master's experience allows the team to avoid obstacles. The Scrum Master must have knowledge of various agile work formats and methods such as XP, Lean, and Kanban.
Transparent - Last but not least, the Scrum Master must be transparent in all forms of communication. There should be no hidden intentions when working with team members; What you see and hear from the Scrum Master has to be what you get. People expect no less from a leader in service.

The Scrum Master also promotes transparent communication outside of the Scrum team. Without transparency, it is difficult for the organization to use Scrum to review and adjust the desired business results.

Different tasks for a Scrum Master

Organizations often find a way to implement the Scrum Master role and therefore there are many types of Scrum Masters. There are Scrum Masters who mainly focus on the development team and support them during Scrum events and in their work. This is often the result of implementing the Scrum Master role as a part-time role. In other organizations, Scrum Masters act more like agile change agents who change the organization, advise top management, and implement change.

The following list is not complete, but some typical scrum masters tasks include:

Employee training and workshop moderation to gain a better understanding and better application of the Scrum framework.
Support, training, coaching and support of the product owner, the development team and the organization if it is necessary or demanded to continually improve and become more self-organized.
Moderation of Scrum events if required or requested by the Scrum team.
Prepare and carry out the Sprint Retrospective by collecting data and observations during the Sprint.
Train stakeholders (including clients, Clevel, top management, and other stakeholders) on agility and understanding of the Scrum framework to effectively interact with the Scrum team; and,
Solve obstacles if necessary and / or teach the Scrum team how to solve obstacles themselves.

Traits of the Scrum Master

Empathy:- Being able to feel what is happening in a group of people is critical to the success of Scrum Masters. The most valuable things are often said between the lines or can be gleaned from non-verbal communication. This is often used for the Scrum Master to train and train people to maximize the value of Scrum.
Courage:- There are many important skills and traits for Scrum Masters, but if you make it to the top three, you must have "courage." As explained in the "Skills" section, the Scrum Master is a servant leader. Many organizations are "damaged" in some way. In many organizations, people are afraid to speak up, make mistakes and, for example, take responsibility. The Scrum Master as a leader plays an important role in showing people the courage to follow him and act boldly.
Openness:- Transparency, necessary for review and adjustment, is one of the pillars of Scrum. Openness is an extremely important value in Scrum. Both are critical to the success of Scrum. However, for many people it is terrifying to be completely open and transparent. Therefore, the Scrum Master must be open and honest and be an example to follow for others.

Wrapping up

As a reminder: the Scrum methodology is a subset of agile software development, in which a development team sets goals to provide new software features and functions in clearly defined iterative cycles. Each iteration delivers small but significant parts of an overall project every two to four weeks. Whether you're interested in becoming a Scrum Master or want to make sure you establish best practices in your Scrum team, learn about these important Scrum Master skills and responsibilities that come with the job. This Scrum Master role is responsible for ensuring that the project runs smoothly within the guidelines of the Scrum methodology. By implementing these tips and working through the requirements, you are on your way to becoming the master of your scrum.

“Scrum master roles and responsibilities” - this elaborated article will help you to grow in your organization and will help you to learn more about teamwork and team management.

The Scrum Framework consists of three roles, the Product Owner, the Scrum Master, and the Development Team. Together they make up the Scrum team. This elaborated article titled Scrum master roles and responsibilities will help you to grow in a professional manner.

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Sep

"Top 10 Project Management Tools for Efficient Workflows"

iCert Global Project Management 0 2021-09-30 1630

The project manager's answer to project management is project management tools. Simple projects only require a checklist, however more complex projects necessitate adequate planning, task assignment, deadline setting, ensuring that everyone adheres to them, and time tracking.

Quantifying, objectifying, segregating, and delegating work appropriately and proportionately is critical, and this is where current tools come in. There are a lot of project management software solutions out there, and if you're new to project management, it can be difficult to figure out what's important, what's useful, and what's not.

The process of initiating, planning, executing, and closing tasks to meet the project's goal is known as project management. The term "project management" refers to the process of overseeing project activities such as the use of advanced tools and new approaches, a wide range of talents, and the involvement of specialists with application knowledge. All of these activities result in meeting the project's requirements.

Employing Project Management Applications or Software to be able to manage the Project Management System smoothly, effectively, and efficiently is the biggest task. Such tools can be used to maintain track of project activities such as which task is assigned to which resource/team member, which phase of the project is completed and when it is completed, and so on.

One must examine the following criteria when choosing Project Management Software for a project.

The project's duration
the number of persons involved in the project
The amount of money that will be spent on the tool
Storage The software tool's capacity
PM Email communication, file sharing, tracking, and more features are offered.
Usability

10 Best Project Management Tools to Manage Projects

1. Asana

Asana is a collaborative project management software as a service (SaaS). Workflows can be used to automate repeating tasks. It's user-friendly, with a variety of task displays and the ability to add custom fields and forms. You can also invite an unlimited number of guests. It's also possible to create custom rules and approval workflows.

While Asana has a lot to offer in terms of efficiency and collaboration, many of the fundamental project management features are handled through integrations, which may not be optimal for many users. It's suitable for all types of enterprises, but not for freelancers. Although some users believe Asana's design is extremely simplistic and the system is too strict, it does offer powerful task management and communication tools.

Costs Involved: A free plan for up to 15 users is available. You can view tasks as lists, on a calendar, or on a Kanban board to manage them. Timelines, reports, custom fields, automation rules, and more are included in their Premium plan, which costs $10.99 per month per user. Approvals, portfolios, rule builders, workload, and advanced integrations are all available in the Business plan, which is not available in the other plans. When paid annually, it costs $24.99 per user per month.

2. Zoho Projects

Zoho Projects is a popular project management software from Zoho product that allows businesses to keep track of tasks, collaborate, track bugs, and generate easy reports. Gantt charts and the ability to billable hours on numerous projects at the same time are among the tools available.

Zoho Projects also has a robust set of communication capabilities, including real-time chat and discussion forums. Zoho Projects, which is part of a larger suite of productivity tools from the same firm, includes nearly all of the basic features you'd expect from a project management app at an especially low price.

However, many users complain that the Gantt charts are difficult to use and that the reporting breakdown is insufficient for large teams. From within the tool, you can share documents. Every project's worth is determined by its planning. Project planning with Zoho Projects software takes less time, allowing you to focus on real-time work the rest of the time. The Zoho Projects software has an online forum where team members can communicate even if they are geographically apart.

Costs Involved: When it comes to subscription plans, Zoho offers numerous options (All monthly plans are per user.):

There is a perpetually free version with limited features and users.
Custom statuses and problem tracking are included in the $3 Standard plan. It can accommodate up to ten users.
The Express plan costs $4 per month and allows for up to 50 users. Recurring tasks, Gantt charts, and timesheet approvals are all included.
The Premium plan costs $5 per month and allows for up to 100 members. Task automation, business rules, resource use, and budgeting are all included.

3. Wrike

Wrike is a cloud-based project management programme that makes project planning simple, allows you to track your team's progress, keep track of deadlines, and engage with all stakeholders with ease. Task management, Gantt Charts, a real-time newsfeed, and more advanced capabilities are available. You can prioritise jobs to ensure that the most important tasks are completed first and that deadlines are met. There are numerous integration options, making it a versatile project management tool.

For most novice users, the sheer quantity of features can be intimidating, and the unintuitive UI doesn't help matters. It's perfect for a variety of internal teams, including marketing, software development, and professional services.

Wrike is a good option. Standard project management tools such as Gantt charts, informative dashboards, and a robust reporting suite are built-in, and getting up and running on a small to medium-sized project can be done quickly without having to learn all the ins and outs of a new, complicated system.

Costs Involved: A freemium version with restricted features and up to five users is available. Paid plans begin at $9.80 per user per month. A Business plan is available for $24.80 per user per month. Subtasks, Gantt charts, time tracking, and workflows are all supported.

4. Monday.com

Monday.com is an intuitive, easy project management software that combines a visually appealing UI with essential project visualisation tools. It's adaptable and clear in how it organises your work. On top of that, there are project templates from which you can create your own boards. There are several display possibilities, including a map view and a calendar view.

It is used by over 100,000 companies to handle everything from marketing campaigns to product development to complicated building projects.

Transform information into action: Increase transparency across your organisation by making your data accessible to anyone.
Integrations that are seamless: More than 40 of your favourite services can be integrated.
Automation of processes: Allow your team to focus on the vital things instead of wasting time on tedious operations.
Collaboration in a small group: There are no email chains, group texts, or approvals to wait for.
Dashboards: Get critical insights and metrics for many boards in one location, and visualise the data that matters most to you.

The lack of recurring activities is a typical source of consumer frustration. For certain people, navigating the mobile app is difficult. They also provide excellent security, a wide range of functions, and simple customization.

Costs Involved: The pricing structure is excessively complex. There is no freemium plan, so you'll have to spend time every month figuring out how many users, automation, and integration activities you'll need. Paid plans for five users start at $39 per month.

5. ProofHub

If you want to make project management and team collaboration easier for small business marketing and creative teams, Proofhub is the way to go. It features everything you'll need to efficiently manage your marketing initiatives, including everything you'll need to keep track of every detail and see what your team is working on in real-time. Leading companies such as Netflix, TripAdvisor, Nike, and others use Proofhub.

Task lists, processes, Gantt charts, discussions, calendars, and documents are all consolidated in ProofHub. It allows you to plan, manage, and track the tasks of your team. It also facilitates collaboration between teams and with external clients. There are other reports available, such as workload and resource reports.

One of the most appealing aspects of adopting ProofHub as a project management system is its user-friendly interface, which requires little to no training. It means you can navigate ProofHub and make the best use of all of its features without needing any specialised knowledge. ProofHub features a small number of integrations and task management options due to its focus on simplicity. It's suitable for both freelancers and small and medium-sized organisations.

Costs Involved: ProofHub has no limit on the number of users and charges a flat rate regardless of that number. There are two plans available: the Essential plan is $50 per month, and the Ultimate Control plan is $99 per month.

6. Clarizen

Clarizen is a well-reviewed online project management tool for mid-to-large-sized enterprises. Because the system is only for web-based project management, the lack of a mobile app may limit the system's utility for some teams. The sophisticated reporting capabilities and ability to track resource utilisation are popular among users, although it lacks a to-do list and time tracking.

Clarizen One's ability to custom build or change OOTB functionality has considerably benefited in producing a system that is tailored to your specific needs while still operating inside a complete framework.

Because it has specialised ways of organising workflows, the learning curve is a little steep. Clarizen is best for enterprise-level project managers, IT organisations, and professional services teams who need strong, versatile, and intuitive web-based project management software.

Costs Involved: Pricing is not published but can be obtained upon request.

7. Airtable

Airtable combines the greatest capabilities of spreadsheets and databases in one application. It's adaptable and simple to use, and it's suitable for businesses of all sizes. It lacks extensive reporting capabilities, which may be an issue for some users.

You can utilise the database to store information for task management and project planning. Many customers appreciate the flexibility of data arrangement that Airtable's spreadsheets provide. There are several views available, including Kanban, list, grid, and calendar.

Airtable is a flexible and dynamic Work Management Solution that can be used for a variety of tasks. Airtable will feel like a natural fit if you're used to spreadsheet-based applications like Microsoft Excel or Google Sheets. Airtable may help you and your team with the following tasks, as this Airtable review demonstrates:

Project Plans: Organize and Manage
Execute Task Management That Is Repetitive
Assign Resources to Tasks
Using Templates to Create Projects
Budgeting for Projects
With powerful integrations, you can make file sharing and workflow management easier.

Costs Involved: Airtable offers a free plan with basic capabilities like rich field types, multiple views, and collaboration. Paid options start at $10 per user per month for businesses with more data storage needs. Advanced features like custom branded forms, customizable views, and domain limited sharing are available in their Pro plan.

8. Kanban Tool

The Kanban Tool is a good place to start if you're new to agile development. It provides a visual representation of your process as well as time-tracking capabilities. Notifications, reporting, and team management capabilities make communication and task tracking simple.

Reporting, document sharing, a native mobile app, and other capabilities make it excellent for medium and big businesses. The Kanban application also allows enterprise users to host the software on their own servers.

Costs Involved: It isn't intended for freelancers, although there is a free plan that supports two project boards and allows up to two users. Paid subscriptions begin at $5 per user per month and include unlimited boards. Enterprises can get sophisticated capabilities like time monitoring, reporting, user management, and process automation for $9 per user each month.

9. Workzone

Your project dashboard gives you access to all of your projects and allows you to conveniently check their status. When you open a project, you'll see subtasks, due dates, and assignees right away. To remain on top of things, you'll also receive handy notifications when deadlines approach. Workzone focuses on functionality rather than frills.

Workzone makes it simple for members of your project team to contribute by including a remark section under each assignment. All of your interactions will be carefully organised and placed where they are most relevant as a result of this.

Users, on the other hand, have complained that mobile applications are in need of improvement, that they lack features such as assigned comments and numerous views, and that the user interface is outdated.

Costs Involved: Workzone provides you with Two options. Team ($24/month per user): Includes a plethora of features as well as 100GB of cloud storage for uploads. Professional ($34/month per user) includes all "Team" features as well as 150GB of cloud storage for uploads.

10. ServiceNow ITBM

According to the Forrester Wave research, ServiceNow IT Business Management (ITBM) is a prominent strategic portfolio management product with significant project management features. It includes tools for planning and scheduling development efforts, resource management based on project priorities, and job tracking. In addition, ServiceNow ITBM allows you to track project expenditures and provides statistics for a high-level project and portfolio management.

A firm can increase the performance of project management, demand management, and programmes while balancing resource availability with ServiceNow (ITBM). ServiceNow's ITBM combines features ranging from cost transparency to project portfolio management. Businesses can use ServiceNow ITBM solutions to increase the visibility of business services and create cost savings by leveraging data and analytic metrics. When a company is attempting to handle demands or projects such as Agile, Waterfall, or Scrum, these functions are required.

Costs Involved: ServiceNow ITBM aids in the reduction of project costs, the acceleration of development processes, and the better alignment of IT with business goals.

These were the 10 best tools to manage projects without any hurdles.

Conclusion

Each of these programmes has its own set of benefits and will be able to help you fill in the gaps in your career. Because not every business is best served by a standard project management system, industry-specific project management systems have been developed to lessen the amount of customisation required after adoption. Construction, software development, financial services, healthcare, and law all have features and adaptations that make them more industry-friendly.

Collaboration tools, expenditure monitoring, portfolio management, contractor management, resource management, and other industry-specific solutions are available. These tools might also come in handy if you're managing a creative team, a remote team, or a specific project inside your bigger portfolio.

Large teams managing a number of concurrent, complex projects may need to track each one separately while still being able to report and assess their progress. Companies can use project portfolio management software to handle several projects within one or more portfolios. With each project, project managers and stakeholders can get a high-level perspective of progress, immediately identify bottlenecks, and dive down into trouble areas. These tools are also useful for allocating team resources and tracking expenses across many project deadlines, as they can demonstrate where slack can be filled by others.

It cannot be stressed that ease of use is not an optional feature when it comes to project management software – it is a need! Team members will become upset and struggle if project tools are not straightforward and intuitive to use. They may even explore ways to avoid utilising some project tools entirely, not because they want to breach the rules, but because they need to stay productive and fulfil deadlines. Ease of use is critical regardless of the context or application – IT project management tools, marketing project management tools, engineering project management tools, and so on.

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Sep

The Importance of Machine Learning for Data Scientists.

iCert Global Emerging Technology 0 2021-09-29 2111

Machine Learning, Artificial Intelligence (AI), and Big Data are all concepts that have been around for a long time. However, the capacity to apply algorithms and mathematical calculations to massive data has only lately gained traction. The most important aspect of artificial intelligence is machine learning. Without clear programming, it causes computers to enter a self-learning state. When fresh data is served by machine learning, these computers learn, grow, change, and develop on their own.

Machine Learning is the most intriguing subject in recent times, and it has been around for quite some time. However, the ability to perform mathematical calculations to large amounts of data frequently and fast is currently ahead of the curve. Machine learning is now being used in applications such as the self-driving Google car, Facebook friend recommendations, online recommendation engines, Amazon offer suggestions, and cyber fraud detection.

Artificial intelligence's fundamental subfield is machine learning. It allows computers to enter a self-learning state without having to be explicitly programmed. These computers learn, grow, adapt, and develop on their own when given fresh data. Data science is a broad, interdisciplinary field that makes use of the vast amounts of data and processing power at its disposal to generate insights. Machine learning is one of the most interesting tools in modern data science. Machine learning allows computers to learn on their own from the vast amounts of data accessible.

These technologies have a wide range of applications, but they are not limitless. Though data science is strong, it can only be used effectively if you have highly trained workers and high-quality data.

Importance of machine learning

Machine Learning is becoming increasingly popular across many industries. High-value forecasts that can lead better judgments and smart actions in real-time without human intervention are one of the main reasons why data scientists require machine learning. Furthermore, machine learning technology aids in the automated analysis of enormous amounts of data, easing the responsibilities of data scientists, and is acquiring a lot of relevance and attention. By involving automatic sets of general methods that have superseded old arithmetical techniques, ML has the potential to transform the way extraction and comprehension work.

Simply said, everyone contributes to Machine Learning through their everyday online interactions. Whether you're looking for a coffee maker on Amazon, "best tips to lose weight" on Google, or "friends" on Facebook, you're seeing Machine Learning in action. It is thanks to Machine Learning that Google, Amazon, and Facebook can provide users with relevant recommendations. With the use of machine learning technology, these corporations can keep track of your daily activities, search habits, and purchase preferences.

With evolution comes an increase in demand and significance. ‘High-value forecasts that can drive better judgments and smart actions in real-time without human interaction,' is one key reason why data scientists need machine learning. Machine learning is getting a lot of traction and recognition as a technology that helps evaluate vast amounts of data and automates the jobs of data scientists. By involving automatic sets of generic approaches that have superseded traditional statistical techniques, machine learning has transformed the way data extraction and interpretation works.

Machine learning is being used in a variety of fields. Allowing a machine learning algorithm to make decisions can be a cost-effective solution to a variety of issues. The use of these approaches in businesses such as financing, hiring, and medical raises serious ethical questions. These algorithms add social biases into their outcomes since they are trained on data generated by people. These biases may be disguised because machine learning algorithms work without explicit guidelines. Currently, certain machine learning algorithms are a "black box." Google is working on improving our understanding of how neural networks "think."

However, before it can solve data bias and other ethical challenges with machine learning, this research may need to go further. When it comes to data science and machine learning, where do they meet? Machine learning is one of the many tools at a data scientist's disposal. A professional data scientist who can organise data and apply the appropriate tools to properly utilise the numbers is required to make machine learning work.

How much is machine learning changing the data analysis landscape?

The experimental and error approach of data analysis has traditionally been used – a method that becomes impractical to apply when dealing with large and diverse data sets. Big data was evaluated for promotion precisely for this reason. The difficulty of bringing in new analytical models that work precisely is directly proportionate to the availability of more data. Static analysis, which is limited to the examination of samples that are solid in time, is more important in traditional statistical solutions.

Enough of this could lead to shaky and imprecise findings. Machine learning is capable of providing precise findings and analysis by generating efficient and fast algorithms and data-driven models for real-time data processing.

How did data science become so popular in the machine learning world?

Machine learning and data science are inextricably linked. Machine learning is defined as a machine's ability to extract knowledge from data. Machines can't learn much if they don't have any data. If anything, the growing use of machine learning in a variety of industries will act as a catalyst for data science to grow dramatically. Machine learning is one of the best because of the data provided and the algorithms' ability to ingest it. Data scientists will be expected to have a basic understanding of machine learning.

There's no shortage of exciting stuff to do in data science, from shiny new algorithms to toss at data. What it lacks, though, is an understanding of why things operate and how to tackle non-standard situations, which is where machine learning comes in.

What is the definition of Data Science?

Data science is an interdisciplinary approach to obtaining useful insights from today's organisations' massive and ever-increasing volumes of data. Preparing data for analysis and processing, undertaking advanced data analysis, and presenting the results to expose trends and allow stakeholders to make educated decisions are all part of data science. Cleaning, aggregating, and modifying data to prepare it for specific sorts of processing are all examples of data preparation. Analysis necessitates the creation and application of algorithms, analytics, and AI models.

It's powered by software that sifts through data in search of patterns, then converts those patterns into forecasts to aid commercial decision-making. These forecasts' accuracy must be confirmed by carefully prepared tests and experiments. And the findings should be disseminated through the effective use of data visualisation tools that allow anyone to detect patterns and recognise trends. There is no limit to the number or types of businesses that could benefit from the opportunities created by data science. Data-driven optimization can make virtually any company process more efficient, and greater targeting and customisation can improve nearly any form of customer experience (CX).

Who are Data Scientists?

Big data wranglers, data scientists acquire and analyse enormous sets of organised and unstructured data. A data scientist's job entails a mix of computer science, statistics, and math. They interpret the outcomes of data analysis, processing, and modelling to generate actionable plans for businesses and other organisations. Data scientists are analytic professionals that use their knowledge of technology and social science to identify patterns and handle data. They identify solutions to corporate difficulties by combining industry knowledge, contextual insight, and scepticism of established assumptions.

A data scientist's job entails deciphering jumbled, unstructured data from sources like smart devices, social media feeds, and emails that don't fit neatly into a database.Data scientists (as data scientists are known) require computer science and pure science skills in addition to those required of a standard data analyst. The following skills are required of a data scientist:

Use mathematics, statistics, and the scientific method to solve problems.
For reviewing and preparing data, use a variety of tools and approaches, ranging from SQL to data mining to data integration methodologies.
Predictive analytics and artificial intelligence (AI), including machine learning and deep learning models, are used to extract insights from data.
Create software to automate data processing and calculations.
Tell—and illustrate—stories that effectively communicate the meaning of results to decision-makers and stakeholders at all levels of technical expertise.
Explain how these findings can be applied to business issues.

Data Analyst and Data Scientist: Differences and Similarities

A bachelor's degree in a quantitative discipline such as mathematics, computer science, or statistics is required for both career routes. A data analyst may devote more time to routine analysis and report generation. The method data is kept, handled, and evaluated can be designed by a data scientist. Simply defined, a data analyst interprets current data, whereas a data scientist develops new methods for acquiring and analysing data that analysts can use.

Both paths could be a good fit for your career ambitions if you enjoy numbers and statistics as well as computer programming. An analyst's job is to answer specific questions concerning the company's operations. A data scientist might work on a larger scale to come up with innovative approaches to ask and answer crucial questions.

Despite the fact that each function is focused on evaluating data to get actionable insights, the tools they utilise can sometimes define them. It assists data analysts in mastering relational database software, business intelligence tools, and statistical software. Python, Java, and machine learning are commonly used by data scientists to modify and analyse data.

The function and responsibilities of a data analyst or data scientist vary based on the sector and area where they work. A typical day for a data analyst can include determining how or why something happened, such as why sales plummeted, or designing dashboards to support KPIs. Data scientists, on the other hand, are more interested in what will or could happen, and they use data modelling techniques and big data frameworks like Spark to do so.

Data Scientists:

Scrubbing data might take up to 60% of a data scientist's effort.
Using APIs to mine data or creating ETL processes.
Using programming languages to clear data (e.g. Python or R).
Natural language processing, logistic regression, kNN, Random Forest, and gradient boosting are examples of machine learning techniques used in statistical analysis.
Using tools like Tensorflow to design and train machine learning models, creating programming and automation techniques, such as libraries, that ease day-to-day tasks.
Using Hadoop and Spark, as well as technologies like Pig and Hive, to build large data infrastructures.
The salary of a data analyst or data scientist can vary by industry and employer.
If you are interested in machine learning or big data, you may want to pursue a data science degree.
The data scientist path focuses on learning frameworks for processing, analyzing, modeling, and inferring from data. A data scientist can use a data lake to manage unstructured data for analysis.

Data Analysts:

SQL is used to query data.
Excel is used for data analysis and forecasting.
Using business intelligence software to create dashboards.
Performing descriptive, diagnostic, predictive, and prescriptive analytics, among other forms of analytics.
A data analyst can start out in an entry-level role where their main responsibilities are reporting and creating dashboards.
If you are interested in data processing and statistical modeling, a degree in data analysis might be for you. In some cases, a data analyst can continue their training and hone their skills as a data scientist.
A data analyst can learn to use statistics, analytics technology, and business intelligence to answer questions specific to the business.

The Top Skills You'll Need to Become a Machine Learning Expert

Every Data Scientist needs the following four talents to become an expert in Machine Learning.

1. Comprehensive understanding and expertise in computer foundations. Computer organisation, system architecture and levels, and application software are only a few examples.

2. Because Data Scientists' work entails a lot of estimation, having a good understanding of probability is essential.

3. Another area where they should concentrate is statistics analysis. For examining distinct data objects and how they interact with one another, data modelling is used.

4. Programming abilities and a thorough understanding of programming languages such as Python and R are required. A quest to understand different database languages other than traditional SQL and Oracle, such as NoSQL.

5. Common skills used by both data analysts and data scientists include data mining, data warehousing, math, statistics, and data visualization.

Importance of Machine Learning for Data Scientists

The most important aspect of artificial intelligence is machine learning. Without clear programming, it causes computers to enter a self-learning state. When fresh data is served by machine learning, these computers learn, grow, change, and develop on their own.

Data scientists are on a mission to become machine learning masters as the demand for the technology grows. Machine learning is expected to provide a lot of value to data scientists in the future. Before diving into the significance of machine learning for data scientists, there are a few things to keep in mind. The development of smartphones and digitization has transformed human life into a data collection endeavour.

People click on thousands of things on their smartphone every day, creating quintillions of data, whether they realise it or not. Meanwhile, Moore's Law - the premise that computing power would drastically rise while relative cost decreased over time – has made cheap computing power broadly available. The void between these two advances is filled by data scientists. In recent years, the function of data scientists has become increasingly important. Traditional businesses who previously did not devote a significant portion of their resources to technology employees are now hiring skilled data scientists to better their decision-making and analytic processes.

Machine learning, on the other hand, allows computers to enter a self-learning mode without the need for explicit programming. The great majority of artificial intelligence developments and applications that we hear about today are due to machine learning algorithms. Machine learning algorithms typically employ statistics to detect patterns in large amounts of data. The data includes a variety of elements such as numbers, text, photos, clicks, and so on.

Machine Learning's Benefits for Data Scientists

Every day, new technologies arise in our fast-changing environment. The majority of the new approaches that emerge as a result of technological advancements are designed to replace humans in their typical hard-labour employment. Machine learning is at the heart of accelerator technology that allows machines to mimic human intelligence and capacities.

Machine learning's increased use in various industries will act as a stimulus for data science to become more relevant. Because data scientists' job entails making people' jobs easier through data analysis and insights, they should be familiar with machine learning for quality prediction and estimation. This can assist machines in making better decisions and taking smarter actions in real time, without the need for human intervention.

Furthermore, machine learning is assisting data scientists on a small scale by revolutionising data mining and interpretation. Traditional statistical procedures have also been superseded by more accurate automatic sets of generic algorithms. Basic machine learning skills will become a need for data scientists in the future. Every data scientist should be knowledgeable of the following four machine learning techniques.

1. Computer foundations, such as computer structure, system architecture and levels, and application software, should be known and understood by data scientists.

2. Because data scientists' work entails a lot of estimation, they need to know a lot about probability. They should also concentrate on statistical analysis in order to improve their performance.

3. Data scientists should plan through data modelling, which is used to examine and interact with diverse data objects.

4. Programming abilities and a thorough understanding of programming languages such as Python and R are key skills for data scientists.

Conclusion

Data is extremely important. To produce insights and make sense of data, science draws together subject expertise from programming, maths, and statistics. When we consider why data science is becoming more essential, we must consider the fact that the value of data is increasing.

Data scientists use their experience in a range of data niches to assist companies in interpreting and managing data and solving complex problems. They usually have a good business sense and a basis in computer science, modelling, statistics, analytics, and arithmetic. Companies that hire data scientists, in particular, have the opportunity to improve marketing by providing personalised campaigns and advertisements based on customer behaviour, to improve innovation by analysing through a thorough understanding of customer needs, and to enrich lives by assisting consumers in their personal lives.

Machine learning is omnipresent, from Netflix, YouTube, and Spotify's recommendation systems to Facebook and Twitter's social media feeds. Businesses may use machine learning to save expenses and create profitable solutions to a variety of issues. Machine learning is one of the many technologies that data scientists have at their disposal. However, when new strategies emerge from machine learning, it is becoming increasingly important for them.

Machine learning and data scientists are already inextricably connected. While data science focuses on data scientists solving large data chores like data preparation, cleansing, and analysis, machine learning consists of machines that train on a set of data using a set of algorithms. To perform better as a data scientist in the future, those in the field should embrace machine learning with open arms. The article titled “The importance of machine learning for data scientists” will help the budding data scientists to build a great future for themselves in the field of machine learning. This will not only help them in their profession but will add a great asset to their career as well.

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Sep

Key Steps to Define Project Scope for Successful Planning

iCert Global Project Management 0 2021-09-28 1503

Whether a company is building bridges, software, or cell phones, the work involved in these finished products is managed as a series of projects with specific goals, schedules, and budgets. A project management plan is critical to ensuring teams complete their work on time and as expected. But before project managers can come up with a detailed plan and a project team can execute that plan, everyone must know what work needs to be done and why it is important.

Every aspect of a project's execution is influenced by its scope. It's critical to understand how the scope of a project will affect your schedule and, eventually, the outcome, in order to finish it efficiently. The whole shape of the task will become obvious when you begin to define project scope and designate what responsibilities each member of your team is responsible for. In this post, we'll explain what establishing project scope comprises, go over the many parts required, and walk you through the process.

This is where the project scope statement comes in. A project scope statement provides a detailed description of the work that must be done to deliver the results of a project on time and within the allotted budget. The document also places the goals and results of the project, this could be a product that a company brings to market or an analysis that uses leadership to make an informed business decision, in the broader context of the goals and objectives of the company. company.

Defining scope for a project

Capturing project scope cannot be overestimated as the project will not achieve the desired results without a well documented and agreed vision. The scoping process requires careful organization and a series of steps.

The time it will take to complete the project, the resources required to complete it, and the precise tasks for which each team member will be responsible are all part of the project scope. The project scope must be calculated by the project manager, approved by upper management, and communicated to the rest of the team before work on the project may begin. The scope will need to be checked often throughout the project to keep the team on track. The scope will also guide the project manager's decisions on how to deal with any issues or bottlenecks that arise.

Image source:- https://www.b2bwritingsuccess.com/2015/01/project-management-defining-project-scope/

Aspects to consider while defining scope for a project

The scope of a project is defined by a number of factors. While the general documents normally follow a pattern, the specifics will depend on the nature of the project, the timetable, and the culture of your firm. The following are aspects of defining project scope:

1. Work description - The creation of a statement of work is the first stage in establishing project scope. The official document that describes the criteria for a certain project is known as a statement of work. It contains a broad description of the task being asked, as well as a deadline, a schedule, any unique talents required, and the location of the job. A statement of work gives managers the information they need to assess expenses and make a proposal.

2. Statement of the Project's Scope - A project scope statement responds to the statements of work's requests and gives the particular information required to accomplish the project. The statement specifies the number of personnel needed for the job, the location where it will be accomplished, the time it will take, and the quality of the final outcomes. Scope statements determine the project's boundaries and ensure that all team members stay on track throughout the project's lifetime.

3. Breakdown of work structure - The work breakdown structure is a document that helps project team members share work effectively. Throughout the project's duration, the work breakdown structure ensures that each department, team, or individual understands exactly what is expected of them. The work breakdown structure also assigns specific job lists to the relevant teams or team members, ensuring that they are not overburdened with information.

7 Steps are involved in defining scope for a project

Step 1. Identify the need of the project:-

If you can identify the needs of a project, you are more likely to establish a solid benchmark from the beginning. Understanding the "what and why" of a project can help you set specific goals. It also lays the groundwork for what tasks should be followed and how they should be performed.

Step 2. Verify the goals and objectives of the project:-

The basis of the project scope should include your objectives and follow a SMART guide. That is, be specific, measurable and achievable. It must also be realistic and completed within a specified time frame.

Time frame - Can the goals and objectives of your project be achieved within the established timeframe? Is meeting these deadlines an important criterion?
Measurable - Are your goals and objectives capable of providing feedback and being accountable?
Specific - This includes specifying exactly what the project will accomplish. That is, what, why and how they are done. Clarity reduces the likelihood of confusion and misunderstandings.
Achievable - Can the objectives of your project be achieved with the resources available?
Realistic - Are goals and objectives easy to achieve, especially when faced with problems or complications? Will this affect the overall quality of the project output and lead to over budget and missed deadlines?\

Step 3. Project Scope Description:-

As a manager, you must be clear about the characteristics and functions required for your product or service. For instance, you are creating a website. You need a list of details about your website structure, branding requirements, etc. In other words, what qualities make your project a success.

Step 4. Acceptance and Expectations:-

Successful projects take into account the satisfaction of the end user. If they meet the expectations of the end user and accept the product, service or process. End users can be your customers or your internal team.

For customers, this includes prices, value, and quality of products / services, as well as availability, delivery, and return guidelines. For employees, this includes the effectiveness and efficiency of new operating processes. Ultimately, the scope of your project should be geared towards delivering better results to your end users.

Step 5. Identify Constraints:-

There are always obstacles to what you set out to do. Being aware of potential limitations along the way can minimize problems that may delay or limit your ability to achieve your project outcome.

These can be caused by dynamic environmental conditions (internal and external), technological disruptions and / or lack of resources. Communicating these issues with your team early on and taking steps to overcome these hurdles can reduce project completion delays and keep expenses on budget. Regardless of whether they are based on assumptions or uncertainties, analyzing their impact during the project period further reduces the risk of failure.

Step 6. Verify necessary changes:-

It is always best not to review the scope of your project as it will mean more time, money and resources. However, sometimes these changes are inevitable and necessary. Limit changes by taking the perspective of customers, stakeholders, and project collaborators.

This minimizes later disagreements.

Step 7. Involve the appropriate stakeholders:-

The right stakeholders from the firm commissioning the project must be well-informed at specific crucial moments for the project to be delivered successfully. If stakeholders aren't adequately included, it might lead to misaligned goals and assumptions. The project will run more smoothly if the correct people are involved and kept updated throughout the process.

Conclusion

The first stage in creating a project timeline, allocating project resources, and setting project goals is defining the project's requirements. Only by following these procedures will you be able to comprehend the work that has to be done, i.e., the project's scope must be specified. After then, team members can be assigned jobs and given instruction in order to complete a project within the time and budget constraints.

After these characteristics have been determined, the project's restrictions must be clarified, as well as the components that will not be included in the project. Stakeholders, senior management, and team members will be able to see what will and will not be included in the final product or service if this is done. Furthermore, the project's scope should have a measurable goal for the entity that is carrying it out. This is critical for the project's scope since it will influence how project approaches are used to execute it.

Some common flaws with Project Scope Management might cause challenges once the project has started. These include:

Ambiguity in scope can lead to a lot of wasted time and confusion. To avoid this, the scope must be specific and well-defined.
Incomplete scopes result in schedule slippages, which in turn result in cost overruns. To avoid this, the scope must be comprehensive and precise.
Scope creep is the primary cause of late delivery and “never-ending” projects, and it is caused by transient scopes. To avoid this, the scope document should be finalised and left unchanged throughout the project.

To guarantee that stakeholders and team members alike understand the scope of the project and agree on how the project goals will be fulfilled, effective project scope management necessitates clear communication. These 7 steps are involved in defining project scope and it will help many people in their profession.

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Sep

Top 10 essential skills you need to become an ethical hacker

iCert Global Emerging Technology 0 2021-09-27 2980

Anyone with advanced computer technology abilities who can trick organisations or breach security and access networks without necessary authorisation is referred to as a "hacker." Some hackers use their expertise to commit fraud, theft, or other illegal activities, while others simply love the challenge.

Compromising computer systems for the purpose of analysing security and acting in good faith by informing the susceptible party is what ethical hacking is all about. Many professional jobs involving securing an organization's internet assets require ethical hacking as a fundamental skill. Professionals in these professions keep the organization's computers, servers, and other infrastructure components in good operating order, preventing illegal access through non-physical means.

It takes time and money to recover from a cyberattack, and there's no assurance that a hacked company will recover at all. Data breaches, in particular, can harm a company's reputation with consumers and clients, and might even result in legal action. That's why ethical hacking abilities are so important for any company with a significant online presence. People mistakenly believe that "hacking" entails breaking into any website in under a minute. They don't even understand the basic concept of what it means to hack or how to accomplish it because they learned it from movies. In reality, it is much different than what it appears.

Top 10 Skills to Become an Ethical Hacker are:

Computer skills
Skills in Computer Networking
Linux Expertise
Skills in Programming
Malware
Reverse Engineering
IoT Device Security
Cloud
Thinking Analytically
Knowledge of databases

What Does Being an Ethical Hacker Entail?

In many ways, an ethical hacker is similar to a secret shopper who goes into stores undercover to find flaws and provide comments on what needs to be improved. To test a store's security, secret shoppers may even stage shoplifting instances. Similarly, ethical hacking skills—which are essentially identical to those used by cyber criminals—are beneficial to businesses looking to identify vulnerabilities, strengthen their networks, and improve their processes.

While corporations frequently hire penetration testers to focus on one or a few specific network vulnerabilities, ethical hackers play a far larger role. They may also try to dupe staff into divulging critical information, test whether laptops and mobile devices are securely secured and safeguarded, and investigate all possible methods a "black hat" hacker would try to cause havoc.

Top 10 skills of an Ethical Hacker

1. Computer skills:

Computer skills refer to the knowledge and abilities required to operate computers and related technology. Data processing, managing computer files, and making presentations are all examples of fundamental computer abilities. Database management, programming, and spreadsheet calculations are examples of advanced computer skills. MS Office, Spreadsheets, Email, Database Management, Social Media, Web, Enterprise Systems, and other computer skills are among the most important. A computer systems specialist is required of an ethical hacker.

2. Skills in Computer Networking:

Networking abilities are one of the most critical talents to have if you want to be an ethical hacker. The computer network is simply the interconnection of several devices, known as hosts, that are connected via multiple pathways to send and receive data or media. Understanding networks such as DHCP, Supernetting, Subnetting, and others can allow ethical hackers to investigate the many interconnected machines in a network, as well as the potential security concerns that this may pose, as well as how to deal with those threats.

3. Linux Expertise:

The Linux Kernel provides the foundation for a community of open-source Unix-like operating systems. It is a free and open-source operating system, and the source code can be updated and distributed to anybody under the GNU General Public License, whether commercially or non commercially. The key reason to study Linux as an ethical hacker is that it is more secure than any other operating system in terms of security. This is not to say that Linux is completely secure; it does have viruses, but it is less vulnerable than any other operating system. As a result, no anti-virus software is required.

4. Skills in Programming:

Programming skills are another crucial ability for becoming an ethical hacker. So, in the computer world, what exactly does the term "programming" mean? It's defined as "the act of writing code that a computing device can understand in order to carry out various commands." So, in order to improve one's programming skills, one must write a lot of code! Before beginning to write code, one must first determine which programming language is suitable for their needs. The following is a list of the most commonly used programming languages by ethical hackers:

Python
SQL
C Programming Language
JavaScript
PHP
C++
Java
Ruby
Perl

5. Malware:

Ethical hackers must be familiar with many types of malware, as well as how they can be utilised to obtain access to a system and the most recent varieties of malware. Malware will be used by hackers either to obtain access or to corrupt and steal data once they have. Ethical hackers can create their own malware or use malware toolkits developed by others.

6. Reverse Engineering:

A term used to describe the process of recovering a product's design, requirement specifications, and functionality from an analysis of its code is known as reverse engineering. It creates a software database and uses it to generate data. The goal of reverse engineering is to speed up maintenance work by making a system more understandable and producing the essential documents for a legacy system. Reverse engineering is commonly employed in software security to ensure that the system is free of severe security flaws or vulnerabilities. It aids in the development of a system's sturdiness, hence safeguarding it from hackers and spyware.

7. IoT Device Security:

Because IoT devices are frequently vulnerable, they are a great target for hackers looking to get access to a company's network. Mobile devices are especially common because practically everyone owns one, and they are frequently directly connected to a company's network via WiFi. Hackers should be conversant with tools like Wireshark, BinWalk, and SAINT, which are used to extract data and acquire access.

8. Cloud:

To collaborate on documents, run programmes, and back up their data, most businesses rely heavily on the cloud. Hackers, on the other hand, can use the cloud to gather information and develop an attack platform. Because enterprises assume that the cloud provider is responsible for security, free cloud platforms are particularly vulnerable. Ethical hackers should be familiar with all of the major cloud platforms, including Amazon Web Services, Google Cloud, and Microsoft Azure.

9. Thinking Analytically:

Hacking necessitates both a creative and analytic mindset. Ethical hackers must be able to deconstruct security frameworks and devise novel techniques to breach a network. This also necessitates thinking outside the box – social engineering is a prevalent strategy used by both white and black hat hackers to get access to restricted places, and it employs psychological techniques.

10. Knowledge of databases:

The database management system (DBMS) is at the heart of all database creation and management. Because accessing a database containing all of the firm's data can put the organisation at risk, it's critical to ensure that the software is hack-proof. To assist the organisation in building a powerful DBMS, an ethical hacker must have a comprehensive understanding of this, as well as different database engines and data structures.

Conclusion

Ethical hackers can work as freelance consultants, for a firm that specialises in simulated offensive cybersecurity services, or for a company's website or apps as an in-house employee.

For a member of a cybersecurity team, a history of cybercrime constitutes an unacceptable danger. This type of risk would be unacceptable to a huge corporation with an experienced legal staff. When applying for work as an ethical hacker, a resume that includes any activity that even smells like unlawful labour or unethical behaviour is a surefire way to be denied. While people can change over time, most employers recognise that adopting a set of ethical life-guiding values entails far more than simply wanting to change careers.

Although an offensive security professional is a better definition, ethical hacker is frequently used to characterise this type of security expert since, let's face it, ethical hacker sounds more mysterious. Regardless of whether the term "hacker" appears in the job description, these positions are not for the ethically dubious, and especially not for someone with a history of bad behaviour. Ethical hackers must have access to sensitive information, which if leaked might be disastrous for the company. For government personnel and contractors, a security clearance is frequently necessary. A background investigation and an analysis of financial and social media data will be required to obtain a security clearance. These top 10 skills of an ethical hacker will teach many ethical hackers who want to work in a professional way.

While there are examples of self-taught gritty individualists dragging themselves up by their digital bootstraps to the summit of cybersecurity ops throughout history, the standard for ethical hackers is a bachelor's degree along with one or more specialised professional certificates. Successful ethical hackers typically have years of mettle-testing experience in software development and/or more traditional defensive security roles. The elaborated article titled “What ethical hacking skills do professionals need?” will teach you some ethical hacking skills in a professional way.

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Sep

Types of Organizational Structures in Project Management

iCert Global Project Management 0 2021-09-24 2657

Project management structure is critical to any project team's performance; a structured organisation or project team provides support for the job that is being done. Project management teams or organisations that are not aligned have a detrimental impact on the project's outcome. This is due to the fact that the project manager's authority is influenced by the organisational structure, which has an impact on how projects are managed.

Non-structured project management teams, by definition, lack guidance, but a directed team leads to successful projects. The organizational structure is the standard hierarchy of activities. It defines how to divide, coordinate and lead groups. In addition, it defines the position and describes the tasks required to achieve the organization's goals and vision.The organizational structure is not static, but adjusted according to the organization's scale, needs, and ideas.

In this article, you will learn about the different types of organizational structures and their working principles in project management. Within an organisation, an organisational structure can be defined as the official line of power and control. The reporting relationships in a company's project management structure tell us how they work. Depending on the context in which the organisation operates, the goals it sets for itself, and the type of the job being done. The several types of organizational structures in project management will help employees to grow an organization as well for the growth of their business.

8 common types of organizational structure in Project Management are:

Line Organization
Functional Organization
Project Organization
Virtual Organization
Matrix Organization
Divisional organization
Organic or Simple Organization
Line and Staff organization

Elements of organizational structure in Project Management

When choosing an organizational structure, certain characteristics should not be overlooked. The main elements that contribute to the establishment of an appropriate organizational structure are as follows:

Physical locations
Simplicity of design
Accountability assignment
Delegation of capabilities
Degree of alignment with organizational objectives

8 common types of organizational structure in Project Management

1. Line Organization:-

This is the simplest form of organizational structure you will find in a small business. It has a clearly defined level of authority in the hierarchy. Power flows from top to bottom to different levels of the company or workers.The hierarchical structure clearly defines the power, responsibility, and accountability at all levels. Because of its simplicity, authorization and responsibilities are transparent and easy to understand. As employees receive quick feedback and react quickly, communication becomes quick and easy.

The project manager performs tasks according to the position or authority in the hierarchy. Some organizations do not have this position, but when they have this position, they may have little or nothing to do.

2. Functional Organization:-

The functional organization groups workers according to their profession. This structure is an extension of linear organization. The functional manager leads the team and manages any operation or business. The head of the functional organization executes instructions within a clearly defined scope of responsibility. This concept comes from Fredrick W. Taylor. Here, you can classify employees according to their functional roles and departments. Some general divisions below are:-

Customer Service
Sales
HR
Finance
Supply chain, etc.

The head of the organization is the president, followed by the vice president, and the chain continues. In addition, department heads made predictions about their department performance. Together, they help organizations control quality and consistency.

This structure positions the department vertically and separates it from other departments. Hence the name "Silos". The head of the department controls the communication between the senior management and their subordinates. The role of the project manager is small, or there may not be a specific position. Typically, you act as an accelerator or coordinator. As a functional manager, you have to deal with -

Decision making
Budget Allocation
Resource Allocation

This type of organization is suitable for manufacturing or engineering companies. It supports the daily operations and practices of manufacturing standard products.

3. Project Organization:-

Project organization is a temporary facility set up for a specific project. It is also referred to as the "projectized organizational structure". The project manager assigned to the project is the person in charge of the structure. After the project is completed, you can immediately cancel this setting or move it to a new project.

If it is a new project, the project manager may need to rearrange employees to adapt to the new plan. You hire resources or experts from different functional departments. As a project manager, you can use the allocated resources until completion and completion.

Although you are responsible for the timely completion of all activities and projects. In other words, you need to spend according to the project budget. The manager assigns clear tasks to each team member and has a complete timetable. These types of organizations are useful in the following situations:

Project is unique and independent
The scope of the project is complete and the objectives are clear

4. Virtual Organization:-

Virtual organization is a new development that spans different locations. If your team runs a project in one area, you can manage it from anywhere else. In this way, you can allocate resources to your project team regardless of location. You can connect to almost any location. The other name of this organizational structure is:

Modular Organization
Network Organization
Digital Organization

ICT (Information and Communication Technology) is the support of virtual organizations. The virtual organization is a social network without vertical and horizontal boundaries.

The resource is not bound to a specific workstation (desk). You can also work from any mobile device. You can manage almost any project activity, including meetings. The team reports digitally, unless in some cases a physical meeting is required. Therefore, virtual offices, virtual teams and virtual leaders are often heard. This setting is most suitable for software or IT companies.

5. Matrix Organization:-

This is a combination of planning organization and functional organization. This hybrid organization overcomes the boundaries of any organization. Here, functional managers and project managers share their respective powers. Project Managers are usually responsible for:

Execution of the project
Completion of project activities
Project Planning
Overall Integration

All activities must be carried out using allocated resources. The functional manager handles the operational aspects of the project. You are also responsible for providing technical advice. Technicians specialize in the skills required for the project. Although the project manager leads the project staff, the functional manager controls the process. This type of organization is most useful when employees need to share available resources.

This combination achieves high efficiency and better utilization of available resources. They are also better able to adapt to changing trends. You can divided Matrix Organization into:-

Weak
Strong
Balanced

The power shared by functional managers and project managers determines their strength.

6. Divisional organization:-

This type of organization is usually similar to a functional organization. Team members work in different departments. This setup divides employees into multiple market segments based on products, markets, or services. However, the divisional organization’s segments or divisions are autonomous. The functional units supporting this structure include:

Operations
Personnel
Marketing
R&D Department

This design focuses on service lines such as product, customer, region, and time. Because they operate as small organizations, they are called "independent structures."

So your independent work area target. But all departments jointly meet the company's guidelines and business goals. This type of organization is suitable for the following companies:

Banking and insurance business
Chain stores with Subsidiaries
Operate in different geographical location

7. Organic or Simple Organization:-

This type of organization is very flexible and can adapt well to market changes. This structure is characterized by fewer regulations and management levels, and decentralized decision-making. The organic organization is designed to respond well to the rapidly changing environment. People work side by side to communicate quickly and often solve unforeseen problems, problems, and requirements. The project manager has little or no authority here, and may or may not have a specific job role.

8. Line and Staff organization:-

The line and personnel organization are modifications of the line organization. Here, experts work with line managers to provide them with guidance and advice. This structure is more common today, and most large organizations use this type of list. The employees are divided into two categories; General and Professional teams.

General employees - Ordinary or general employees consist of simple employees who support senior management. These people are not experts.
Professional employees - The team is composed of experts who provide services to the organization. Their role can be advisory, control (such as quality control) or service (such as maintenance). Th line and employee organizations use the expertise of experts. In this way, the managers can become better in several ways.

These are the total 8 types of organizational structure in project management.

Wrapping up

Through different types of organizational structures, it is easy to know what you need. Although each structure has its limitations, a large and complex organization has taken over the matrix organization. Lines and staff organizations are clearly structured. Therefore, it is used for simple organization. Software or information technology companies usually use virtual organizations.

Even if you choose the right organization, type will ensure that you are doing well in the market. This elaborated article “Types of organizational structures in project management” will help employees to create a good structure in their project for the betterment of their organization.

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Sep

Top 10 AI applications transforming industries and life.

iCert Global Emerging Technology 0 2021-09-23 1898

When most people hear the word Artificial Intelligence, they immediately think of robots or a popular science fiction film such as The Terminator, which depicts AI's rise against humans. However, it isn't even close to the current state of AI. Artificial Intelligence is a discipline of computer science that aims to imbue human intelligence into machines or computers so that they can perform human-like functions and jobs. Artificial Intelligence (AI) is a breakthrough technology that has broadened the scope of technology and accelerated developments in this sector. It is concerned with human activities such as human thought processes, information processing, and data interpretation.

Learning, reasoning, and perceiving are all goals of AI. AI, in conjunction with these goals, instructs computers to do human-like functions using techniques such as Deep Learning and Machine Learning. AI is everywhere in the modern digital era, from self-driving automobiles to the production of captcha text on website portals.The top 10 artificial intelligence applications will help you to learn more about AI.

When it comes to technical growth, Artificial Intelligence plays a huge role. AI has revolutionised several sectors with its sophisticated innovations and adaptable strategies, involving various fields and industries in the world of technology. Despite the criticism it has received over time, AI remains a topic of discussion among academics and scientists all over the world. Artificial intelligence has a long history dating back to the mid-nineteenth century. What began as a hypothetical circumstance has evolved into a real-life example that affects people's lives on a daily basis. While few people believe that machines will ever be able to govern how humans function.

Top 10 Real World Artificial Intelligence Applications are

1. Outer-space Exploration

2. Finance and Stock Market

3. Digital Media

4. Medical care Industry

5. Fitness Apps

6. Face recognition

7. Automated cars

8. Virtual Voice Auxiliaries

9. Robotics

10. Customer Service

Pros and Cons of Artificial Intelligence

Here's a quick rundown of the benefits and drawbacks of artificial intelligence that we should all be aware of.

Pros of AI

Potentially Massive - One of the most significant advantages of artificial intelligence is its enormous potential. AI is known for its cutting-edge technology, which engages numerous businesses and sectors through new approaches such as Machine Learning and Deep Learning.
Excellent all-around performance - Machines, unlike humans, do not require rest. Artificial intelligence allows computers to work indefinitely and around the clock, resulting in more efficient output. When compared to human abilities, AI's 24x7 work cycle is extremely favourable.
Results that are free of errors - Another advantage of AI is that it generates results that are error-free. Humans are prone to errors and mistakes when doing manual work, whereas machines with artificial intelligence are extremely efficient. This produces error-free results that would otherwise be a significant agony for people.

Cons of AI

Architecture Is Expensive - One of the disadvantages of artificial intelligence is that it necessitates costly infrastructure to function. Even though this is a one-time cost, AI can be a significant investment for many firms and people.
Unemployment in the Workforce - “Machines have taken the place of men, and materialism has taken the place of hard labour.” Since the introduction of machines, Artificial Intelligence has been the source of mass unemployment. While AI is likely to increase in the future, it will inevitably result in more human unemployment, which is a big disadvantage.
Patterns that aren't dynamic aren't present - Machines rely on data rather than intuition to function. Another disadvantage of AI is the lack of dynamic patterns, which suggests that robots are merely consistent in their task performance. Despite their ability to mimic human behaviour, machines still fall behind in terms of creativity.

The Four Types of AI

1. Machines that react

This type of AI is solely reactive, with no ability to develop "memories" or make judgments based on "previous experiences." These devices are made to carry out specific duties. Programmable coffeemakers and washing machines, for example, are built to fulfil specific functions but lack memory.

2. AI with a limited memory

This type of AI makes decisions based on prior experiences and current data. Because the machines have limited memory, they are unable to generate new concepts. They have a memory-running application built-in. Changes in these machines necessitate reprogramming. Limited memory AI is exemplified by self-driving automobiles.

3. Mind-Body Theory

These AI computers will be able to socialise and understand human emotions, as well as cognitively understand people based on their surroundings, facial traits, and other factors. Such powers have yet to be developed in machines. This sort of AI is the subject of a lot of research.

4. Self-Awareness

This is the way AI will develop in the future. These machines will be super-intelligent, sentient, and aware of their surroundings. They have the ability to react in a human-like manner, however, they are likely to have their own characteristics.

Top 10 Real World Artificial Intelligence Applications are listed below:

1. Outer-space Exploration:-

Artificial intelligence not only exists on earth but also exists in space! When it comes to the application of artificial intelligence, machines have travelled through space, allowing humans to explore space. Whether it is a Mars mission or an outer satellite device, artificial intelligence is constantly striding forward to space exploration. Some aspects involving the application of artificial intelligence to space exploration are mapping, satellite navigation, and location tracking technology.

2. Finance and Stock Market:-

Another list of artificial intelligence applications from the financial sector. With the help of artificial intelligence algorithms, machines can now interpret past stock market developments, analyze the profit and loss of related stocks, and even predict future stock market developments.

AI has been a major contributor in the financial field recently. One of the financial companies, Nomura Group, has successfully implemented artificial intelligence technology. In addition, artificial intelligence is seeking ways to enter financial processes, such as payment transfers, e-commerce platforms, and many other areas.

3. Digital Media:-

The Internet is everywhere, and so is artificial intelligence! Another use of artificial intelligence is digital media, which can help social media platforms check fake news, understand foul words hidden in comments or captions, and promote brands online. From these aspects of digital media and artificial intelligence, virtual platforms have emerged, and their users seem to know too well.

Have you ever wondered why when you look for a smartphone online, your Instagram will show you smartphone ads? Well, artificial intelligence is the answer. By interpreting data and analyzing the patterns hidden behind the user interface, artificial intelligence has adjusted our Google search engine, integrated various digital marketing tools, and provided us with exactly what we were looking for!

4. Medical care Industry:-

Medical care is a basic service for all citizens of the world. While doctors and scientists work hard from time to time to bring about a medical revolution, artificial intelligence does its part by making great contributions to the industry. The role of artificial intelligence in healthcare enables machines to interpret the patient’s medical history and predict possible diseases that individuals may be susceptible to in the next few years.

In addition, artificial intelligence facilitates drug discovery and the development of drugs that can cure harmful and even fatal diseases. AI's impact on the industry is huge. IBM Watson Health is a medical company that actively integrates artificial intelligence into the healthcare industry. It assists in research, data analysis and provides clients with medical solutions.

5. Fitness Apps:-

Fitness is everything that people desire today. From the number of steps you walk in a day to the number of calories you burn, fitness plays a huge role in our lives. And artificial intelligence! Artificial intelligence has formed an alliance with fitness and has promoted the release of fitness equipment, such as fitness bracelets and watches, to help people recognize their health, enhance their physical fitness, and achieve goals.

The role of artificial intelligence in this regard is to interpret the data that occurs every day and predict future data based on the data analyzed by the machine. One example is Fitbit, which trades with fitness bands powered by artificial intelligence.

6. Face recognition:-

Does your smartphone have facial recognition technology? If so, your smartphone is powered by AI. Are you thinking how is this possible? Well, applications of artificial intelligence include facial recognition, which focuses on learning and perceiving patterns to obtain fast and effective results.

So when you insert a selfie and register for face recognition, your phone will learn a face recognition algorithm. Next time you log in to your phone without entering a password, your phone will be easily unlocked by your photo. In addition to smartphones, airports, offices, etc. Face recognition is also used for other security and privacy purposes.

7. Automated cars:-

Artificial intelligence is how self-driving cars work. Self-driving cars are a typical example of artificial intelligence applications, explaining the progress in this field and the automotive industry. Driverless vehicles have recently gained traction, and Tesla has emerged as the frontrunner, with its AI-powered autonomous cars easily navigating the streets. Tesla's AutoPilot feature, which is backed by self-predictive skills, sets it apart from other self-driving technology companies. One of the most important artificial intelligence applications is Tesla's self-driving system.

The idea of self-driving cars with artificial intelligence algorithms is the future of the automotive industry. Large companies like Tesla are developing self-driving cars and are moving in this direction. Thanks to artificial intelligence, people no longer need to drive a car or hire a driver to do so.

8. Virtual Voice Auxiliaries:-

"Hey Alexa, explain the 8th application of artificial intelligence." Have you ever wondered how Alexa can do what you tell her to do? The answer is simple artificial intelligence. The design of virtual voice assistant devices such as Siri or Alexa incorporates technologies such as artificial intelligence and deep learning.

By enabling such voice assistants, artificial intelligence focuses on delivering human intelligence to these tools to help them perform human-like functions and tasks. Due to multiple modes and deep learning algorithms, such voice assistants have successfully followed human commands, making them a real example of artificial intelligence.

9. Robotics:-

As we all know, artificial intelligence is the driving force behind robotics. The use of artificial intelligence in robotics enables robots to appear in multiple industries such as finance, marketing, and healthcare. For years, robotics has been trying to integrate human intelligence into machines that can think and work like humans. A real example of this application is the Sophia robot. The robot Sophia is considered a "humanoid", a hybrid of humans and robots, with built-in functions of both.

10. Customer Service:-

Artificial intelligence also makes it easier to integrate machines into customer service. A computer designed to record feedback from various customers visiting major brand stores, shopping centres or showrooms. ML chatbot technology (bots that chat online with customers) is also one of the best AI applications to expand the scope of bots. By simulating the human behaviour and dialogue methods of marketers, chatbots interact with customers through online platforms.

For example, the e-commerce platform Amazon integrated chatbots into its customer service department. This is where customers are tricked into chatting with bots who want to resolve issues or disagreements related to purchases, orders, etc.

Implementation of AI Examples

Predictions Powered by AI at Google - Google Maps (Maps) may measure the speed of traffic movement at any given time using anonymized location data from cell phones. User-reported traffic occurrences, such as construction and accidents, can be more easily incorporated into maps.

Flights on Commercial Airlines Make Use of AI Autopilot. - Commercial airline AI autopilots are a relatively early application of AI technology, dating back to 1914, depending on how loosely you define autopilot. According to the New York Times, a Boeing plane's average journey includes only seven minutes of human-steered flying, which is usually reserved primarily for takeoff and landing.

Email Categorization That Works - Gmail takes a similar method to categorize your emails into primary, social, and promotion inboxes, as well as flagging essential emails. Gmail learns every time you flag an email as important.

Voice-to-Text - Voice-to-text is now a standard function on cell phones. You can start speaking by pushing a button or stating a certain phrase (“Ok Google,” for example), and your phone will convert the audio to text.

For many AI researchers, creating a machine with human-level intelligence that can be applied to every endeavour is the Holy Grail. Although super-intelligent robots have long been the subject of dystopian science fiction, experts believe that this isn't anything to be concerned about anytime soon. In the last decade, AI and machine learning technologies have advanced at a breakneck pace. These technologies have established themselves as a must-have in a variety of industries, and they continue to grow in importance and demand new ones.

Figures and Facts about Artificial Intelligence

The Global AI Market is predicted to generate a revenue of 118 billion dollars by 2025, according to Tractica, a market research organisation.
According to Gartner, 37% of companies have deployed AI in some manner. Over the last four years, the number of businesses using AI has increased by 270 per cent.
AI will fuel 95 per cent of customer interactions by 2025, according to Servion Global Solutions.
According to Statista's latest estimate for 2020, the global AI software industry is predicted to increase by 54 per cent year over year, reaching a forecast value of 22.6 billion US dollars.

Conclusion

With its applications, Artificial Intelligence is transforming industries and assisting in the resolution of complicated problems. The preceding list is merely a small sample of artificial intelligence case studies available today. As more companies take steps in this direction and learn how to integrate artificial intelligence, the possibilities for the future will only rise. Artificial intelligence is already automating corporate processes and will continue to do so in the future. Artificial intelligence is a vast field with plenty of information to be discovered. Only AI professionals are capable of realising the technology's full potential.

Artificial intelligence is all around us, and it is playing an increasingly important part in our daily lives. AI is lurking in the background every time someone opens their Facebook newsfeed, performs a Google search, receives an Amazon purchase recommendation, or books a trip online.

It can be said that artificial intelligence is widespread in people's lives. The drastic changes in the 21st century have led to the development of artificial intelligence, which has further expanded the application of technology in many fields. AI enables machines to work in the manner of human intelligence, and computers have been trained to mimic human behaviour well. In the long run, this technology will try to map neural networks to make machines operate like a human brain (neuromorphic computing).

All in all, artificial intelligence has many applications that make it useful to people in daily life. Although many scientists have warned humans about artificial intelligence, the future of artificial intelligence is very important to the development of technology.

AI is redefining how business processes are executed in various fields such as marketing, healthcare, and financial services. The company has been studying how to benefit from this technology. As efforts to improve existing processes continue to increase, it makes sense for professionals to gain expertise in the field of artificial intelligence. Top 10 Artificial Intelligence Applications, this article will help you to learn and grow in this industry without any hindrance.

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Sep

What is S-Curve in Project Management?

iCert Global Project Management 0 2021-09-22 7125

Business relies on a variety of computations and variables that change throughout time. It has always been reliant on these factors, but now humanity has developed a variety of tools and parameters for those tools to aid in the calculation of progress.

These tools and parameters are quite beneficial to your business because they allow you to learn more about your job and dig deeper into your flaws. The S-Curve graph, which uncovers some of the most crucial data about your company, is one of these significant features.

Finding an answer for What is S-curve in Project Management? Here you go - An S-curve is a graph that shows a cumulative data field versus time, such as man hours or cost. It's helpful in project management because it allows project managers to track project progress by comparing the expected shape of the S-curve to the present shape

On this one, there are no surprises. Because of the shape it takes on the graph, it's referred to as an S-curve. Progress is slow at the start of the project (the graph line is flatter). The project team is forming, stakeholders are approving, and you're spending more time planning than doing.

The steep curve upward creates the centre half of the S-shape once the project is fully operational. Growth in project activity — such as man-hours — is substantially higher once the project is fully operational. The point of inflexion is the highest point of activity. The curvature begins to level out as the project winds down and approaches completion. S-curve represents the entire system life cycle. There are four stages: infancy, rapid growth, maturity, and decline. Every stage has its own unique features.

S-Curve in project management represents the cumulative workload or cost over time on a man-hour basis. The name stems from the fact that data usually takes a slower-paced form at the beginning and end of the project.

What is a S-Curve in Project Management?

In project management, a curve is a mathematical graph or illustration that correctly represents the corresponding cumulative data of the project or task. This data can be the relationship between cost or labor hours and time. The reason it is called the S-curve is not very technical. It depends on the shape of the graph. You know that this shape of the chart depends entirely on the type of project you are working on, so many other forms can also be used.

Basically, the term project management is a chart used to effectively track the progress of your ongoing project. This is very convenient because in today's fast-paced corporate culture, it is very important to ensure that the set budget is used on time to meet all the needs and requirements of the project.

What role does S-curve knowledge have in project management?

1. S-curves assist you in keeping track of project progress. - S-curves are useful to project managers because they provide a straightforward and intuitive measure of project progress.S-curves, in particular, demonstrate how the project is using project resources — both human and financial — in comparison to the quantities set aside at the outset.

Only half of project managers establish a baseline for their projects, making it difficult to track actual progress. You have a baseline to track progress against by plotting an S-curve during project beginning, utilising estimates for variables such as expected man-hours and cost. The project manager can plot actual resource utilisation during the project lifecycle to see how well it matches what was predicted. If there is a discrepancy between them, there is a chance to make changes to how resources are allocated.

2. They allow you to forecast when resources will be in high demand. - When you plot your S-curve, you can see when the project will be the most resource-intensive.That might be when you need a cash injection or when you have a lot of work to do and need more resources. This is useful since it may signal that a major portion of the project money needs to be released by business stakeholders, or that you need to hire contractors to complement your core project team.

3. They aid in the management of stakeholder expectations. - Understanding S-curves can also help you keep your project's stakeholders engaged. S-curves are a visual and straightforward technique to describe the likely pace of work to stakeholders during the planning stage.Explaining that progress would be modest in the early stages of project execution before there is a major increase in the amount of work to be done will help control stakeholder expectations of rapid change.

It can also assist line managers in anticipating when their team members will be required to contribute the most to the project, either through their abilities or their business expertise.

4. They give you the ability to plan for various timetable circumstances. - After you've generated your baseline S-curve, you can experiment with the inputs to see how they affect the project's outcome. Plotting the earliest and latest start dates for jobs in your project schedule is one of the most prevalent examples.

This results in two curves that meet at the beginning and end and are referred to as a "banana curve" due to their shape. Project managers frequently calculate when a work can begin and end in the schedule without influencing the overall time. This shows how much wiggle room or "float" there is in the timeline if things go wrong during the project.

You may plot actual work against the banana curve as it is delivered. If the data points are close to the ‘latest date' curve, a danger of project delay is signalled, and the project team is prompted to take action.

5. Estimate the number of man-hours required. - It's not the same as ordering products or equipment when it comes to hiring staff. You must prepare ahead of time, therefore use an S-curve to chart out estimated man-hours for a project to ensure optimal hiring efficiency.

During the early stages of a project, you won't have too many people standing about doing nothing, and you won't have to hustle to add staff as the project progresses. Map up a plan to have the right man-hours at the right moment, no matter what phase of the project you're in, using S-curves from previous similar projects — or just making an informed guess.

Different types of S-curve in Project Management:

There are a variety of S-curves available for project management applications. These are as follows:

Actual S-Curve
Target S-Curve
Baseline S-Curve
Costs Vs. Time S-Curve
Value & Percentage S-Curve
Man-hours Vs. Time S-Curve

Why an S-curve?

Well, the "S" shape is not forced or developed, it is just the shape formed by the chart in the early stage of the project when the standard growth of the project is very slow. In the initial stage, the project began to disband, and the team members were only in the research industry or just started the first phase of project execution. This process may take longer at the beginning, but once the team masters it, they will quickly solve the problem, and as the process progresses, the process becomes seamless.

As progress increases, growth accelerates suddenly. If you want to grow quickly in the graph, this is the middle part of the "s". The point of greatest increase is called the turning point. These are the most important parts of the curve, because this is where growth stagnates. At this point in the process, team members usually work very hard on project tasks. As they accelerate this process, more and more tasks and the accompanying costs continue to increase.

After the turning point, a growth plateau is formed, forming the upper part of the curve. This part is called the upper asymptote. Basically, this is the mature stage of the project. This maturity is due to the fact that most projects have been completed and are in progress at this time. Generally speaking, at this point in the process, only tasks such as finishing and final approval are left.

How to Generate S-curves?

Benchmarks for projects

On a regular basis, percentage S-curves can be used to compute critical project benchmarks, such as:

Percentage growth projections (Target and Baseline S-curves)
Percentage slippage in the project (Target and Baseline S-curves)
To date, the actual percentage completed has been compared to the target percentage completed.
To date, the actual percentage completed has been compared to the baseline percentage completed.

What is the process of creating an S-curve?

A Baseline Schedule is necessary to create a Baseline S-curve. For each task, the Baseline Schedules should include the following information:

Dates of the baseline start and finish
Man-hours and/or cost baselines

A Production Schedule is required to generate Actual and Target S-curves. For each task, the Production Schedules should include the following information:

Actual Start and End Dates
Costs and/or actual man hours
Actual Completion Percentage

Common uses of the Curve S in Project Management

Some of the most common uses of S-curve are to measure progress, evaluate performance, and make cash flow forecasts. The S-curve in project management helps to monitor the success of the project as cumulative real-time data from various project elements-such as cost-can be compared with projected data. The degree of alignment between the two charts indicates the progress of the project under review-or lack of progress. If corrections are needed to get back on track, S-curve can help identify them.

Throughout the life cycle of a project, S-curve can be used for many different purposes. Some of the main uses of S-curve are discussed below:

Banana Curves or Scheduled range of Possibilities:- This is probably the most important use of the bowl. As we all know, most planning software with

Quality
Man hours
Cost

The banana shape curve shows us the range of possibilities for the project to be completed on time.

Quantity output comparison:- Another important use of the S-curve is to evaluate the volumetric performance that your project will produce. This is mainly used in the construction and manufacturing industries.
Cash Flow forecasts:- The next use of the S-curve is to develop cash flow and predict the changes that cash flow will bring. What is it? Well, cash flow is the time and flow of funds related to tasks and events that occurred during the execution of the project.

This cash flow curve is very useful to stakeholders. The main benefit of creating a cash flow curve is that it allows you to assess cash requirements and actual payment time based on the company's accepted commitments.

Performance and Progress Evaluation:- The S-curve is mainly used to evaluate the progress and performance of related projects. This is achieved through the use of earned value management. The S-Curve in project management diagram is traditionally generated as part of the EVMS process and is the basic building block for evaluating project progress and project performance.

In order to determine the current state of the project and future predictions, many factors need to be evaluated. They are:

Performance Measurement Benchmark (PMB), also known as planned value
Earned value
Actual cost

All of these factors must be compared with the planned curve to produce results. This comparison makes sense, because if you want to know if the project is over budget or if other tasks are going on as planned, you can view the graph and your query will be answered immediately.

Determining Growth, Slippage and Progress

Choosing a Growth Strategy

When the Baseline and Target S-curves are compared, it's easy to see if the project's scope has expanded i.e. Target S-curve finishes above Baseline S-curve or shrunk i.e. Target S-curve finishes below Baseline S-curve. A change in the project's scope necessitates a re-allocation of resources (increase or decrease) as well as the very real possibility of contract variation increases. If the resources are fixed, the project's duration will either rise (complete later) or decrease (finish sooner), necessitating the submission of an extension of time claim.

Identifying Slippage

The term "slippage" is defined as: The length of time that a task has been pushed back from its initial schedule. The difference between a task's scheduled start and finish dates and the baseline start and finish dates is known as slippage. When a baseline plan is established, and the actual dates submitted for tasks are later than the baseline dates, or the real durations are greater than the baseline schedule durations, slippage might occur.

Any project slippage is easily seen by comparing the Baseline and Target S-curves i.e. the Target S-curve finishes to the right of the Baseline S-curve. In order to remove or at least lessen the slippage, more resources will need to be allocated or more hours will need to be worked. If the slippage cannot be eradicated or reduced to an acceptable level, an extension of time claim may be required.

Keeping Track of Progress

The difference between the Target S-curve and the Actual S-curve reflects the project's development over time. For the majority of the project, the Actual S-curve will be lower than the Target S-curve (due to many factors, including delays in updating the production schedule). The curves will only converge and intersect near the end of the project. The Target S-curve can never finish higher than the Actual S-curve. If the Actual S-curve at the Cut Off Date is higher than the Target S-curve, the Production Schedule should be reviewed to see if the project is actually ahead of schedule or if the Production Schedule contains unrealistic percentage completion values for continuing jobs.

Conclusion

Nowadays, project management is a very tricky business, and if you want your business to succeed, you need to monitor many factors. S-curves are a useful tool for project management. They enable for the visual tracking of a project's progress through time, as well as the creation of a historical record of what has occurred thus far. Project managers can use S-curve analysis to swiftly identify project growth, slippage, and prospective difficulties that could have a negative impact on the project if no action is taken.

These factors need to explore the appropriate tools and parameters, and S-curve is just that. We can use an incredible tool that can help us monitor the cost of all man-hours and other factors. Therefore, if you want your business or project management activities to be successful, use S-curve to research in depth and get rid of all problems. The S-curve can be particularly useful when companies are trying to best understand new product launches and their impact on demand, supply, and finances.

Several mathematical equations produce S-curve in project management of different shapes, where shape refers to the beginning, end, and steep time of the four stages of market growth (start and slow growth, rapid growth, slow growth again, and no growth). This article is titled “What is S-curve in Project Management?” will help you to make the S-curves in your project.

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Sep

10 Most In-Demand Programming Languages You Need to Learn.

iCert Global Other 0 2021-09-21 1908

Almost everyone knows that today’s technology is changing at a fast pace. It has become quite normal to see alternative technologies that are frequently exceeded with regular updates and advances. In the middle of all this, a domain that has hit a lot with such volatile nature of the technology world, and this is the programming language!

The good news is that as you start your career as a software developer, you'll begin to figure out which programming language is best for you, your interests, and your professional objectives. For several of the most prevalent use cases, such as web development, mobile development, game development, and more, the greatest and most in-demand programming languages to learn in 2021 will be explored in this article.

Top 10 Programming Languages

1. Python:-

The language has experienced huge growth of about 18 to 19% in the last 5 years. In the Pypl index, Python is classified in position number 1 for the 2020 December index. The language is among the most popular programming languages on different other renowned platforms, such as overflowing the battery, Github, etc. Furthermore, compatibility with Python technologies such as Ai & ML trends makes it more preferable among developers. This is the best programming language to learn in 2021.

2. C or C++:-

Talking about all in the language C, the programming language of generic procedures is more commonly used in the development of low-level systems, such as operating systems, main development and others. This language can be used in developing games, VR and many more.

And many other programming languages inherit the properties of this particular language. On the other hand, C ++ is a marked programming language (mainly developed as an extension of C). The language is widely used in the development of games, GUI and desktop applications and competitive programming along with several other fields. This can be the best programming languages to learn in 2021

3. PHP:-

The open source server side script language is used for website development and meets some exceptional features such as cross-platforms compatibility, objective programming functions, easy integration with HTML, CSS, JavaScript, etc., support for the community and many others.

The language is strongly recommended for beginners, as it is quite easy to learn. Some of PHP's popular frameworks that can be considered are Laravel, Symfony, CodeIgniter, etc. Therefore, if you can't wait to enter the web development domain, PHP would be an excellent option for you! This is one of the best programming languages to learn in 2021.

4. Scala:-

Several technology giants like Netflix, Linked In, eBay, Twitter, etc. They are using scale for their respective platforms and products. It is highly recommended for beginners to opt for scale due to its easy to learn behaviour. Since many other companies expect to incorporate scale into their activity and consider their significant request among the developers. Scala can be the best language to learn for the future.

Furthermore, the Scala code can be converted into byte codes and can be performed on the Java virtual machine. The language is widely used in the web development area, in data science and automatic learning. This is the best programming language to learn in 2021.

5. Go:-

Although Go is not that much popular programming language, in recent years, it has witnessed a significant increase in its demand and popularity among the developers. Companies like Uber, Google, etc.

They are working with Go Language and you can choose to learn. It seems that you seem that the language will be larger and larger in the coming years. This can be the best programming language to learn for the future. It provides you with numerous enrichment features, such as waste collection, dynamics, type security, high performance and efficiency and many others.

The language allows multithreading and can be used in the distributed system, in cloud computing, etc. The best thing about the language is that it solves different problems, such as a slow compilation and execution, the lack of availability of the rich standard library, etc. This could be the best programming languages to learn in 2021.

6. Kotlin:-

In the current scenario, provided there is a speech of the development of the Android application, the name of 'Kotlin "is undoubtedly first! However, a great inclination of developers to Kotlin is evident after Google has declared it as its favorite language for the development of Android applications.

As is known to all those in the Android's market , you are not going to retire at any time, so you can choose to learn from Kotlin by 2021 from some professional opportunities that are worthwhile in the future. This can be the best programming language to learn in 2021.

7. R Language:-

Several companies with great techniques like Facebook, Google, Uber, etc. They are using the R language for their activities and considering the rapid request for data science trends and machine learning, the learning of the programming language R is worth it for their future career efforts.

Furthermore, it can be easily integrated with different data processing technologies such as Hadoop & Spark. Some of the other exceptional features of this particular language, such as the compatibility of crossed-platforms, extremely extensible graphic functionality, and strong distributed calculations, etc., make it a more preferred language among developers. This could be the best programming language to learn in 2021.

8. Javascript:-

Many languages have come and disappeared, but Javascript is one of those few renowned languages that enjoy a great career and demand in the world of programming. Meanwhile, some of the famous companies in the world of technology that use JavaScript are Facebook, Google, Microsoft, Uber, etc. This language can be used for e-commerce websites, app development, etc.

Furthermore, the language is used for the development of the front-end and the development of the back-end. Furthermore, its compatibility with some prominent frames such as reaction, vue, node, etc. It makes it more preferable among the developers. Because there are millions of websites that already exist through the web that are largely based on JavaScript and at the top of that, observing the demand and domain of language. This is the best programming language to learn in 2021.

9. Swift:-

If you are interested in Apple products and the development of mobile demand, Swift is a good starting point. Before being announced by Apple in 2014, Swift is a relatively new programming language that is used to develop iOS and MacOS applications. Also, this can be the best programming language to learn for the future.

Swift has been optimized for performance and was built from scratch to match the realities of modern iOS development. IOS does not only work on each iPhone and iPad, but it is also the basis for other operating systems, such as watches (for Apple watches) and tvOS (for Apple TVs).

10. HTML:-

Technically, HTML is a markup language, which means that it is responsible for formatting information training on a website. Essentially, HTML is used to describe the web pages with ordinary text. This language is used for various purposes like web documents, website development, website maintenance and so on.

It does not have the same functionality as other programming languages on this list and is limited to the creation and structuring of the text on a site. The sections, headers, links and paragraphs are part of the HTML domain. This is the old and best programming language to learn in 2021.

Conclusion

The world is becoming increasingly digital, and as more and more aspects of our life become digital, the demand for computer expertise is increasing every day. As a result, knowing programming languages has become essential for any IT professional. Programming languages, in fact, are at the heart of this ever-expanding subject of computer science. If you're new to programming, picking up a new language or framework is critical. As a newcomer to the realm of programming, make sure you stay consistent in your learning and coding. However, deciding on the finest one from a pool of hundreds of programming languages can be difficult and perplexing.

It's crucial not to get caught up in flashy trends or popularity competitions while picking which programming language to study. The top programming languages to learn in 2021 are expected to be the same as they were in 2017 and 2018, and this trend will likely continue for the next several years. Despite the fact that the area of computer programming is continuously changing, the languages we've explored so far have a lot of staying power. You'll be in great shape not only this year, but in the years to follow if you study one or more of these languages.

Despite the fact that there are hundreds of programming languages, just a few are on the list of languages you should be familiar with. Learning one of these languages is a fantastic place to start if you want to start a career as a programmer, make a lateral shift into another industry, or rise up the ladder at your existing employment. You can find the appropriate match for you because courses span from Python for beginners to Java for experts.

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Sep

Agile Methods: Scrum, Kanban, XP, Lean, DSDM, FDD, SAFe!!!

iCert Global Agile and Scrum 0 2021-09-20 3093

The agile software development methodologies were created in 2001 and were based on the revered agile manifesto, which laid out the principles and core practices. It's important to understand what agile is before diving into the definition of agile methodologies.

Agile is a set of practices used by a team to manage a project or plan by breaking it down into stages and collaborating with customers on a regular basis. Every stage of the project's software development is constantly monitored. The advantages of the agile technique include that, unlike the traditional waterfall methodology, both development and testing activities are concurrent and synchronised.

What is Agile Methodology?

The agile methodology is one of the simplest and most straightforward ways to turn a concept and a variety of requirements into workable software solutions. The Agile methodology is an iterative and incremental approach to software development that emphasises continuous planning, understanding, updating, team collaboration, development, and delivery. The agile method is broken down into individual models that teams work on, allowing for more adaptability to changes.

The agile process begins with customers specifying the end uses of the final product and the types of problems the final product seeks to solve. It is guided by the ideals of giving value and engaging with stakeholders. This exercise aids the project development team in resolving and clarifying the customer's expectations and requirements.

As soon as the project begins, the selected teams begin to prepare and work on a comprehensive process that includes planning, implementation, and evaluation. Errors are resolved in the project's intermediate stage because the development process is iterative. This method allows the final deliverable product to better match the needs of the customer.

Different Types of Agile Methodologies

There are several sorts of agile methodologies available on the market to meet the needs of each project. Despite the fact that there are various agile techniques, they are all founded on the agile manifesto's key ideas.

As a result, any framework or behaviour that adheres to these principles is referred to as Agile, and regardless of the various forms of agile techniques that a team employs, the agile methodology benefits can only be fully realised with the participation of all parties involved. The following list of agile techniques includes well-known forms of agile approaches from which to choose:

1) The Kanban system

The phrase ‘Kanban,' which comes from the Japanese language, means “visual board or signboard” and is linked to the concept of “just in time”! Initially established as a lean manufacturing method, the Kanban concept has gradually found its way into agile software development teams. This method develops and manages projects using visual methods.

Kanban projects are managed with the use of a Kanban Board, which is separated into columns to illustrate the software development process flow. This increases team visibility by allowing them to see progress through each stage of production and prepare for impending activities in order to deliver the product "just in time"!

This method necessitates extensive engagement and transparency in order for team members to be aware of the current state of development at all times and to maintain a continuous flow of work.

Kanban is a process intended to promote collaborative working more successfully, similar to Scrum. It functions effectively based on three principles:

It could be quite helpful to see what needs to be done today, i.e. workflow automation, which specifies all the pieces in relation to one another.
To keep the flow-based method in harmony by limiting the amount of work in progress, so that teams don't start and commit excessive work all at once.
When a task is close to being completed, the next priority would be to bring something from the backlog into play.

2) Scrum: A software development methodology.

The agile scrum development approach, which is portrayed through numerous development cycles, is one of the most common agile methodology examples. Scrum, like Kanban, divides the development process into stages or cycles called sprints. Each sprint's development time is maximised and devoted, allowing only one sprint to be managed at a time.

Scrum and agile techniques emphasise ongoing deliverables, therefore this strategy allows designers to alter priorities to guarantee that any sprints that are incomplete or overdue receive further attention. The Scrum Team has dedicated project responsibilities such as a scrum master and a product owner, with daily scrums where activities are harmonised to determine the best method to implement the sprint.

3) XP (Extreme Programming)

Extreme Programming (XP) is a software development process that prioritises collaboration, communication, and feedback. It emphasises continuous improvement and client happiness. This strategy, like scrum, makes use of sprints, or short development cycles. This is created by a group of people in order to produce a productive and efficient workplace.

In a circumstance where clients have frequent and fluctuating expectations, the Extreme Programming technique comes in handy. It encourages developers to accept modifications in customer requirements, even if they arise late in the development process.

In Extreme Programming, the project is tested from the beginning by gathering input that improves the system's output. This also serves as a spot check to ensure that any consumer requests are easily implemented.

4) Crystal

Crystal is a series of smaller agile development approaches that include Crystal Yellow, Crystal Clear, Crystal Red, Crystal Orange, and more, and was introduced by Mr Alistair Cockburn, one of the key figures in establishing the Agile credo for software development. Each has its own unique structure, which is defined by criteria including system criticality, team size, and project priorities. The type of crystal agile methodology is chosen according to the nature of the project or system criticalities, such as Comfort (C), Essential Money (E), Discretionary Money (D), and Life (L).

Crystal, like other Agile approaches, focuses on timely product delivery, regularity, minimal administration with high user interaction, and customer satisfaction. The Crystal family believes that each system or project is unique, necessitating the use of a variety of techniques, processes, and policies to obtain the best results, giving them the title of agile methodology's lightest approaches.

5) Dynamic Systems Development Method (DSDM)

The Dynamic Systems Development Method was created in response to the demand for a common industry charter for the rapid delivery of software. DSDM provides a comprehensive structure that can be developed and adjusted to plan, execute, manage, and expand software development processes. The DSDM believes that project modifications should always be expected, and quality and timely delivery should never be negotiated, based on a business-driven strategy and eight principles.

6) Lean

Although it is a deeply adaptive, evolving methodology with the absence of fixed principles, laws, or techniques, it is an iterative, agile methodology that leads the team on addressing client values through persuasive value stream mapping.

The following are some of the core Lean principles:

Uninterrupted advancement
Respect for other people
Eradicate waste
Rapid delivery
Knowledge-making and
Defer commitment.

In comparison to the hierarchical flow of control, Lean offers each individual and small team decision-making authority. It focuses on the effective utilisation of team resources and ensures that everyone is as productive as possible for as long as feasible.

Conclusion

As the struggle for market share tightens, agile development offers a number of benefits and few negatives. More and more businesses are migrating to a digital environment that emphasises agility, extensibility, and increased productivity, as well as agile approaches.

Choosing the proper agile methodology from the several forms of agile methodology necessitates a dynamic approach. In order to entice talent and deliver outstanding digital experiences in this fiercely competitive industry, the advantages and downsides of agile methodology must always be weighed while choosing the framework for one's firm.

Each highly-operating enterprise must evolve quickly, reveal, and achieve remarkable results in less time. At the same time, when an individual works in a team of exceptionally brilliant and motivated people, there will be certain limitations and disparities in terms of concept, perspective, and techniques. All of these difference matrices can be normalized/derived using the Agile method. Any Agile Methodology that is appropriate for any business is dependent on a number of criteria.

Individuals that are willing to apply Agile methods are classified as team types.
The size of the organisation and the circumstances under which an individual seeks to ascend agilely from the bottom to the top
Organizational culture: To identify whether a company is ready for, or interested in, a highly-configured agile strategy, or prefers more conforming methods.

Agile development is based on an incremental paradigm that promotes team communication and continuous planning, as well as continual evolution and learning. Agile approaches should respect the software development cycle - planning, execution, and final delivery – allowing software to be produced in stages, making bug detection and resolution easier. Because Agile approaches are incremental, the major benefit is not just the quick delivery of software, but also the constant delivery of value to the customer.

However, agile software's numerous applicability in multiple industries, as well as accompanying benefits in the digital workplace, have prompted widespread adoption around the world.

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Sep

Certified Associate in Project Management (CAPM) Overview.

iCert Global Project Management 0 2021-09-17 1530

The CAPM (Certified Associate in Project Management) credential is designed to assist candidates in learning the skills required for entry-level project management roles. It may serve as the first step toward a career in the sector. The Project Management Institute (PMI) offers various internationally recognized project management qualifications, and the Certified Associate Project Manager (CAPM) certification is a good place to start if you're new to the industry.

Earning the CAPM certification can assist in establishing a dedication to project management as a profession and add credibility to your CV if you don't have the required experience for the Project Management Professional (PMP) test.

What is CAPM Certification?

Passing a proctored exam at an approved test center or online is required for the CAPM. The exam is targeted toward persons interested in managing larger, more difficult projects, taking on a larger responsibility, or expanding their project management knowledge and skills. It focuses on project management ideas, processes, and terminology.

The Certified Associate in Project Management is an asset that will distinguish you in the job market and boost your credibility and effectiveness working on — or with — project teams, regardless of your professional stage. According to our 2015 Pulse of the Profession® report, organizations with standardised procedures achieve greater results. You'll stand out to employers and be ready to move forward since the CAPM® validates your knowledge of the profession's top global standard. Project management is a career that is rapidly expanding.

Prerequisites for Certified Associate in Project Management

To take the CAPM, you must have completed 23 hours of project management instruction and have a secondary degree (high school diploma, associate's degree, or global equivalent) by the time you take the exam. To keep their CAPM certification, CAPM holders must obtain 15 PDUs every three years.

CAPM Certification Costs

Passing one exam is required for the CAPM. As of July 2021, the exam costs are as follows:

Non-PMI members will be charged $300.
$225 for PMI members

A PMI membership costs $129 per year, plus a $10 one-time application fee. As a new member, this takes the total cost of becoming CAPM-certified to $364. A free download of the PMBOK (Project Management Body of Knowledge) Guide and access to a project management job board are among the benefits of membership.

You may be qualified for the student bundle, which costs $257 if you're a full-time student in a recognized, degree-granting school. This includes a $32 membership fee as well as the CAPM exam fee. You might also ask faculty members who teach project management courses at your institution if they have any bulk purchase arrangements with PMI, which could save you even more money.

If you're already employed and believe the CAPM will benefit your company, talk to your senior executives about whether your company will fund exam and training costs.

Is the CAPM worth it?

Earning a certification frequently leads to more opportunities, as it does with most certifications. The CAPM is a globally recognized certification that can provide new project managers with the following advantages:

Ensures that you have a firm grasp of project management.
It improves your trustworthiness.
Establishes your resume with a professional achievement from a well-known organization.
Assists you in gaining the respect of your peers and project managers.
Increases your self-assurance in your talents
Increases your chances of getting a promotion and a higher income.

For many people interested in a career in project management, the CAPM will be worth the time it takes to learn and pass the exam, given the benefits and relatively low cost of the exam.

A CAPM certification will demonstrate the following, in addition to improving your job prospects: Your knowledge, vocabulary, and processes related to global project management foundations. Your capacity to work in a project team – or with one. Your dedication to project management and personal skill development is admirable.

What to Expect on the CAPM Exam

The CAPM exam is a proctored online exam administered by the Project Management Institute (PMI), with questions based on the PMBOK Guide. It is made up of 150 multiple-choice questions that must be answered in three hours. To preserve your credentials after passing the exam, you must earn 15 PDUs every three years.

Exam preparation for the CAPM

You may have concerns about what to expect on exam day, such as what to bring if you're taking the test at an approved test center standardized what technical requirements your computer must meet if you're taking the test at home. To assist alleviate any unnecessary tension, PMI provides answers to a variety of frequently asked topics. It also includes an exam content outline to give you get a sense of what to expect in terms of learning objectives and weighting across the test's 13 focus and knowledge areas:

An overview of project management
The project's setting
Project manager's responsibilities
Management of project integration
Management of the project's scope
Management of project schedules
Management of project costs
Management of project quality
Management of project resources
Management of project communication
Risk management in projects
Management of project procurement
Management of project stakeholders

CAPM Training Courses

Training courses for CAPM

CAPM training is available directly from PMI or through these PMI-certified in-person and online trainers.

PMI: This official PMI online course for new practitioners focuses on PMI standards and technical skills. Non-members pay $400, while members pay $350.
Project Management PrepCast: Master the knowledge, skills, tools, and approaches required to pass the CAPM test with this video-based instruction. A test simulator is also available.
GreyCampus: This 2- or 3-day boot camp is conducted by a teacher and includes mentorship and assistance, as well as an exam simulator.
Simpli Learn: This online boot camp gives prospective project managers an overview of project management principles as well as knowledge of the five process groups and ten knowledge areas. There's also an exam simulator included.

Additional resources for CAPM Preparation

PMI provides guidance and tools, such as the CAPM Handbook, sample questions, a list of approved registered education providers, and more, to help you pass the CAPM.

Qualified project management experience is in high demand, with about 1.57 million new jobs produced each year, and the CAPM certification is an excellent way to start a fulfilling career in project management.

Certified Associate in Project Management Salary and Jobs

Project management positions are in high demand, and as the competition for experienced Project Management Professionals (PMPs) heats up, many businesses will turn to hire CAPMs. This opens up positions such as project manager assistant, associate project manager, jr. project manager, project coordinator, project delivery manager, and others for new CAPMs.

Project management is a skill that is in high demand and a rising career field. According to research by Burning Glass Technologies, over 280,000 entry-level project management opportunities were advertised between March 2020 and February 2021. According to the research, the number of these job openings increased by 51% from 2017 to 2019.

According to a report published by the PMI in 2021, by 2030, the global economy will require 25 million new project professionals to meet demand. As of July 2021, a Certified Associate in Project Management earns an average salary of $67,476 in the United States.

Does a CAPM have an expiration date?

Unlike PMP, CAPM does not necessitate the acquisition of Professional Development Units. The CAPM accreditation, on the other hand, is only valid for five years. You must repeat and pass the exam during your fifth year. If your CAPM certification expires, you must reapply as if you were a new candidate.

Is it possible for you to add CAPM to the end of your name?

As long as your credentials are valid, you can use CAPM in your correspondence, website, business card, email signature, and letterhead. However, PMI forbids it from being used as part of a company name, a product name, or a domain name.

PMP vs. CAPM

The CAPM certification is an associate-level certification offered by PMI for persons interested in project management or those who are new to project management and have little or no practical experience. The Project Management Professional (PMP) certification is for project managers who have at least 4,500 hours of experience managing and directing project teams.

Should you get the Certified Associate in Project Management or Project Management Professional(PMP) Certification?

Obtaining the CAPM certification as an entry-level certification can make sense if you have little or little project management expertise. It can be a good method to enter into the sector, or it might help you take on more project management-related responsibilities at work. Your choice should be based on your personal objectives. It'll also be useful to know how much the exam will cost, as well as your other possibilities.

The PMP is a recommended consideration if you have at least three years of project management experience. The PMI also offers the Project Management Professional (PMP) credential. The PMP is a professional-level certification. With over one million PMP holders globally, the PMP is also significantly more popular than the CAPM.

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Sep

What Is a Project in Project Management and Why It Matters?

iCert Global Project Management 0 2021-09-16 1695

In today's highly competitive global business world, the ability to deliver projects on time, on budget, and in alignment with corporate goals is critical. Project managers play a key role in this. Project managers have a difficult job that requires a combination of organisational skills, analytical thinking, and excellent interpersonal skills.

A project is defined as a set of tasks that must be performed in order to achieve a specific goal. The term "project" is defined by the Project Management Institute (PMI) as "any temporary undertaking with a known beginning and finish." It can be controlled by a single person or hundreds of people, depending on its complexity. A project can also be defined as a collection of inputs and outputs necessary to accomplish a specific aim. Projects might be simple or complex, and they can be managed by one or a hundred people.

A manager or executive is frequently in charge of describing and delegating projects. They discuss their objectives and goals, and the team is responsible for managing logistics and completing the project on schedule. There are occasions when deadlines are set. For good project productivity, some teams break it up into individual tasks to manage accountability and utilize team strengths.

A project isn't something you do every day. Because it lacks a defined start and end, day-to-day operations or maintenance is not considered a project. The discipline of utilising information, skills, tools, and strategies to execute a project according to precise requirements is known as project management. It all boils down to identifying the issue, devising a strategy to address it, and then carrying out that strategy until the issue is resolved. That may appear to be a simple task, but there is a lot that goes into it at each stage.

A project`s characteristics

A project is a collection of interconnected tasks with a shared purpose. The following are features of projects:

A project is not the same as a process - Projects and processes are frequently confused. A process is a set of predetermined processes that must be followed in order to fulfil a specific function, such as cost reimbursement approvals. It's not a one-time thing. It determines how a specific function is carried out on a consistent basis.
A specific start and end date - While some initiatives may last several years, they cannot continue indefinitely. It must have a distinct beginning, a distinct end, and a summary of what occurs in between.
A project creates something new - Each project is one-of-a-kind, creating something that didn't exist before. A project is a one-time, one-of-a-kind action that will never be done again in exactly the same manner.
A project has limits - A project operates within time, budget, quality, and functionality constraints. In the following sections, we'll go through this in further detail.

The nature of projects

Projects are available in a variety of shapes and sizes. A project can be:

Be big: Like the Hoover Dam, your project should take years to finish and have a massive budget.
Consider a little job, such as laying a pathway in your grass on a weekend.
Involve a large number of people: It's similar to arranging a wedding.
Rearranging the images in your wedding album by yourself

Various types of Projects

The ways in which projects are implemented can vary greatly. Here are some project examples:

Traditional projects: These are carried out in stages, one after the other. Initiation, planning, execution, monitoring, and closure are the most common phrases. Traditional project management is used in the majority of high-cost infrastructure projects.
Agile initiatives are commonly utilised in software development. They are adaptable and people-oriented. In addition, they usually have quick turnaround times.
Remote projects are typically employed by distant teams that meet seldom in person. A remote project is one that involves managing freelance participants.
Projects outsourced to an agency: Projects outsourced to an agency are likely to have several clients. Agencies are frequently used to handle marketing and design initiatives.

There are five stages to a project's life cycle.

Projects are frequently organised into five project phases, each of which has its own set of activities, objectives, and deadlines. By breaking down a project into phases, teams can stay on track throughout its full life cycle.

1. Initiation

Initiation is the first stage of a project's life cycle. A project is formally launched here. It is given a name, and a broad strategy is laid out. The project's constraints, hazards, and stakeholders are all recognised, as well as the project's goals. Shareholders must now determine whether or not they want to invest in the project. Studies may be undertaken to determine the project's feasibility, depending on the project. Requirements are typically obtained and reviewed during the commencement phase of IT projects.

2. Preparation

During the planning step, a roadmap is created that will take teams from the creation of a project plan to the project's execution and closure phases. There must be deadlines specified and resources allocated. It is easier to manage project risks, costs, quality, time, and other factors when jobs are broken down into smaller, manageable operations. Simultaneously, breaking down duties into manageable chunks will enable everyone involved to complete the project on schedule and on budget.

3. Implementation

During the execution phase, the project plan is put into action. Teams will work on the deliverables at this time to ensure that the project fits the requirements. Everyone normally joins for a meeting to mark the project's official start, when teams may get to know one another and discuss their roles in the project's success. Before the project plan is implemented, communication modes and project management tools are identified.

Furthermore, team members become familiar with the required status meetings and reports that will be held during this phase to collect project data. The project execution phase is crucial in the life cycle of a project since it determines whether or not everyone's efforts will be profitable in the end.

4. Controlling and monitoring

The monitoring and control phase occurs concurrently with the execution phase. The project manager's role is to oversee operations and ensure that everything is going according to plan. Project managers must monitor resources, manage risks, lead status meetings, and prepare reports, among other things, in addition to managing the project's performance. If unexpected problems develop, the project manager may need to make changes to the plans and the timetable.

5. Concluding

The last stage of the project management life cycle isn't as straightforward as simply delivering the product. During the project closing phase, project managers must keep track of all deliverables, organise records in a centralised area, and hand over the project to the client or the team in charge of managing its operations. Not only that, but teams meet for a final meeting to review the lessons they've learned and to recognise each member's hard work.

How to put a project into action

Depending on the methodology employed, the process of implementing a project can differ. Implementation is done in five steps in traditional project management.

Initiation: This phase entails persuading stakeholders to support the initiative. A Project Initiation Document (PID) is generated with basic project information such as likely resource utilisation and viability.
Once a project has gotten stakeholder consent, it enters the planning phase. This is a crucial phase that entails a variety of duties such as contingency planning, work allocation, and resource sharing planning.
Execution: This is the stage in which the real task is carried out. Periodic assessments are carried out to guarantee that execution is completed on time.
Monitoring is done in conjunction with execution. To ensure that work proceeds without problems, the project manager must keep a close eye on everything.
Closure: This phase includes the project's critical final tasks, such as delivering the project to the client and recording the project's learnings.
A project is said to be well implemented whenever these steps are completed.

How project management aids project management

Projects can be extremely complicated enterprises that need a significant amount of time and resources. Using project management principles, regardless of the purpose, will ensure that the effort runs smoothly. Projects will be handled haphazardly if proper project management principles are not followed, and they will be at a much higher risk of failing, delaying, and going over budget.

Knowing the basics of project management increases one's chances of effectively completing a project. Project management approaches and frameworks enable organisations to lead projects in the right direction, regardless of their sector or expertise.

What are the responsibilities of project managers?

In a nutshell, project managers are in charge of project planning, execution, monitoring, control, and completion. However, that is only the tip of the iceberg when it comes to project management. The following are some of the most important project manager responsibilities:

Build the plan: Project managers are in charge of charting the project's most realistic path. The project scope, timeline, and money must all be included in the plan. This may also entail determining the appropriate tools for the work.
Assemble the team: Choosing the right team is essential to the project's success. Depending on the extent of the initiative and the functions required to accomplish the project, each project team will be unique. It's best to find specialists and subject matter experts for each of the required duties.
Assign tasks: Project managers must provide a detailed description of specific tasks and timelines for each phase of the project to their team. Despite the fact that each team member will be responsible for their own duties, many activities will necessitate collaboration from both internal and external team members.
The project manager must keep the machine well-oiled now that the team has been recruited and their tasks have been assigned. This will entail checking in on people for updates, detecting and removing bottlenecks, resolving conflicts, maintaining strong team morale, and offering training and mentoring.
Budget management: Most projects will necessitate some expenditures, thus knowing how to set together a project budget and manage costs is vital to success. This will entail comparing actual spending to estimates and, if necessary, revising the project plan.
Managing timelines: Just like with the budget, project managers are responsible for keeping things on track so that the team may fulfil their estimated completion dates. Setting realistic deadlines throughout the project's lifecycle, communicating regularly with their team for status updates, and maintaining a thorough schedule are all required.
Stakeholder engagement: Stakeholders play an important role in your project. They are usually powerful persons who will be impacted by the project. Stakeholders can assist in clearing hurdles and empower your team, but they can also create unneeded bottlenecks and derail a project if they are unhappy with the direction. Project managers must maintain a good connection and an open line of communication with them.
Transfer of the project: The project manager's job isn't done just because the project's objectives have been met. The project manager must now hand over the project to the team that will oversee its management, maintenance, and operation in the future. The project manager will then be allocated to a new project and will no longer be the "go to" person.
Keep a record of the procedure: Identifying and documenting "lessons learned" is a valuable practice not just for personal project manager development, but also for passing on that knowledge to other teams in the business. Others will be able to avoid making the same mistakes or make use of the shortcuts that have been discovered as a result of this.

How Management Software Is Useful for Projects?

Bringing your team together and preparing them to work as a team is critical to the success of your projects. However, if you don't have the right project management software, you can end up doubling your efforts rather than streamlining them. Consider how much time you've wasted handling spreadsheets and dealing with an overcrowded email. You may be more strategic with your resources if you have the correct tools.

Job management/collaboration tools and personal productivity tools are two types of technologies that can help you manage your work more effectively. Project management software varies by team, but the majority are computer systems that allow users to plan, execute, and manage projects all in one place.

Regardless of the size of the organisation or the industry, project management software is advantageous to all firms that manage projects. Anyone, including businesses that don't perform formal projects, can use the software's project planning and resource management capabilities.

Project management software may help any firm that needs an efficient way of estimating, planning, tracking, delivering, and charging for their services. It enables you to design, implement, and monitor effective and optimal business processes for your team.

Project management software can be used for a variety of tasks, including:

Planning a project
Timetables for projects
Allocation of resources and capacity planning
Keeping track of project costs and budgeting
Management of a project portfolio
Management of business processes
Management of the workflow
Management of quality
Documentation and project records are stored and shared.
Producing and disseminating project reports
Keeping track of the time spent on project tasks
Trend analysis and forecasting

What types of people should use project management software?

Project management software can help anyone who manages projects. Project management software can be useful even if you don't handle formal projects or have the title of "project manager."

Many businesses do not engage in traditional project management utility software to plan, organise, track, monitor, and execute their work. These tools, like projects, come in a variety of shapes and sizes. Some of your ideas, for example, maybe basic processes involving only you and another person, while others may require many teams to fulfil over the course of months (or even years).

Three types of tools that can assist with task management and teamwork.

1. Instant chat solution that works in real-time

Any organisation needs a solution that allows employees to voice or video chat with faraway colleagues in real-time. In meetings, you need to be able to hear your coworkers, and it's even better if you can see them (because, as we all know, non-verbal communication is just as important in these situations).

In the instant messaging market, there is fierce competition. Along with an increasing variety of mobile-first applications, Slack, Zoom, Google Hangouts, Skype, Chatter, and Facebook Messenger dominate the field.

2. Tool for creating a knowledge base

Consider a repository for your team's collective knowledge, accessible to all members via a searchable database. This can be accomplished via knowledge management technologies such as internal blogs or wikis (something Wrike can do very well). These technologies allow you to document processes and capture expertise or best practices to share with your team, ensuring that everyone has access to the information.

3. A file-sharing application

You'll need a simple way to share files if you want to work cooperatively. It is possible to attach files to emails, although this is discouraged because it frequently causes problems and wastes time. File-sharing software makes it simple to save, sync, and share files with your colleagues. There are many possibilities, including Box, Dropbox, OneDrive, and Google Drive, all of which interface with Wrike directly. You can quickly attach files from these services to your tasks if you use Wrike.

Tools for personal productivity

Every 11 minutes, the average worker is distracted. It might be difficult to block out distractions and focus entirely on work, which is why many people use productivity software. Productivity apps may turn off alerts and messages, forcing you to focus on one browser tab at a time, drown out the noise in your office (or home office), and help you organise your work.

Many firms, however, discover that these technologies aren't versatile enough to handle all types of projects. When project management is done solely through email and group chat, information is lost, document versioning issues arise and prioritising and task dependencies are unclear. This is where project management software enters the picture.

Important tasks to improve product lifecycle

1. Identification of project stakeholders

Key project stakeholders vs. stakeholders

Stakeholders in a project might be individuals or entire organisations who are impacted by the project's execution or outcome. It makes no difference if the project has a bad or positive impact on them; if they are affected, they are a stakeholder. Key project stakeholders, on the other hand, are those who have the power and influence to determine whether or not a project is a success. These are the individuals and organisations whose goals must be met, as they have the power to make or break the project. Even if all deliverables are completed and budgets are reached, the project will not be regarded as a success if the stakeholders are dissatisfied.

A project's typical essential stakeholders

The following are some of the most common significant project stakeholders:

Customers: The end-users of a product or service, who are frequently both internal and external to the firm that is carrying out the project.
The project manager is in charge of the project.
Members of the project team: The group in charge of completing the project under the direction of the project manager.
The project's financier is the project's sponsor.
The sponsor, executives, and key stakeholders from the organisation make up the steering committee, which provides guidance on crucial choices.
Executives: Those in charge of the project's execution; those in charge of the organization's strategy.
Other managers in charge of the resources needed to complete the project are known as resource managers.

Sellers/suppliers, contractors, owners, government agencies, media outlets, and even society at large are all examples of project stakeholders.

2. In project management, what are project objectives?

Simply said, project objectives are goals. These are the business goals you wish to achieve with the project. The clarity of a project's objectives is critical in project management since they will influence every choice made during the project lifecycle. Project objectives must be measurable and include key performance indicators that will be utilised to evaluate the overall success of the project. Budget, quality, and time to completion are frequently included in these measures.

3. In project management, what is a project charter?

A project charter is a formal, usually short document that explains your project in detail, including the goals, how it will be carried out, and who will be involved. It is an essential component of project planning because it is employed throughout the project lifecycle.

4. What is the best way to write a project charter?

Recognize the project's goals and objectives: Determine the project's scope and identify the project's vision.
Define the project's structure: List all of the project's critical responsibilities, including consumers, stakeholders, and the project's day-to-day personnel.
Make a plan for implementation: For the entire team and stakeholders, outline significant milestones, dependencies, and the schedule.
Make a list of potential issues: This isn't about being pessimistic; rather, it's about being realistic. Including potential risks and concerns in the project, the charter encourages everyone to plan ahead and even helps to avoid potential stumbling blocks.

5. Custom Workflow

Custom processes and statuses are available to all users on Business and Enterprise accounts; however, this is a regulated admin privilege, so some admins may not have it. Task statuses represent the various stages in which a task can be at any time during its lifecycle. Each process is made up of groups: Active, Completed, Deferred, and Cancelled. Workflows are made up of a collection of statuses. Custom workflows and statuses can be created for tasks and projects in Business and Enterprise. If an item has a specific status, they can designate who should be added as an assignee. Create a new workflow to match the needs of your team, and include statuses in it that reflect the common states of your tasks or projects.

Conclusion

It is important to understand that the term "temporary" does not apply to the project's outcome or service. The project may be finished, but the outcome is not. A project to create a monument, for example, would have a limited term, whereas the monument itself could be for an indefinite period of time.

A project is an activity that involves creating something new. Of course, many of the office buildings constructed are similar in many ways, but each one is distinct in its own way. Finally, a project must be developed gradually. This signifies that the project will be completed in stages and in increments. This also means that the project's description is refined at each stage, and the progress's goal is finally stated. This means that a project is defined first, and then as the project develops, the definition is examined and additional clarity is added to the project's scope as well as the underlying assumptions.

The project life cycle is made up of the phases of a project as discussed above. For management and tracking purposes, project managers find it useful to break the project into phases. Each state's milestones are then elaborated on and tracked for completion. The primary phases of a project are determined by the type of project being undertaken. A software project, for example, might include requirements, design, build, test, and implementation phases, but a metro or building project might have different names for each step. Each project phase is assigned a milestone, and the set of deliverables that each phase is intended to produce is tracked for compliance and closing.

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Sep

Understanding the Impact of Social Media [Pros and Cons]

iCert Global Other 0 2021-09-15 2770

Over the last 20 years, information and communication technology has evolved significantly, with the introduction of social media being a key development. The speed of change is quickening. For example, the evolution of mobile technology has had a big impact on social media's impact. Mobile devices dominate the world in terms of total minutes spent online. They made it possible for everyone to join from any location, at any time, and on any device.

The motivations that participants identified for sharing information on social media were exposed in a fascinating study by the New York Times Consumer Insight Group. These include the urge to provide people with useful and amusing material, to define themselves, to establish and nourish connections, and to spread the word about brands and causes they like or support. As a result of these causes, social networks have progressed from being a convenient way to keep in touch with friends and family to being used in ways that have a significant impact on society. Social media's influence is being utilised to change politics, business, international culture, education, careers, and innovation, among other things.

Impact of Social Media on Humankind

1. The Political Impact of Social Media

According to a new Pew Research study, roughly one out of every five Americans gets their political news mostly from social media. According to the study, people who get their political news primarily from social media are less well educated and more likely to be exposed to unsubstantiated claims than those who get their news from traditional sources.

The influence of social media in political campaigns has expanded in comparison to prior types of media. In political politics, social media has become increasingly important, first in Howard Dean's ultimately unsuccessful bid in 2003, then in Barack Obama's election as the first African-American president in 2008, and now in Donald Trump's Twitter-fueled campaign.

According to the New York Times, “the victory of Donald J. Trump is arguably the clearest example yet that social networks are helping to dramatically rewire human society.” Because social media allows people to interact more freely, it is facilitating the emergence of unexpectedly powerful social organisations among previously marginalised people.

2. The Impact of Social Media on Society

As social networks develop in power, they feed off of people's interactions. Because of the internet, anyone with a minority viewpoint can realize that he is not alone. When these people connect through social media, they can do things like developing memes, newspapers, and entire online worlds that support their point of view, then break into the mainstream. Social, ethical, environmental, and political concerns would have little visibility if not for social media. The balance of power has moved from the hands of a few to the majority as issues have become more visible.

An Alternative Look:

Slacktivism is slowly eliminating real activism as a result of social media. While social media activism raises awareness of societal concerns, the question of whether this awareness leads to genuine change remains unanswered. Some claim that social media has encouraged people to utilize computers and mobile phones to voice their worries about social issues without having to participate in real-life campaigns. Their involvement is restricted to pushing the 'Like' button and sharing content.

3. The Effects of Social Media on Business

With the rise of social media, finding a company that doesn't use one or more social media channels to reach out to customers and prospects is becoming increasingly rare. Businesses understand how important it is to use social media to communicate with customers and earn revenue. Businesses have realised that social media can be used to gather information, increase demand, and create tailored product offerings. Both traditional brick-and-mortar businesses and, of course, e-commerce require these obligations.

An Alternative Look:

A low number of social "shares" can affect negative social proof and corporate reputation. Interestingly, despite the fact that social sharing has become the norm rather than the exception in business, some businesses have chosen to go against the grain and remove social sharing buttons from their websites after witnessing firsthand some of social media's negative implications. Conversions increased by 11.9 percent after Taloon.com, a Finnish e-commerce shop, eliminated share buttons from product pages, according to a case study.

4. Social Media's Impact on Training and Development

Job seekers who learn the most up-to-date and advanced social media methods have a much better chance of landing a job. On behalf of Pearson and Connections Academy, OnePoll interviewed 2,000 U.S. parents and their high-school-aged children about the "new normal" of high school in 2020. Social media, according to 68% of kids and 65% of their parents, will be a valuable tool and part of the new high school normal. Many educational institutions currently use blogs, wikis, Linked In, Twitter, Facebook, and podcasts as learning tools. Social media has supported the growth of long-distance online learning.

5. The Effects of Social Media on the Workplace

The usage of social media in the recruitment and hiring process has had a big impact. For anyone attempting to build a reputation for themselves in their field, LinkedIn and other professional social media sites are essential. They enable users to develop and advertise their brand.

Nineteen percent of hiring managers rely on social media data to make their decisions. 70 percent of companies use social networking sites to explore job seekers, according to CareerBuilder's 2018 social media recruitment survey.

Social Media's Concerns

1. Privacy Issues

Some of the hazards that social media users face include stalking, identity theft, personal attacks, and data exploitation. The majority of the time, it is the users who are at blame, as they publish content that should not be made public. The misunderstanding stems from a lack of knowledge of how an internet profile's private and public sections work.

Unfortunately, it's usually too late by the time private stuff is removed. and the content has the potential to cause issues in people's personal and professional lives.

2. Cyberbullying

Teenagers strive to fit in, be popular, and outperform their peers. This was a difficult procedure even before the emergence of social media. When you add Facebook, Twitter, Snapchat, and Instagram to the mix, teenagers are now under pressure to grow up too quickly in an online world.

According to the Cyberbullying Institute's 2019 poll of US middle and high school students, more than 36% say they've been cyberbullied at least once in their lives, with 30% saying they've been victimized twice or more. It was also shown that over 15% acknowledged cyberbullying someone at least once, with nearly 11% confessing to doing so twice or more. Teenagers can use social media to spread falsehoods, upload films intended to harm others' reputations, and blackmail others.

3. It's easy to become addicted to social media.

When you're playing a game or doing a chore, you want to perform the best job possible. When you achieve, your brain releases dopamine and other pleasant hormones, making you feel good. When you upload a photo to Instagram or Facebook, the same logic is at work. You'll subconsciously register it as a reward once you see all the alerts for likes and good remarks crop up on your screen. But that's not all; social media is rife with mood-altering activities.

Conclusion: The Bottom Line

It is claimed that knowledge is power. People cannot harness the potential of information without a way of disseminating it. In today's society, social media has a good impact on information diffusion. Information can now be accessed at the touch of a button thanks to platforms like Facebook, Linked In, Twitter, and others.

According to research, a narrative published on the web has a 2.6-day life expectancy, compared to 3.2 days for a tale shared on social media. That's a 23 percent difference, which is considerable when you consider how many people use the internet regularly. The active lifespan of a social media post differs from the lifespan of an article. A Facebook post has an average duration of 6 hours, an Instagram or LinkedIn post of 48 hours, and a Twitter tweet has an average lifespan of 18 minutes.

The more time individuals spend actively accessing material on social media, the more debate it produces and the larger the social media impact. The shorter the active lifespan of a channel, the more frequently it must be updated to retain engagement (recognizing that posting too frequently can cause reader burnout). While the world would be a much slower place without social media, it has had both positive and negative consequences. The good influence of social media, on the other hand, is enormous and easily outweighs the drawbacks of sharing.

Finally, getting people to view and respond to content is the goal of sharing. It's always worthwhile for any company to use social media to maintain publishing as long as the content is still relevant and the need for information continues.

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Sep

Exploring the Role of Project Design in Project Management

iCert Global Project Management 0 2021-09-14 2121

Introduction

The first step toward a successful project is to design it. A project design is a method of organising ideas, materials, and processes in order to achieve a specific goal. Project managers rely on smart design to avoid mistakes and offer parameters to keep key components of the project, such as the timeline and budget, on track.

Some people make the mistake of rushing through the basic stages of a project, such as a project design. Any seasoned project manager will tell you that the more effort you put into the front end of a project, the better the backend results will be.

Design projects aren't the same as other types of projects. Because design is such a subjective science, there will almost certainly be more adjustments and revisions than with other sorts of projects. It also necessitates the coordination of a variety of abilities and input sources. There's a real risk of having too many cooks spoil the broth - or, in design terms, having too many creatives ruin the mock-up.

So What actually is a Project Design?

One of the initial roles of the project manager is to design the project. Decisions about how to manage and govern the project are made at this stage. A project plan is developed, focusing on the needs of the stakeholders, the organisation, and, of course, the project itself. This document will thereafter be used to oversee the project's remaining stages.

The thinking that occurs during project design, on the other hand, is less concerned with minutiae and more concerned with project management. Project management software can aid in the organisation of both the high-level strategy and the finer points of a project's design. For example, ProjectManager includes Gantt charts for creating comprehensive timetables, as well as kanban boards for simple collaboration on the strategic side of project planning. In one easy-to-use project management software, you can manage your strategy, plan, schedule, execution, and reporting.

Everything from who is accountable for finishing the project to a description of the project, its aims, outcomes, and objectives is included in the project design. It specifies the dates on which these goals, outcomes, and objectives will be met, as well as the primary deliverables, products, or features that will be accomplished. The project design also includes a budget estimate and a plan for tracking and evaluating progress. Stakeholders may be offered multiple designs, from which they can select the one that best meets their demands.

The Project Design Structure

How can you create a product that fulfils its promise? It's a challenge! Project management, on the other hand, follows a set of procedures. There are processes to define projects and build a plan for implementation. They are the most crucial steps in a project's development. As a result, you should involve your team and stakeholders in the process to ensure that you've covered all of your bases. Following are the 9 steps to project design:

1. Vision

A vision statement that depicts a problem that has to be solved. This entails defining the project's purpose. The vision statement is a formal document that outlines the project's possibilities. It is provided to stakeholders to demonstrate the project's viability and benefits.

It isn't a lengthy, in-depth paper. You can have a brief, utopian vision for the project's outcome; after all, this is how you sell the project. As a result, construct a picture of the project's success and set it in context.

2. Foreseeing Possible Problem

You must first identify a problem that has to be solved in order to support that vision paper. As a result, a needs assessment is frequently required so that you can see the challenges that the company is facing. This will bring the problem you're working on into line with the organization's overall plan. It will also give you the information you need to come up with the best solution to the situation.

To begin, what data are you collecting? What sources do you have for such knowledge, and how will you go about gathering it? Next, examine and identify the issues that your project is intended to address. Organize your findings in a document.

3. Who and What Resources?

Recognize the resources required to complete the project. People, equipment, and facilities are all examples of resources needed to perform a project successfully. The same way journalists tackle news stories, using the Five W's: who, what, where, when, and why, is an excellent technique to figure out the resources. What resources are necessary to complete the project, what resource management tools are required, where will the work be completed, when will the project begin and end, and why are these resources required?

4. Goal of the Project

You won't be able to reach your objectives until you first identify them. A goal is something that can be seen and measured at the end of a project. A goal is the same as a solution to a problem.

Make a goal statement that explains how the project's objectives are met. Use the SMART method, which stands for specific, measurable, achievable, realistic, and time-relevant, to achieve this well. These terms should be used to define each goal.

5. Strategy of the Project

A strategy must be in place to achieve the project's objectives. A strategy is a method for achieving the project's objectives while staying within the project's restrictions, such as resources, schedule, and budget. How can a plan be developed to meet the project's objectives?

Consider precedent and look back on similar projects in the past to see what they may have revealed about the benefits and drawbacks of their chosen tactics. Best project management practises are always a sound foundation, and then incrementally create a plan, creating a route to success.

6. A Backup Plan

Few things go according to plan, as any project manager knows. There must be a backup plan in place to respond swiftly and correctly to concerns that develop throughout the course of a project. As a result, this must be considered when planning your project.

Keep an eye out for the project's unfavourable hazards. They are immersed in a variety of settings, including teams that may be lacking in skills, have unavoidable absences, turnover, and so on. Delays may wreak havoc on schedules. It's possible that the scope was not clearly established. Costs are understated, or funds become scarce. Make a plan to deal with these dangers.

7. Plan that Evaluates

A project must always be evaluated, according to the assessment plan. An evaluation plan will assist you in keeping track of the project and may even notify you if it begins to deviate from the original plan. Analyze the project's components, outcomes, and implications using this strategy.

Impacts are how well the project aims are being met, whereas outcomes are measurable changes. As a result, the evaluation plan is a detailed document that establishes criteria for determining the project's effectiveness and efficiency by tracking all areas of the project's progress.

8. Budget

This is where you must match the client's expectations with your team's capabilities (and let your team know how much the client has to spend). When a creative designer is given free rein over Procreate and no budget, things can quickly spiral out of hand.

The budget lays forth the financial resources needed to complete the project. Each of the project criteria will be assigned a cost in a budget. Creating a project budget entails formally allocating financial resources to the project. This starts with deciding on a method for estimating costs, identifying impacts, and reporting on the evaluation.

9. What is the scope of the project proposal?

All of this culminates in a project proposal that explains why the project should be carried out and what benefits it would provide. The previous steps are summarised by putting up the project's goal and a concise description of the issue it addresses. Then, identify the project's objectives and the method that will be employed to attain them.

Conclusion

The project management paradigm is a tangled web of contradictions. Every project that emerges from the project development process is distinct, with its own set of characteristics and issues, but they all have one thing in common: a Project Design.

Project design is such a crucial component of a project that it would be impossible for the project development process to stand on and succeed in the future without it. The majority of project managers in the business rush the design process, unaware that by failing to properly execute a project design phase, their project will be an unmitigated disaster with no possibility of recovery.

Any project's success depends on effective management. Things might quickly spiral out of control if you don't have a plan. Nobody wants to be the deer in the headlights when a client asks for "that paper you promised" that went lost in the midst of a mountain of other responsibilities. Design projects are particularly turbulent because they bring together a diverse group of people with various skills and qualifications.

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Sep

What is Data Science and Why It Was Important in 2021

iCert Global Other 0 2021-09-13 1675

What is Data Science and Its Importance in 2021

Introduction

Given the vast volumes of data created nowadays, data science is important and is a crucial aspect of any industry. Data science is currently one of the most hotly disputed subjects in the industry. Its popularity has expanded over time, and businesses have begun to use data science approaches to expand their operations and improve customer happiness.

This article will discuss the importance of Data Science in the year 2021 by defining Data Science, Why it is helpful, what is a Data Scientist, ways in which data science can add value to the business, Applications of Data Science and finally, Data Science as a Career.

What is Data Science?

Data science is a field of study that works with large amounts of facts and uses cutting-edge tools and techniques to uncover hidden patterns, extract useful data, and make business decisions. To create prediction models, data scientists use complicated machine learning algorithms. Data for analysis can come from a variety of sources and be in a variety of formats.

In other words, data science is important as it is the process of extracting knowledge from data collected through various approaches. As a data scientist, you take a difficult business problem, gather information, turn it into data, and then utilise that data to solve it.

Why is Data Science Helpful?

Any organization's data is a valuable asset. It assists businesses in better understanding and improving their processes, resulting in time and cost savings. Waste of time and money, such as a poor advertising decision, depletes resources and has a negative influence on a company. Businesses can reduce waste by examining the success of various marketing channels and focusing on those that provide the best return on investment. As a result, a business can produce more leads without spending more money on advertising.

Data is pointless until it is transformed into useful information. Mining massive datasets containing structured and unstructured data and uncovering hidden patterns to derive relevant insights is what Data Science is all about. The value of Data Science can be seen in its numerous applications, which vary from simple tasks like asking Siri or Alexa for recommendations to more complicated ones like piloting a self-driving car. Better decision-making, predictive analysis, and pattern finding are all aided by data science or data-driven science. It's beneficial because:

By asking the appropriate questions, you can determine the root cause of an issue.
Conduct an exploratory analysis of the data.
Various algorithms are used to model the data.
Graphs, dashboards, and other visual aids can be used to communicate and visualise the results.

In practice, data science is already assisting the airline sector in predicting flight interruptions to help both airlines and customers avoid misery. Airlines may improve their operations in a variety of ways with the help of data science, including:

Plan your itineraries and decide whether to fly direct or connect.
To predict flight delays, create predictive analytics algorithms.
Provide clients with customised promotional offers depending on their booking patterns.
Choose which plane class to buy for better overall performance.

Data science is important in every aspect of digital as well as offline recurring data methods. Its existence has solved major flaws in human society and continues to do so.

Data Science Prerequisites

Here are some technical terms you should be familiar with before diving into the world of data science.

1. Machine Learning

The backbone of data science is machine learning. Data scientists must have a strong understanding of machine learning (ML) as well as a fundamental understanding of statistics.

2. Statistics

The foundation of data science is statistics. With a firm grasp of statistics, you can extract more intelligence and produce more relevant results.

3. Modelling

Based on what you already know about the data, mathematical models allow you to make quick calculations and predictions. Modelling is another aspect of machine learning, and it entails determining which algorithm is best for solving a specific problem and how to train these models.

4. Databases

You must grasp how databases function, how to maintain them, and how to extract data from them in order to be a competent data scientist.

5. Programming

A successful data science project necessitates some level of programming. Python and R are the most widely used programming languages. Python is particularly popular because it is simple to learn and supports a variety of data science and machine learning libraries.

What is a Data Scientist?

Data scientists are particularly interested in fraud, particularly online fraud. Data scientists use their abilities to design algorithms to detect and prevent fraud. Data scientists are employed in a wide range of fields. Each is critical to problem-solving and necessitates specialised knowledge. Data capture, preparation, mining and modelling, and model maintenance are among these fields. Data scientists take raw data and convert it into a wealth of knowledge using machine learning algorithms to provide answers to questions posed by businesses.

A data scientist examines corporate data in order to derive actionable insights. To put it another way, a data scientist solves business challenges by following a set of procedures, which include:

Obtain data from a variety of sources, including company data, public data, and so on.
Process raw data and turn it into an analysis-ready format.
Feed the data into the analytic system, which could be a machine learning algorithm or a statistical model.
Prepare the findings and conclusions to be shared with the relevant parties.

Five Ways Data Science can Add value to Businesses in 2021

1. Providing management and officers with the tools they need to make better decisions.

By ensuring that the staff's analytics capabilities are maximised, an experienced data scientist is likely to be a valued advisor and strategic partner to the organization's higher management. Through measuring, tracking, and documenting performance metrics and other information, a data scientist conveys and illustrates the value of the institution's data to support improved decision-making processes across the entire company.

2. Trends are used to guide actions, which in turn aid in the definition of goals.

A data scientist evaluates and explores an organization's data before recommending and prescribing specific measures that would help the institution enhance its performance, better engage customers, and increase profitability.

3. Encouraging Employees to Adopt Best Practices and Concentrate on Critical Issues

One of a data scientist's responsibilities is to guarantee that the company's analytics product is well-known and understood by its employees. They set the team up for success by demonstrating how to use the system effectively to extract insights and drive action. After the team has a good understanding of the product's capabilities, they may work on solving significant business problems.

4. Locating Possibilities

Incorporating data science evaluates existing procedures and assumptions while interacting with the organization's present analytics system in order to build new methodologies and analytical algorithms. Data science improves the value obtained from the organization's data on a continuous basis.

5. Target Audiences: Identifying and Refining

Most businesses will collect consumer data from a variety of sources, including Google Analytics and customer surveys. However, data is useless if it isn't used properly, such as to identify demographics. The value of data science is predicated on the capacity to connect existing data that isn't always relevant on its own with other data points to develop insights that a company can use to learn more about its customers and audience.

A data scientist can assist in the precise identification of significant groups through a thorough investigation of diverse data sources. Organizations may personalise services and goods to specific consumer groups and increase profit margins with this in-depth knowledge.

Lifecycle of Data Science projects

A full overview of the stages involved in a data science project's lifetime can be found in the following:

Study of the Concept

The idea research is the first step in every data science project. The purpose of this step is to figure out what's wrong by looking at the business model. Let's imagine you're attempting to forecast the price of a 1.35-carat diamond. In this situation, you must first learn the industry's vocabulary as well as the business challenge, and then gather enough relevant data about the industry.

Preparation of Data

Data preparation is the most important part of the data science lifecycle because raw data may not be usable. A data scientist must first look over the data to see if there are any gaps or data that isn't useful. Several steps must be completed during this procedure, including:

Integration of data: Remove any redundancy from the dataset by resolving any conflicts.
Transformation of data: ETL (extract, transform, load) procedures can be used to normalise, transform, and aggregate data.
Reduction of data: Reduce the size of data without sacrificing quality or outcome by employing a variety of tactics.
Cleaning of data: Fill in missing numbers and smooth out noisy data to fix inconsistencies.

Model Preparation

After you've cleaned up the data, you'll need to pick a model that fits your needs. Is it a regression problem or a classification problem? The model you choose must reflect the nature of the problem. Exploratory Data Examination (EDA) is also used in this step to give a more in-depth analysis of the data and to better understand the link between the variables. Histograms, box plots, trend analysis, and other EDA techniques are employed.

Model Construction

Building the model is the next step in the lifecycle. You can alter the data with various analytical tools and approaches in order to ‘discover' important information.

Communication

The next stage is to obtain the study's major findings and communicate them to the stakeholders. A good scientist should be able to explain his findings to a business audience, outlining the processes required to solve the problem in detail.

Operationalize

They are launched once all parties have agreed to the findings. Stakeholders also receive final reports, code, and technical papers during this phase.

Applications of Data Science

Data science is now being used in practically every business such as:

Gaming

Data science is currently being used to build video and computer games, which has elevated the gaming experience to new heights.

Recognition of images

One of the most prominent data science applications is detecting objects in photos and identifying patterns in them.

Healthcare

Data science is being used by healthcare companies to develop advanced medical tools that can identify and cure ailments.

Systems of Recommendation

Netflix and Amazon make movie and product suggestions based on your viewing, purchasing, and browsing habits on their platforms.

Logistics

Organisations employ data science to optimise routes in order to assure faster product delivery and increase operational efficiency.

Detection of Fraud

Data science and related algorithms are used by banking and financial institutions to detect fraudulent activities.

Data Science as a Profession

Data science and associated disciplines have seen a large increase in job openings over the previous five years. According to the 2021 forecast, the number one job in the United States is data scientist. Data Scientist, Machine Learning Engineer, Data Consultant, Data Analyst, and others are some of the significant career roles.

Conclusion

Data is essential for any company because it allows them to make decisions based on trends, statistics, and facts. Because of the importance of data, data science is important as it has evolved into a multi-disciplinary profession. To extract insight from a large amount of data, it employs scientific methodologies, frameworks, algorithms, and procedures. Data science is the backbone of any enterprise these days, and current trends indicate that it will become much more important.

In the future decade, data will be the oil for businesses. Companies may now estimate future growth and assess potential dangers by incorporating data science techniques into their operations. Any company that can effectively use its data can benefit from data science. Data science is valuable to any organization in any industry, from statistics and insights throughout workflows and hiring new applicants to assist senior employees in making better-informed decisions.

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Sep

10 Real World Examples of IoT Applications

iCert Global Other 0 2021-09-13 8180

Introduction

The Internet of Things (IoT) is no longer a mystery fad. It's a technology that has quietly gained traction and is now altering our future invisibly. The Internet of Things is the outcome of humanity's curiosity and desire to live a more convenient and connected lifestyle, which reduces work and eliminates the possibility of human error. That is why devices have evolved to take care of tasks that require efficiency. Humanity has realized that data is the new money, and that data can be used to address and fix a wide range of important issues, which is what drives the Internet of Things notion.

IoT is a technology agency that affects several industries. In addition, for IoT experts, a bright future is shining on the horizon.

Engineers enabled the gadgets to collect and share data and make accurate and educated judgments using Machine Learning and Neural Networks by connecting them and the internet (complex mechanisms). This step has yielded excellent results. As you read this, billions of linked devices are collecting billions of petabytes of data every day all around the world. These vast data sets contain critical pieces of information that can help with home security, entertainment, and even water conservation and fuel emission management.

Here is the list of Top 10 Real World Examples of IoT Applications are:

1. Houses with Smart Technology

2. Autonomous Vehicles

3. City of the Future

4. Shops that sell IoT products

5. Wearables

6. Farming

7. Smart Grids

8. Internet of Things in Industry

9. Telehealth

10. Supply-chain Management with Intelligence

Top 10 Applications of IoT

1. Houses with Smart Technology

Smart homes are one of the best and most practical IoT applications because they take both convenience and home security to the next level. Though IoT can be used at several levels for smart homes, the finest is the one that combines intelligent utility systems and entertainment. Your electricity meter with an IoT device that gives you insights into your daily water usage, your set-top box that allows you to record shows from a distance, Automatic Illumination Systems, Advanced Locking Systems, and Connected Surveillance Systems are all examples of smart homes. As the Internet of Things progresses, we can expect most gadgets to become smarter, allowing for improved home security.

2. Autonomous Vehicles

There has been a lot of talk about self-driving automobiles. Google experimented with it, as did Tesla, and Uber even developed a self-driving car that was ultimately shelved. Because we're dealing with human lives on the roadways, we need to make sure that the technology has all it needs to improve passenger and road safety.

Automobiles use a variety of sensors and embedded technologies that are connected to the Cloud and the internet to continuously generate data and send it to the Cloud for Machine Learning-based decision-making. Though it will take a few more years for the technology to mature fully and governments to adjust their laws and policies, we are currently experiencing one of the best IoT applications.

3. City of the Future

Smart cities are expected to be made up of not just internet connection for people in a city, but also access to the city's devices. And we can happily report that we're on our way to making this idea a reality. Efforts are being made to integrate linked technology into infrastructural requirements as well as certain critical concerns such as traffic management, waste management, water distribution, and electricity management, among others.

All of these things help to alleviate some of the problems that people experience daily while also adding convenience.

4. Shops that sell IoT products

You should see the video of Amazon Go — the eCommerce giant's concept store – right away if you haven't already. Perhaps the best application of technology for bridging the gap between an online store and a physical store is this. By deducting money from your Amazon Wallet, the retail outlet allows you to go cashless. When you select items from the shelves, it also adds them to your cart in real-time.

If you change your mind and choose another item, the prior one is removed from your cart and replaced with the new one. The concept store's best feature is that there is no cashier to bill your purchases. You don't have to wait in line; simply walk out after picking up your items from the shelves. If this technology proves to be beneficial in attracting more customers, it will undoubtedly become the norm in the coming years.

5. Wearables

IoT wearables are reshaping the way we receive healthcare and providing innovative insights and analytics for business sponsors, physicians, and patients. Data from IoT devices can help healthcare, pharmaceutical, and life science companies make better decisions and gain a competitive advantage.

Even now, wearables are a popular topic in the market. These gadgets are used for a variety of applications, including medical, health, and exercise. Jawbone, a wearables company, is the most well-funded of all the IoT businesses.

6. Farming

One of the industries that will benefit the most from the Internet of Things is agriculture. With so many advancements being made in agricultural gear, the future looks bright. Drip irrigation, crop patterns, water distribution, drones for farm surveillance, and other tools are being developed. These will enable farmers to produce a higher-yielding crop and better address their concerns.

On the farm, the Internet of Things allows devices to remotely measure various data and provide this information to farmers in real-time. IoT devices can collect information such as soil moisture, chemical applications, dam water levels, and livestock health, and monitor fenced vehicles and weather.

7. Smart Grids

Smart grids are part of the IoT framework and can be used to remotely monitor and manage everything from lighting, traffic signs, traffic jams, parking spaces, road warnings, and early event detection. such as the inrush of energy caused by earthquakes and extreme weather conditions.

A smart grid, for example, is a holistic system that employs a wide range of Information Technology resources to enable current and new gridlines to reduce electricity waste and costs. Electricity efficiency, reliability, and economics will all benefit from a future smart grid.

8. Internet of Things in Industry

The Industrial Internet of Things is made up of interconnected sensors, instruments, and other devices that are linked to industrial computer applications such as production, energy management, and so on. While the industrial internet is currently unpopular in comparison to IoT wearables and other uses, market research firms such as Gartner, Cisco, and others feel it has the greatest overall potential.

The IoT supports technologies such as cybersecurity, cloud computing, edge computing, mobile technology, machine-to-machine, 3D printing, advanced robotics, big data, the Internet of Things, RFID technology, and cognitive computing.

9. Telehealth

Telehealth, often known as telemedicine, is still in its infancy. Nonetheless, it has a bright future ahead of it. IoT Telemedicine includes digital medical imaging communication, remote medical diagnosis and evaluations, video consultations with specialists, and so on. The Internet of Things can promote various medical applications, such as remote health monitoring, body conditioning programs, rehabilitation, chronic diseases, and elderly care (Adibi, 2015). Compliance with remote monitoring of treatments and medications at home is an important potential for telemedicine applications.

10. Supply-chain Management with Intelligence

Supply chains have been around for a long time in the market. Solutions for tracking things while they're on the move are excellent examples. They are certain to stay in the market for a long time, thanks to IoT technology.

Intelligent supply chain management requires the implementation and use of modern technology to optimize all aspects of the supply chain. With the help of smart supply chains, companies can save costs, earn more revenue, speed up customer contact, and stay ahead of the competition.

How close is IoT to the Real World?

IoT is constantly changing, and it is being tested and used in more ways than you might think. Smart Breweries, Smart Coffee Machines, Smart Parking Facilities, Smart Supply-chain Mechanisms, and other IoT examples are just a few.

The breadth of the Internet of Things, according to Fortune Business Insights, the worldwide Internet of Things market was valued at US$250.72 billion in 2019 and is expected to reach US$1,463.19 billion by 2027, growing at a 24.9 percent compound annual growth rate (CAGR).

Conclusion

In just one year, the number of internet-connected gadgets has increased from 5 million to billions. According to Business Insider Intelligence, 24 billion IoT devices will be installed by 2021, generating over $300 billion in income.

The Internet of Things iterates, improves and expands. Its networks aren't pre-assembled; instead, they develop throughout time. To create a smarter society, the Internet of Things (IoT) has connected hardware and software to the internet. It has been rapidly expanding and provides a plethora of options for both government and business. Indeed, the number of job postings for IoT experts has reached an all-time high.

As a result, now is the greatest time to start investigating this technology's true potential. Because the Internet of Things (IoT) is here!

The Internet of Things is a concept that connects the virtual world of information technology to the real world. IoT technologies such as RFID and sensors make our lives better and more comfortable.

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Aug

Top 20 Trending Technologies in 2021

iCert Global Other 0 2021-08-27 22286

Top 20 Trending Technologies in 2021

Introduction

The 21st century, a century of technological change. In the early 2000s, some of the highly commercial and fashionable technologies disappeared altogether, and new technologies gained their place. In 2021, a number of entirely new technologies emerged, especially in the fields of computer science and engineering. Due to the outbreak of COVID19, more changes have taken place this year, making IT professionals aware that their roles will no longer be the same. In the contactless world of tomorrow. IT professionals in 2021 will continue to learn, forget and relearn out of necessity, if not hope. In 2021, these new technologies have the potential to grow and possibly reach the general public.

Here is the list of Top 20 Trending Technologies in 2021:

1. Artificial Intelligence and Machine Learning

2. Data Science

3. Full Stack Development

4. Robotic Process Automation

5. Edge Computing

6. Virtual Reality and Augmented Reality

7. Blockchain

8. 5G

9. Cyber Security

10. Quantum Computing

11. Internet of Things

12. Big Data Analytics

13. Human Augmentation

14. Everything-as-a-Service(XaaS)

15. DevSecOps

16. Predictive & Personalised Medicine

17. Voice Search Technology

18. Drones and Unmanned Vehicles

19. Mass personalization and Micro-Moments.

20. Genomics and Gene Editing

1. Artificial Intelligence and Machine Learning - A strong AI implementation will promote performance, scalability, and reliability, while providing a full return on investment. But artificial intelligence projects often face certain problems, which is a challenge for most organizations. But there are new solutions to solve these problems. Machine learning represents a field of computing in which algorithms can predict future data based on previously generated data. Artificial intelligence represents the next step in machine learning, in which algorithms develop database intelligence and can even perform basic tasks on their own.

In areas such as retail and e-commerce, machine learning is an important part of improving user experience. The product recommendations you see on such sites are usually the result of a machine learning algorithm that analyzes your previous searches and recommends similar products. In the field of healthcare, machine learning can help analyze data and provide doctors with treatment information. Although AI helps us every day, considering its potential, it will still be a new technology in 2021.

2. Data Science - In the 2020s, data analysis is likely to blow up more than ever. With computational technology growing at a more excellent pace than ever, the data analysis capabilities in people’s hands are likely to increase. Newer, faster data analysis algorithms and methods are likely to come up and be put into practice.

The benefit of having a career in data science, regardless of the domain your company works in, is that you are an essential part of the firm’s overall business. The data that you produce and the interpretations that you provide are likely to be a necessary part of the business strategy of any company that you serve. No matter what field your company works in, the advantage of a data science career is that you are an important part of the company's overall business. The data you generate and the explanations you provide can be a necessary part of the business strategy of any business you serve.

3. Full Stack Development - The 21st century began with the rise of .com and the Internet, a relatively new phenomenon that is spreading to households all over the world. In those days, websites were nothing more than simple web pages, and web development was not as complex as it is today.

Today, Web development involves front-end and back-end. Especially for service-related fields such as retail and e-commerce, the website includes the client side (the website you view) and the server side (the website controlled by the business).

Usually the task of a web developer is to deal with the client or server side of the website. However, as a full-stack developer, you and your company have the flexibility to work at both ends of the web development spectrum. Clients or front-end generally need to understand packages like HTML, CSS, and Bootstrap. The server side requires knowledge of PHP, ASP and C ++.

4. Robotic Process Automation - Robotic process automation is more than just robots. Compared to anything else, process automation is more important. Before the advent of computers, most processes involved some human intervention. Humans even operate manufacturing machines, and large-scale manufacturing employs thousands of people.

However, since computers have taken over most of the processes, the manufacturing industry has not been affected. All fields, be it manufacturing or information technology, now involve some automation in their processes. The amount of human intervention in these processes will only decrease, and this trend may continue for the foreseeable future.

These processes can mean anything, from automated email responses to automated data analysis and automated processing and approval of financial transactions. Robotic process automation speeds up tasks for ordinary consumers by automatically performing such approvals based on certain conditions entered by programmers.

In industries such as financial services, robotic process automation can reduce the lean time for online approval of financial transactions. It improves the productivity of the entire company and its customers.

5. Edge Computing - Edge computing has great applications in IoT devices. When it comes to the Internet of Things, the physical devices that you need to control with your smartphone don't need to access data in centralized repositories that can be located thousands of miles away. Instead, the data should be as close to the device as possible.

Edge computing enables data to be processed at the "edge" of the cloud and devices so commands can be completed in less time.

The next step after cloud computing is edge computing. This is another trending technology emerging in 2021, very similar to cloud computing, except that the data is not stored in a centralized repository. In areas where network access is difficult or impossible, cloud computing is challenging because you can no longer access the repository where the data is stored. The role of edge computing is to transmit data closer to where it needs to be used.

6. Virtual Reality and Augmented Reality - Innovative technologies provide more immersive experiences, such as AR and VR. Virtual reality immerses users in a simulated environment, and augmented reality is a superposition of technologies in the real world. Cisco predicts that by 2022, ARVR traffic in all entertainment sectors worldwide will increase 12 times.

Nowadays, virtual reality work does not require a lot of training. Simple programming skills should be enough to find a job, as well as interest in the field and the power of visualization. With millions of virtual reality devices sold around the world every year, it is only a matter of time before we see that virtual reality and augmented reality take over our daily lives.

7. Blockchain - Thanks to the security provided by the blockchain, this data can be shared seamlessly between all parties. Another application of blockchain is maintaining the integrity of the payment system. Blockchain-based payment systems are currently highly immune to external attacks and theft. Blockchain can also be used to track the status of products in the supply chain in real time. In recent years, you may have heard of blockchain, primarily in the context of cryptocurrency. However, blockchain has evolved to have several different applications. The important part of the blockchain is that it is never completely controlled by a single entity, because it is driven by total consensus. It will never change the data you store on the blockchain, which is widely used for sharing medical data in the healthcare industry.

8. 5G - 5G technology is the next generation of cellular networks and services. It is expected to provide at least a 20GBPS downlink and a 10GBPS uplink, making the 5G network at least 40 times faster than current 4G LTE. This will open the door to new services, network operations and customer experience for telecom operators. Currently, the market is led by

Switzerland, followed by South Korea and the United States.

When 5G technology is still in the development stage, there are few 5G jobs, and most jobs are assigned to employees within the company. However, in recent months, the company has begun recruiting network engineers to specialize in work related to its 5G network.

As 5G technology becomes more and more popular, there have been efforts among networks to purchase spectrum and deploy the technology first. This has led to the need for more labor to focus on the development and launch of 5G networks.

9. Cyber Security - With so many organizations undergoing a tremendous digital transformation, awareness of upcoming cyberattacks continues to rise, not only for large organizations, but also for small businesses.

Now, cyber security is nothing new, but its trend definitely is!

Virtual Distributed Network (VDN) is a unique network security method in which signals are transmitted in the form of short pulses or quantum data packets and cannot be secretly read without destroying their content. Basically no one can intercept the data sent to them without introducing some noise.
Blockchain cyber security is a more modular and responsive security method through centralized orchestration and distributed execution.

10. Quantum Computing - The next noteworthy technology trend is quantum computing, which is a form of computing that uses quantum phenomena such as superposition and quantum entanglement. This surprising technological trend also involves the prevention of the spread of the coronavirus and the development of potential vaccines, thanks to its ability to easily query, monitor, analyze and process data, regardless of the source of the data. Another application area of quantum computing in banking and finance, credit risk management, high-frequency trading and fraud detection.

11. Internet of Things - Another promising new technology trend is the Internet of Things. Many "things" are now being built to connect to WiFi, which means they can connect to the Internet and connect to each other. Therefore, the Internet of Things or the Internet of Things. The Internet of Things is the future. It has enabled devices, household appliances, automobiles, etc. to connect and exchange data via the Internet.

12. Big Data Analytics - Big data analytics has been in the market for a long time. More and more companies are adopting it to go beyond traditional data storage and processing methods.

Big data analytics also provides us with interesting trends. For example, decision intelligence provides a framework to help data engineers design, model, execute, and monitor decision models and processes in the context of business outcomes and behaviors. In fact, by 2023, more than 33% of large organizations will allow analysts to practice decision intelligence.

13. Human Augmentation - Humans have constantly tried to use technology to improve the lives they know. This curiosity has now entered another field: human enhancement, which basically means that with the help of technologies such as artificial intelligence and the Internet of Things, we can not only improve our daily lives, but also human intelligence can be elevated. to a new level.

Today, these studies are committed to helping the disabled through bionics and artificial limb enhancement, and treating disease through genetic testing. But the promise is to end the existing physical disability or prevent the injury entirely.

14. Everything-as-a-Service(XaaS) - Everything-as-a-Service (XaaS) is a cloud computing term that refers to various services and applications that appear for users to access on-demand through the Internet instead of using local media. It gives you the flexibility to customize your computing environment to create the experience you want, everything on demand. XaaS has been expanded to include many services, such as:

FunctionasaService
ITasaService
Infrastructure as a Service
Security-as-a-Service
Database-as-a-Service

As these applications become more portable, the calculation cycle is easier to obtain in real time, and the data integration platform simplifies the connection and provider form cross-platform Alliance, this may soon start to look more like Omnicloud.

15. DevSecOps - DevSecOps is short for Development, Security, and Operations. Their goal is to implement security at the same scale and speed as development and operations, not just for them. With the widespread adoption of microservices, DevSecOps appears to have entered our DevOps market more deeply.

This is not all. An operating model anywhere is critical for companies to successfully differentiate themselves from today's economy. Essentially, this operating model allows services to be accessed, delivered, and activated anywhere. This format is now exploring other aspects of the technology, such as GitOps, DataOps, and NoOps.

16. Predictive & Personalised Medicine - Technology is pushing medical care forward at an expanding rate: the potential to receive data about the lifestyle from smartwatches (like Apple Watch, Fitbit etc.) provides medical professionals with the ability to forecast and even treat possible health problems before a patient even has any symptoms. This means that the medical status of each customer will be tracked and considered by insurance companies only when the risks associated with their lifestyle and habits are determined. When it comes to treating these patients, this technology trend will help doctors prescribe more personalized medicine, often referred to as predictive medicine. The info-driven understanding of how useful some treatments are for people will boost the healthcare market in 2021. This is the top trending technology in 2021

17. Voice Search Technology - The Voice Search allows users to speak into a device rather than typing keywords for a search query to generate results. This technology trend uses speech identification to understand what a user is saying with high accuracy and then delivers the result through voice to the user.

For a long time, voice search technology has been in the tech market, software like speech-to-text and voice dialing are some excellent examples of voice search and as we have discussed above, devices like Amazon Echo use voice search as their main functionality and due to these extensive features, this technology trend improves the user experience to the fullest – and because of this, by the year 2020, 50% of all online searches will be made through voice search technology.

18. Drones and Unmanned Vehicles - This is the top trending technology in 2021 and will be top trending technology in upcoming years. These aircraft, manned either remotely or autonomously, have changed the face of military operations - but the impact doesn’t stop there: Search and Rescue missions, firefighting, law enforcement and transportation will all be transformed by drone technology - get ready for passenger drones (drone taxis) too!

19. Mass Personalization and Micro-moments - Mass-personalization is the ability to offer highly personalized products or services on a mass scale; while the term "micro-moments" essentially means to respond to customer needs at the exact right time – both are made possible by technologies such as AI, Big Data and analytics.

20. Genomics and Gene Editing - Genomics and gene editing are the top trending technologies in 2021. Advancements in computing and analytics have driven incredible leaps in our understanding of the human genome and now we’re trying to change the genetic structure of living organisms (for example, to “correct” DNA mutations that can lead to cancer).

Conclusion:

The global economy will resurface in 2021 and new technologies will almost certainly drive this trend. The major tech trends mentioned above may take over our daily lives for years to come. Work related to these technologies and skills will be very valuable. In the long run, getting an education related to them will definitely help you a lot in your career. Choosing and mastering the right new technology in 2021 will help you face the future.

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Aug

Find the Length of a List in Python:Easy Methods & Examples

iCert Global Other 0 2021-08-26 1500

How to Find the Length of List in Python?

Introduction- Software developers and data scientists all over the world have a great demand for Python. Lists are an indispensable part of daily Python programming. All Python users should understand their profits and operations which is essential and is always an advantage. A list in Python is an ordered and changeable collection data type. The list can also have duplicate entries.

A list is implemented in Python to store sequences of various data types. However, there are six data types in Python that can store sequences, but the most common and reliable type is a list. One of the very similar features such as the list is Arrays. The difference between lists and arrays is that they provide a more compact and efficient way to store large numbers of items.

Although matrices involve numerical operations, there is no need to perform direct mathematical activities on lists.

List being an integral part of Python day-day programming has to be learned by all the python users and having a knowledge of its utility and operations is essential and always a plus.

If you are a new IT or software professional, or a data professional, you should be proficient in this programming language.

Most refresher courses are designed to familiarize candidates with Python by using the basics of programming, statistical tools, and predictive analysis as part of the main project and coursework.

How to find the length of a list in python?

Calculating the length or size of the list is similar to finding the total number of items present in the list. For example, if list1: list1 = [5,4,7,2,9,6], then the length of list lis1 is 6. Because the total number of elements or elements is 6.

There are two basic and most commonly used methods for finding the length of a list in Python:

- Len() method

- Naive method

- Using The __len__() Method

- Using length_hint()

- Using Python for loop to get length method

1. Len() Method:

There is a built-in function called len() to get the total number of elements in a list, tuple, array, dictionary, etc. The len() method accepts a parameter in which you can provide a list and return the length of the list.

The len() method is one of the most widely used and convenient methods for finding the length of a list in Python. This is the most traditional technique used by all programmers today.

The built-in len() method in Python is widely used to calculate the length of any type of sequential data. Calculate the number of elements or the number of elements of the object, and return the same value as the length of the object.

Therefore, we can directly obtain the length of a list and pass it to the built-in method len().

The syntax of the len () function

The basic syntax of the len () function in Python is as follows:

len (List_name)

Parameters:

Parameters - List_name

Description - The length of the list will be calculated.

Return value - will return an integer value that is the length of the list.

Definition list - the list is enclosed in brackets

Example:- len (list)

The List parameter is a list to count the number of elements. Returns the number of items in the list.

ListName = ["Hello", "Alexa", 1, 2, 3]
print ("Number of items in the list = ", len(ListName))

Output:5

2. Naive Method:

The len(list) method The len() method is the most widely used method for finding the length of a list in Python. But there is another basic way to provide the length of the list.

In the Naive method, you only need to loop and increment the counter to the last item in the list to know its count. This is the most basic strategy that can be used without other effective techniques.

In other words, In this Naive method, we use the count variable to find the number of items in the list. It is a technique that uses an established (para) control loop format. In this set, the controlled loop does not follow any conditions, it only follows the length of the set. To do this, we simply add 1 to the value of the count. Finally, it returns the number of elements.

Example:

ListName = [ "Hello", "Alexa", 1,2,3 ]
print ("The list is : " + str(ListName))
counter = 0
for i in ListName:
counter = counter + 1
print ("Length of list using naive method is : " + str(counter))

Output: The list is : ["Hello", "Alexa", 1,2,3]

The length of a list using the naive method is: 5

It's about finding the length of the list in Python. The len () method is the most popular method. However, you can also use the basic method to find the length with the help of the naive method.

3. Using The __len__() Method:

The __len __ () method is another built-in Python method that can be used to find the length of a list.

Although the len () and __len __ () methods appear similar, there is the slightest difference between the two.

When the len () function is called, it calls the __len __ () method internally, which returns the count of elements in the sequence, which is a list. Also, we can directly call the __len __ () method.

Example:

# Python program to find length of list

# Use __len __() method

# Initialize the list to find the length

MyList = [`Red`,`Yellow`,`Green`,`Orange`,`Pink `]

Length = MyList. __ len __()

print("The length of the list is: ", Length)

Output:

The length of the list is: 5

4. Using length_hint():

This technique is a little known technique for finding the length of a list. This special method is defined in the operator class and can also indicate that it is not. Items present in the list.

Definition - Returns with the length of iterable items.

Syntax - Operator.length_hint()

Parameters - objective, iterable

Example:- Demonstrating finding length of list using len() and length_hint()

# Python code to demonstrate

# length of list

# using len() and length_hint

from operator import length_hint

# Initializing list

test_list = [ 1, 4, 5, 7, 8 ]

# Printing test_list

print ("The list is : " + str(test_list))

# Finding length of list

# using len()

list_len = len(test_list)

# Finding length of list

# using length_hint()

list_len_hint = length_hint(test_list)

# Printing length of list

print ("Length of list using len() is : " + str(list_len))

print ("Length of list using length_hint() is : " + str(list_len_hint))

Output :

The list is : [1, 4, 5, 7, 8]

Length of list using len() is : 5

Length of list using length_hint() is : 5

5. Using Python for loop to get length method:

To find the length of a list in Python, using the for loop is considered a traditional technique or a naive method, as shown below:

Declare a counter variable and initialize it to zero.

Use a for loop to loop through all data items. After each item is found, the counter variable is incremented by 1.

In this way, the length of the array will be stored in the counter variable, because the variable will represent the number of items in the list.

Example: inp_lst = ['Python','Java','Kotlin','Machine Learning','Keras']

size = 0

print("Length of the input string:")

for x in inp_lst:

size+=1

print(size)

Output:

Length of the input string: 5

List in Python:

A list is implemented in Python to store sequences of various data types. However, there are six data types in Python that can store sequences, but the most common and reliable type is a list.

A list is defined as a collection of different types of values or elements. Items in the list are separated by commas (,) and enclosed in square brackets [].

It is defined as follows:

list1 = ['alexa', 'python', 2019];

list2 = [1, 2, 3, 4, 5 ];

list3 = ["a", "b", "c", "d"];

The execution time of various methods to find the length of the list in python:

len(): 0.0 (seconds)
__len__() : 0.0 (seconds)
length_hint(): 0.00046 (seconds)
Naive method: 0.00057 (seconds)

Therefore, len() is the best way to find the length of the list in python and can be used because it has the shortest execution time of all available methods.

Conclusion:

Python List is now known to be a variable ordered sequence. It can contain heterogeneous and homogeneous elements. It is a widely used data structure in Python. For traversal and other operations on the list, sometimes it is necessary to find the length of the list. It's about finding the length of the list in Python. The len () method is the most popular method. You can clearly see that the time spent is naive >> length_hint ()> len (), so len () is the best option.

However, you can also use the basic method to find the length of the list in Python with the help of the naive method. This information on measuring the length of a list in Python is one of the most basic things you should do as a beginner. So, use the steps above to improve our programming skills and stay curious to learn more!

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Jan

Top 10 Trending Technologies to Watch Out for in 2021!!

iCert Global Other 0 2021-01-05 2419

Here is the list of Top 10 Trending Technologies In 2021:

1. Machine Learning

2. Data Science

3. Robotics Process Automation

4. Edge Computing

5. Quantum Computing

6. Virtual Reality and Augumented Reality

7. Blockchain

8. Internet of Things (IOT)

9. 5G

10. Cyber Security

1. Machine Learning:

Machine Learning

Machine learning (ML) is the study of computer algorithms that improve automatically through experience. It is seen as a subset of artificial intelligence. Machine learning is an exciting branch of Artificial Intelligence and continues to be one of the new technology trends. With the aid of machine learning, computers will be programmed to learn to do which they are not programmed to do so. Due to the new computing mechanization, the machine learning program has changed a lot, which means it is not the same as it was in the past. Machine learning practices are used for data mining, data analytics, and pattern recognition. Machine Learning is already being deployed in many different industries thus creating demand for skilled professionals. Every big company and organization is focusing on improving the customer experience and modernizing their business actions by using AI. The machine learning business is looking forward to enlarging to $9 billion by 2022. With AI spreading across sectors new jobs will be created and it is predicted that Machine Learning and Artificial Intelligence will create almost 10 percent of new jobs by 2025 in USA.

2. Data Science:

Data Science

Data Science has become a revolutionary technology that everyone seems to talk about. Data science is about extracting, analyzing, visualizing, managing and storing data and requires the usage of both structured and unstructured data. Data scientists must have the skills and proficient training to help conquer important goals that are possible or essential for a great deal with more time and energy. Data Science is growing rapidly and transforming many companies across the globe. Kaspersky a leading cyber security company is applying data science and machine learning to look for 300,000+ samples of malware on a regular basis. Data Science is in great demand and predicted create 12 million jobs by 2026. It is also one of the highest paying jobs with an average salary of $125,000 per annum.

Data scientists often come from many different educational and work experience backgrounds, most should be strong in, or in an ideal case be experts in four fundamental areas. In no particular order of priority or importance, these are:

Business/Domain

Mathematics (includes statistics and probability)

Computer science (e.g., software/data architecture and engineering)

Communication (both written and verbal)

3. Robotics Process Automation:

Robotic process automation is gaining a lot of traction and being adopted and implemented in businesses of every industry. Robotic Process Automation allows an individual to arrange computer software or robot to copy and incorporate the actions of the human relating with digital systems to develop a business process. RPA uses structured inputs and logic, As an IT Professional who is looking to make a career in RPA it offers plenty of opportunities like Business analyst, solution architect, project manager, development and consultant. The average salary of an Robotic Process Automation professional ranges from $ 130,000 - $170, 000.

4. Edge Computing:

Edge computing is a distributed, open IT architecture that features decentralized processing power which enables mobile computing and Internet of Things (IoT) technologies. In edge computing the data is processed by the device itself or by a local computer or server, rather than being transmitted to data Centre. The upcoming fastest network which happens to be 5G is allowing edge computing systems to advance the forming of real time supplications like analytics, artificial intelligence robotics and self-driven cars. Edge computing offers high speed, reduced latency and better reliability which allows quicker processing and content delivery. It is predicted that the edge markets is headed for strong growth over the next few years. The global revenue for edge devices and networks deployed for AI will reach $828 billion by 2025.

5. Quantum computing:

Quantum computing is the use of quantum phenomena such as superposition and entanglement to perform computation. Quantum computers perform calculations based on the probability of an object's state before it is measured - instead of just 1s or 0s - which means they have the potential to process exponentially more data compared to classical computers. Quantum computer are reinventing aspects of cyber security through their ability to break codes and encrypt electronic communications. Tech giants like Microsoft, Google, Intel, Alibaba and IBM are exploring quantum computing for better cyber security. The quantum computing market is expected to reach $2.2 billion by 2026.

6. Virtual Reality and Augmented reality:

Virtual Reality is defined as the use of computer technology to create a simulated environment and Augmented reality is defined as enhanced version of reality created by the use of technology to add digital information on an image. Virtual reality and augmented reality bridge the digital and physical worlds. They allow us to take in information and content visually, in the same way you take in the world. Virtual reality is widely used for gaming purposes; however the military sector which has always been at the forefront of using emerging technologies is adapting virtual reality for training purposes and combat enhancements. Virtual reality has huge potential in gaming, entertainment, marketing, training and education industry. The global VR and AR market was $11 billion in 2017 and expected to reach $571 billion by 2025. Getting started in VR and AR doesn’t require any specialized knowledge, basic programming skills should suffice to help you get a job in this sector.

7. Blockchain:

Blockchain, which began to emerge as a real-world tech option in 2016 and 2017, is poised to change IT in much the same way open-source software did a quarter century ago. It is based on peer-to-peer (P2P) topology, blockchain is a distributed ledger technology (DLT) that allows data to be stored globally on thousands of servers – while letting anyone on the network see everyone else's entries in near real-time. That makes it difficult for one user to gain control of, or game, the network.

Many industries are implementing blockchain, and as the use of blockchain technology increases, so does the demand for skilled professionals. Block chain developer specializes in developing and implementing architecture and solutions using block chain technology. Driven mainly by financial technology (fintech) investments, blockchain has seen a fast uptick in adoption for application development and pilot tests in a number of industries and will generate more than $10.6 billion in revenue by 2023. The average salary ranges from $130,000 - $150,000 per annum.

8. Internet of Things (IoT):

The Internet of Things (IoT) describes the network of physical objects—“things”—that are embedded with sensors, software, and other technologies for the purpose of connecting and exchanging data with other devices and systems over the internet. These devices range from ordinary household objects to sophisticated industrial tools. With more than 7 billion connected IoT devices today, experts are expecting this number to grow to 10 billion by 2020 and 23 billion by 2025. As consumers we are already using IoT in our daily lives like controlling thermostat to turning up the volume on the TV to dimming the lights and more, soon practically every device will be connected for streamlined control. Smart cities are on the rise, and IoT developers are devising ways to use the IoT to monitor city conditions such as traffic, air quality, electric/water usage, and environmental factors. Doing so can assist city planners as well as residents to come up with solutions to current issues and conserve resources.

9. 5G:

5G is the 5th generation mobile network. It is a new global wireless standard after 1G, 2G, 3G, and 4G networks. 5G enables a new kind of network that is designed to connect virtually everyone and everything together including machines, objects, and devices. 5G runs on the same radio frequencies that are currently being used for smartphones, on Wi-Fi networks and in satellite communications, but it enables technology to go a lot further. The 5G technology is growing faster than initially thought and more businesses and individuals, will have access to it in less time than we imagined.5G services are expected to launch in 2021 globally. The global 5G services market is expected to grow at a compound annual growth rate of 43.9% from 2021 to 2027 to reach USD 414.5 billion by 2027.

10. Cyber Security:

Cyber-crime is on the rise, and many small scale businesses are extremely vulnerable as a result of ineffective cyber security. Cyber-attacks threaten organizations, customers and employees. Cyber security solutions protects your business, protects personal information, productivity, denies spyware, prevents adware and stop websites from going down. As long as we have hackers around us, the need for cyber security professionals rises and the number of cyber security jobs is growing three times faster than any other tech job. It is estimated that $6 trillion will be spent globally on cybersecurity.

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