With everyone talking about MongoDB and Spark, I’m wondering if I should still invest time in learning deep SQL data analysis techniques. Is the language becoming obsolete, or is it still the primary way that data scientists interact with structured data in 2024 and beyond?
3 answers
SQL is far from obsolete; in fact, it’s experiencing a renaissance. Even tools like Spark and various NoSQL databases have added SQL-like interfaces because the language is so efficient for declarative data retrieval. When you perform SQL data analysis, you are using a standard that has existed for decades for a reason. It is the universal language of data. Most "Big Data" jobs still require SQL as the primary filter for candidates. It is much easier to teach a SQL expert a new tool than it is to teach a tool-specific person the logic of relational algebra.
Do you think the trend of "SQL-on-everything" will continue, or will we eventually see a new language take over for SQL data analysis?
Most modern BI tools generate SQL code under the hood, so knowing SQL data analysis helps you troubleshoot when those tools produce incorrect results.
Exactly, Betty. Understanding the underlying code gives you a level of control and precision that "drag-and-drop" users simply don't have when things get complicated.
I think it’s here to stay, Justin. Even the newest AI-driven data platforms use SQL as their underlying query engine. It’s too embedded in the global infrastructure to be replaced anytime soon, so your investment in learning it is very safe for your future career.