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Why SQL is still the first data skill to learn

AI tools can write queries, but someone still has to ask the right question and check the answer. That someone needs SQL.

By Priya Raman ·5 min read
Charts and dashboards on a laptop screen

Every few months someone asks me whether SQL is still worth learning now that AI assistants can write queries. My answer hasn't changed: yes, and maybe more than ever.

AI writes queries. You still own the question.

An assistant can turn "show me revenue by region" into a query in seconds. But which revenue? Gross or net? Including refunds? Which time zone defines "last month"? Those choices change the answer, and only someone who understands the data can make them.

SQL is how you check the answer

The most valuable data skill isn't writing a query from scratch. It's reading one and spotting what's wrong: a join that duplicates rows, a filter that silently drops nulls, an average that should have been a median.

SELECT region, SUM(amount) AS revenue
FROM orders
WHERE status = 'paid'
  AND created_at >= DATE '2026-09-01'
GROUP BY region
ORDER BY revenue DESC;

If you can read that and immediately ask "what about refunded orders?", you're already more useful than the tool.

It transfers everywhere

SQL has been around for fifty years and runs underneath almost every product analytics tool, BI dashboard and data warehouse. Learn it once and it pays off in every job you'll have.

Start with five ideas

You can do a surprising amount of real analysis with just:

  • SELECT and WHERE to filter
  • GROUP BY with COUNT, SUM and AVG to summarize
  • JOIN to combine tables
  • ORDER BY and LIMIT to rank
  • Common table expressions (WITH) to keep things readable

Tools change every year. The ability to ask a precise question of your data doesn't go out of date.

Our Data Analysis with SQL course starts from zero and ends with a real business analysis you can present.

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