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Learn SQL for Data Analysis

Turn business questions into queries you can trust.

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SQL for data analysis is the slice of SQL analysts use every day: reading data, not designing databases. It means turning questions like "which customers bought twice last quarter" into SELECT statements with filters, GROUP BY aggregates and joins, then reaching for CASE expressions, common table expressions and window functions such as ROW_NUMBER and LAG for rankings, running totals and period-over-period changes. Just as important is checking results, since a bad join quietly duplicates rows and inflates totals. Learnr builds a course on SQL for analysis around the questions you need to answer, in short lessons with queries to write and check.

How to learn SQL for Data Analysis, step by step

Learn the grain of every table. Before writing queries, state what one row represents, such as one order or one order line. Most wrong answers in analysis come from misunderstanding grain, especially when joining tables at different levels.
Answer questions with GROUP BY. Count orders by month, sum revenue by product and filter groups with HAVING. Learn the difference between COUNT(*), COUNT(column) and COUNT(DISTINCT column), because NULLs and duplicates change the answer.
Join tables and check row counts. Practice INNER and LEFT JOIN between customers, orders and products. After every join, compare row counts before and after; an unexpected increase means a one-to-many join is fanning out and will inflate sums.
Use CASE and dates for real reports. Bucket customers into segments with CASE WHEN, replace NULLs with COALESCE and truncate timestamps to week or month with your database date functions, which differ between PostgreSQL, BigQuery, SQL Server and others.
Break hard questions into CTEs. Write each step as a named WITH block: first orders per customer, then first purchase date, then a cohort summary. Readable steps are easier to debug than one nested query. A Learnr exercise a day keeps the syntax familiar.
Master a handful of window functions. Use ROW_NUMBER to pick each customer latest order, SUM OVER with ORDER BY for running totals, and LAG to compare a month with the one before. PARTITION BY is the key idea to understand.

What you'll learn

Filter, aggregate and group data with WHERE, GROUP BY and HAVING
Join tables correctly and detect duplicated rows from bad joins
Bucket and pivot data with CASE expressions
Structure multi-step analysis with common table expressions
Use window functions for rankings, running totals and period comparisons

What's inside your SQL for Data Analysis course

A sample path Learnr builds for SQL for Data Analysis. Your real course adapts to your goal and level.

1. SELECT, WHERE and sorting
2. Aggregates, GROUP BY and HAVING
3. Joins and row grain
4. CASE, NULLs and date functions
5. CTEs and subqueries
6. Window functions for analysis

How long does it take to learn SQL for Data Analysis?

Core analysis queries, filters, aggregates and joins, take about 2 to 4 weeks at 4 hours a week. CTEs and window functions usually take another 3 to 6 weeks before they feel natural, faster if you practice on a real company dataset.

What you need before you start

No programming background is needed. Basic spreadsheet experience helps, since rows, columns, filters and sums map directly onto SQL concepts.

Common mistakes to avoid

Joining tables without checking row counts, which duplicates rows and silently inflates revenue or customer totals.
Putting a filter on the right-hand table of a LEFT JOIN in the WHERE clause, which turns it into an inner join. Move that condition into the ON clause.
Forgetting that NULL is not equal to anything, so WHERE column = NULL never matches. Use IS NULL and COALESCE instead.

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SQL for Data Analysis questions, answered

Which SQL dialect should I learn for analysis?

The core is the same everywhere. Learn the one your workplace uses, such as PostgreSQL, BigQuery, Snowflake or SQL Server, and expect differences mainly in date functions and a few syntax details.

How is SQL for data analysis different from general SQL?

Analysts mostly read and summarize data with SELECT, joins, aggregates and window functions. Database design, indexing, transactions and writing data are more the territory of engineers and administrators.

Is SQL enough to get an analyst job?

It is one of the most requested analyst skills, but most roles also expect spreadsheets, a visualization tool such as Tableau or Power BI, basic statistics and clear communication of findings.