Overview

Stop memorizing SQL syntax and start thinking like someone who can actually solve data problems at work. This book teaches you the exact habits that separate ""I can write a SELECT"" from ""I can trust my results, explain them, and ship them without breaking anything."" If you've ever run a query that looked right but returned the wrong totals, duplicated rows after a join, or produced numbers you didn't fully trust, you're the target reader. You'll learn the set-based mental model that prevents the most common mistakes, how to sanity-check outputs before you believe them, and how to build queries in clear layers that you can debug and maintain. It begins with how to think in SQL (sets, not loops) and why SQL is strong for filtering, joining, aggregating, and enforcing clean data, but not meant to be used like a general-purpose programming language. What makes this book different is how practical it is. You work inside a small, realistic starter database (customers, orders, products, order_items, payments) so every concept is tied to real query patterns, not toy examples. You also get a step-by-step workflow for staying safe and accurate: start at the correct grain, add one join at a time, measure row counts, stop when duplication appears, and validate with slices. By the end, you won't just ""know SQL."" You'll be able to produce clean deliverables like a queryable sales model, monthly metrics that reconcile back to source tables, cohort retention and churn signals, inventory and time-series helpers, and data-quality monitors, with clear validation steps baked in. And when you want reps, the practice packs include step-by-step solutions across core filtering, joins and fan-out debugging, aggregation and reconciliation, window functions, and safe schema/DML habits so you don't learn bad patterns that blow up production data later. If you want SQL that's accurate, reviewable, and safe, this is your playbook.

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