The SQL Thinking Book: One Dataset. Five Levels. 550 Questions with Complete Solutions

By Madhu Vadlamani

You finished the course. You know SELECT, JOIN, and GROUP BY. Then a real question arrives and you freeze.

That pause isn't a syntax problem. It's a thinking problem - and almost no SQL book addresses it.

Most SQL books teach commands: a keyword, a tidy example, a new dataset every chapter. You learn the vocabulary and still can't answer "which customers are we most at risk of losing?" because nobody taught you how to look at a database and see a system.

This book takes the opposite approach. Every one of its 550 questions runs against one single dataset - a fictional bank with six connected tables. By question 400 you know that schema the way you know a building you work in, and that familiarity is exactly what makes real problems feel obvious instead of frightening.

Five levels, each a different kind of thinking:

Level 1 - Basics and Filters. One table at a time. What separates the rows you want from every other row.
Level 2 - Joins and Relationships. Inner, outer, anti-joins, self-joins. How to spot a join that runs perfectly and returns the wrong answer.
Level 3 - Analytics and Aggregations. Window functions, running totals, ranking, trends, distribution.
Level 4 - Workflows and System Thinking. INSERT, UPDATE, DELETE, CTEs, views, transactions, data-quality investigation.
Level 5 - All-In-One Thinking. Business questions with no single right answer, phrased the way real requests actually arrive.
Plus The Jumble 50 - mixed questions with no level labels, because nobody tells you the difficulty before they send the request.

What makes this different:

- Complete solutions for all 550 questions. Every answer was executed against the dataset and verified to run.
- The full schema and sample data are printed inside - and available as downloadable .sql files. You can be practising in five minutes.
- The dataset is deliberately imperfect. Missing values, empty categories, and seven planted data-quality defects, because clean data doesn't exist outside textbooks.
- A full chapter on using AI to write SQL responsibly - what it's genuinely good at, the three errors it makes constantly, and why reviewing SQL demands more understanding than writing it.
- Runs on MySQL, PostgreSQL, SQL Server, and SQLite, with an appendix covering every difference between them.

Who this is for: analysts and engineers who can write queries but want to stop guessing; anyone preparing for data interviews; professionals in finance, HR, sales, or operations who are tired of waiting in a queue for someone else to answer their questions; and trainers who want a ready-made practice environment.

Written by Madhu Vadlamani, an AI practice lead with 17 years in data and AI and over 100 speaking engagements, who has watched the same gap open in classrooms and corporate teams alike: people learn tools but struggle to apply them.

Stop memorising commands. Start thinking in data.

• Format: Paperback
• Language: English
• ISBN: B0HGGN7VZ4
• ISBN13: 9798192438251
• Release Date: August 2026
• Publisher: Independently published
• Length: 241 Pages
• Weight: 0.72 lbs.
• Dimensions: 9.0" x 0.6" x 6.0"