Table of Contents

SQL Habit has 2 main parts – course aka "business simulator" and practice exercises. Practice exercises are standalone and based on various datasets, where the course is based on a story of a fictional startup company called Bindle.

Bindle is a subscription service for reading books online. The course starts with a launch of Bindle's website and together with the founders will learn how to analyze website performance, marketing performace, dive into analytics of web and mobile apps and much more.

The course covers the first year of Bindle. Each chapters covers one month focused on a specific topic. During each chapter we'll see many real life example in the life of Bindle, learn how data helps to take decisions and solve them. The most important – we'll learn all nuances of how data is recorded and stored in Bindle's data warehouse.

The course requires no prio knowledge of SQL. It'll take you from absolute 0 to Advanced with real life examples, lessons and exercises.


You’ll learn how SQL Habit works and how to get the most out of the course. A quick chapter to set you up for an efficient and effective learning 🚀

Fundamentals of Data Analysis

Together with Bindle’s founders you’ll learn SQL basics and how it helps to segment users (by country, time etc), work with basic timelines 📈

Running marketing

This chapter focuses on SQL for marketing: what data can help us measure an effectiveness of our campaigns, how to group data, work with time lines and cohorts 📊

Revenue analytics and unit economics

In this chapter we’ll dive into all things revenue: calculating gross revenue, revenue per country/time period. We’ll see how we can join marketing and revenue data to calculate ROI and business unit economics (revenue per user etc) 💸

Product Analytics. Part 1

Bindle launches a mobile app to allow users read books on the go. In this chapter we’ll learn funnel analysis for product flows (onboarding, purchase), retention metrics and more 💻

Mobile attribution

You’ll learn about mobile attribution. How it works technically and how mixed attribution model works on web and mobile 📱

Product Analytics. Part 2

Second part of Product Analytics focuses on analytics for mobile apps, retention rate, churn rate and LTV 📈

AB-tests analysis

It’s time for the new chapter at Bindle – running AB-tests. Just shipping features is not enough, AB-tests allow learning how and why changes in the product affect users behavior and happiness. This chapter talks about AB-tests analysis with SQL 💊

Text analysis with SQL

In this chapter we’ll be learning about getting useful insights from text data using Pattern Matching, Regular Expressions; we’ll go over all String functions in SQL 📖

Dashboards and alarms

This chapters talks about using SQL in BI tools, analytics dashboards and typical SQL queries behind them. We’ll also discuss automatic error detection using data and SQL. 🚨

SQL at work

This chapter is a collection of tips and tricks from Marketers, Product Managers and Data Analysts that will give you a head start on using SQL at work 💼

Manipulating data

In this chapter we’ll talk about everything we haven’t been talking yet – modifying data in the database. Inserting new rows, updating and deleting 🛠


This is SQL Habit’s storage room. It covers the aspects of SQL databases we haven’t discussed yet: rare JOIN types, set theory, lists of scalar, aggregate and window functions 🚚