Data-Driven Decision Making in SQL

You should be comfortable with basic SELECT queries. The course reviews core commands but moves quickly to GROUP BY, JOINs, and OLAP extensions, so prior exposure to SQL is assumed.

Data analysts, BI professionals, and SQL users who want to go beyond basic queries and apply SQL to real business decisions like identifying top-performing movies, tracking customer engagement, and analyzing sales trends.

You will be able to write queries that answer questions like which genres are most profitable, what each customer's favorite actor is, and how rental revenue develops over time — using the same SQL patterns applied in BI and analytics roles.

OLAP stands for Online Analytical Processing. It lets you aggregate data across multiple dimensions in a single query. The course covers the CUBE, ROLLUP, and GROUPING SETS extensions, which are standard tools for summarizing large datasets without running separate queries for each breakdown.

All exercises use a fictional online movie rental company with five related tables covering customers, rentals, movies, actors, and cast data. This consistent dataset lets you build progressively more complex queries without switching contexts between chapters.

The course has four chapters. Chapter 1 introduces the case study and basic filtering. Chapter 2 covers GROUP BY, JOINs, and subqueries. Chapter 3 moves to nested and correlated queries with EXISTS and UNION. Chapter 4 focuses on OLAP extensions and ends with a complex query combining multiple techniques.