Data-Driven Decision Making in SQL

Overview

Learn how to analyze a SQL table and report insights to management.

In this course, you will learn how to use SQL to support decision making. It is based on a case study about an online movie rental company with a database about customer information, movie ratings, background information on actors and more. You will learn to apply SQL queries to study for example customer preferences, customer engagement, and sales development. This course also covers SQL extensions for online analytical processing (OLAP), which makes it easier to obtain key insights from multidimensional aggregated data.

Syllabus

Introduction to business intelligence for a online movie rental database

The first chapter is an introduction to the use case of an online movie rental company, called MovieNow and focuses on using simple SQL queries to extract and aggregated data from its database.

Decision Making with simple SQL queries

More complex queries with GROUP BY, LEFT JOIN and sub-queries are used to gain insight into customer preferences.

Data Driven Decision Making with advanced SQL queries

The concept of nested queries and correlated nested queries is introduced and the functions EXISTS and UNION are used to categorize customers, movies, actors, and more.

Data Driven Decision Making with OLAP SQL queries

The OLAP extensions in SQL are introduced and applied to aggregated data on multiple levels. These extensions are the CUBE, ROLLUP and GROUPING SETS operators.

Taught by

Bart Baesens, Tim Verdonck and Irene Ortner

Reviews

4.4 rating at DataCamp based on 52 ratings

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