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  3. Data-Driven Decision Making in SQL
  • 1

    Introduction to business intelligence for a online movie rental database

    Free

    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.

  • 2

    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.

  • 3

    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.

  • 4

    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.

Initializing

Exercise

Ratings of movie 25

The movie ratings give us insight into the preferences of our customers. Report summary statistics, such as the minimum, maximum, average, and count, of ratings for the movie with ID 25.

Instructions

100 XP
  • Select all movie rentals of the movie with movie_id 25 from the table renting.
  • For those records, calculate the minimum, maximum and average rating and count the number of ratings for this movie.