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.

Introduction to data driven decision making

Exploring the database

Exploring the table renting

Filtering and ordering

Working with dates

Selecting movies

Select from renting

Aggregations - summarizing data

Summarizing customer information

Ratings of movie 25

Examining annual rentals

Introduction to business intelligence for a online movie rental database

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

Grouping movies

First account for each country.

Average movie ratings

Average rating per customer

Joining movie ratings with customer data

Join renting and customers

Aggregating revenue, rentals and active customers

Movies and actors

Money spent per customer with sub-queries

Income from movies

Age of actors from the USA

Identify favorite actors of customer groups

Identify favorite movies for a group of customers

Identify favorite actors for Spain

KPIs per country

Decision Making with simple 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.

Query annidata

Film noleggiati spesso

Clienti frequenti

Film con valutazione sopra la media

Query annidate correlate

Analizzare il comportamento dei clienti

Clienti che hanno dato valutazioni basse

Film e valutazioni con query correlate

Query con EXISTS

Clienti con almeno una valutazione

Attori nelle commedie

Query con UNION e INTERSECT

Giovani attori non provenienti dagli USA

Drammi con valutazioni alte

Data Driven Decision Making with advanced 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.

OLAP: CUBE operator

Groups of customers

Categories of movies

Analyzing average ratings

ROLLUP

Number of customers

Analyzing preferences of genres across countries

GROUPING SETS

Queries with GROUPING SETS

Exploring nationality and gender of actors

Exploring rating by country and gender

Bringing it all together

Customer preference for genres

Customer preference for actors

Data Driven Decision Making with OLAP SQL queries

MovieNow

In questo corso imparerai a usare SQL per supportare il processo decisionale. È basato su un caso di studio di un servizio di noleggio di film online, con un database che contiene informazioni sui clienti, valutazioni dei film, dati sugli attori e altro ancora. Imparerai ad applicare query SQL per analizzare, ad esempio, le preferenze dei clienti, il loro coinvolgimento e l’andamento delle vendite. Il corso tratta anche le estensioni SQL per l’online analytical processing (OLAP), che semplificano l’estrazione di insight chiave da dati aggregati multidimensionali.

Data Manipulation in SQL

Impara ad analizzare una tabella SQL e a riferire le intuizioni alla direzione.

Decision making basato sui dati in SQL

Impara come analizzare una tabella SQL e condividere le tue scoperte con i capi.

Analista dati associato in SQL

SQL per analisti aziendali

Film noleggiati spesso

Decision making basato sui dati in SQL

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