F-Zarian / Investigate-a-DVD-Rental-Database-Using-SQL

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Investigate Sakila DVD Rental Database Using SQL

Project Overview

This project explores data from the Sakila DVD Rental Database. The Sakila Database holds information about a company that rents movie DVDs. For this project, I will be querying the database to gain an understanding of the customer base, such as what the patterns in movie watching are across different customer groups, how they compare on payment earnings, and how the stores compare in their performance and sales.

Data Set

This PostgreSQL sample database was introduced by Udacity as part of the Programming for Data Science with Python Nanodegree Program in March 2021. The dataset can be found here.

The DVD rental database represents the business processes of a DVD rental store. The DVD rental database has many objects including: • 15 tables • 1 trigger • 7 views • 8 functions • 1 domain • 13 sequences

Steps

• I set up a PostgreSQL database on my local machine

• Downloaded the Movie database from this page.

• Loaded the DVD Rental database into my PostgreSQL server on my machine using the PgAdmin tool. You will find the instructions to do so on the this link.

• Connected back to the PostgreSQL server

• Connected to the DVD rental database

• Selected the DVD Rental database

• Started running queries on the DVD rental database

• After running several queries to get familiar with the data within the database, I answered 6 questions to get a deeper insight into the company that rents the DVDs.

Questions Proposed for Deeper Understanding of the Rental Business

• What are the Top 20 films and categories families are watching based on rental count? (categories of considered family movies: Animation, Children, Classics, Comedy, Family and Music)

• How Do Rental Duration and Rental Count Change within Family-Friendly Movie Categories?

• How Does Rental Duration of Family-Friendly Films Compare within Combination of Each Category?

• How the Two Stores Compare in Their Count of Rental Orders During Every Month for all The Years We Have Data For?

• Who Were the Top 10 Paying Customers, How Many Payments They Made on a Monthly Basis During 2007?

• What is the Difference in Monthly Payments During 2007, for each of these Top 10 Paying Customers?

Key Insights for Presentation

Technologies Used

• PostgreSQL

• pgAdmin 4

Resources

License

The contents of this repository are covered under the MIT License.

Note: This is a fake database