Sakila DVD Rental Data Analysis

Overview

This project involves using PostgreSQL to explore the Sakila DVD Rental database, which contains data related to a company that rents movie DVDs. The objective is to gain insights into customer behavior, movie rentals, payment earnings, and store performance. SQL queries are used to extract relevant data, and visualizations are created to showcase the findings.

Dataset

The Sakila DVD Rental database can be downloaded from the following link: Sakila DVD Rental Database

Project Structure

The project consists of SQL queries and data visualizations. Here's a brief overview of the key components:

1. SQL Queries: SQL queries are written to extract and analyze data from the database. Four main queries are used to answer specific questions and generate insights.

   • Query 1: Examines movie rental patterns across different film categories.
   • Query 2: Divides family movies into quartiles based on rental duration.
   • Query 3: Analyzes the count of movies within each category for different rental duration categories.
   • Query 4: Provides information on store performance in terms of fulfilling rental orders.

2. Data Visualizations: Visualizations are created to present the results of the SQL queries. The visualizations can include bar charts, line graphs, or any other relevant types to effectively communicate the findings (in report.pdffile).

How to Run the Queries

To run the SQL queries in this project, follow these steps:

1. Database Setup: Ensure you have PostgreSQL installed on your computer.
2. Download Dataset: Download the Sakila DVD Rental database from the provided link.
3. Connect to Database: Use a SQL client (e.g., pgAdmin, DBeaver, or psql command-line) to connect to the Sakila database.
4. Execute Queries: Open and execute the SQL queries provided in the project.

Results and Visualizations

The project's SQL queries provide insights into customer behavior, movie rentals, and store performance. Visualizations are generated to present the findings effectively.

Project Files

• queries.txt: Contains the SQL queries used in the project.
• report.pdf: File containing visualizations generated from the query results and insights.

Dependencies

• PostgreSQL: The project requires a PostgreSQL database to run the SQL queries.

Credits

• This project was completed as part of the Programming for Data Science Nanodegree offered by Udacity. Its already the first project of Introduction to Python Programming course on the whole program.

Udacity Nanodegree Program:

• Programming for Data Science Nanodegree