This project is aimed at creating a comprehensive football database structure using PostgreSQL and visualizing KPIs using Microsoft PowerBI. The database encompasses various aspects of football data, including player statistics, match details, team information, and much more.
- Database Structure: A relational database structure developed from scratch to store football-related data efficiently.
- Data Collection and Cleaning: Collected data from various sources on the internet and performed data cleaning using the Pandas library to ensure data accuracy and consistency.
- Query Development: Generated multiple pgSQL queries to create tables, populate them with data, and extract meaningful KPIs.
- Visualization: Utilized Microsoft PowerBI to create interactive visualizations of the extracted KPIs, providing intuitive insights into football performance metrics.
- Database Management: PostgreSQL
- Data Cleaning: Pandas module
- Data Visualization: Microsoft PowerBI
You can take a look at the schema here, or if you wish of a more a detailed look, refer to the Documentation.html file.
- Install and setup PostgreSQL on your local machine.
- Execute schema.sql to create the necessary tables.
- Optionally, you can run data.sql to populate the dataset with sample data.
A special thanks to @MichaelaRif for heavily contributing to this project