football-data-warehouse-showcase
A powerful data warehouse project dealing specifically with structured football match records to showcase normalized ETL pipeline processing.
The Challenge
Designing complex relational schemas maintaining massive integrity mapping teams efficiently processing massive raw JSON sources locally continuously.
My Solution
Developed a dedicated Python ETL runner reading JSON structures dynamically exporting them properly into pure MS SQL relations reliably parsing natively.
Tech Stack
- Microsoft SQL Server: Used Microsoft SQL Server for building this project.
- T: Used T for building this project.
- Python 3.x: Used Python 3.x for building this project.
- `pyodbc` for database connectivity: Used `pyodbc` for database connectivity for building this project.
- JSON as the raw data format for the ETL process: Used JSON as the raw data format for the ETL process for building this project.
Technical Deep-Dive
Presents top scorer formulas computing complex joins recursively over large historical records directly embedded into optimal query layers securely.