La Liga Analytics
End-to-end data pipeline ingesting multiple sources to produce analytics and visualizations for teams and players.
#Python#Power BI#Azure#Airflow
La Liga Analytics (WIP)
La Liga Analytics is an end-to-end data consolidation pipeline designed to fetch, merge, and analyze football data from multiple disparate sources to provide a unified view of team and player performance.
Data Pipeline Architecture
The system orchestrates a complex workflow to ingest data from public APIs and unstructured CSVs, standardizing it for analytical consumption.
Key Features
- Data Orchestration: Uses Apache Airflow to schedule and manage ETL jobs reliably.
- Cloud Storage: centralized data lake using Azure Data Lake Storage Gen2 (DLS2) for scalable storage of raw and processed data.
- Analytics Engine: Merges and aggregates statistics on players, teams, and matches to derive meaningful insights.
- Interactive Visualization: Delivers comprehensive dashboards via Power BI, allowing for deep-dive trend tracking and performance analysis.
Tech Stack
- Pipeline: Python, Pandas, Apache Airflow
- Cloud Infrastructure: Azure Data Lake Storage Gen2 (ADLS Gen2)
- Visualization: Power BI, Matplotlib