The project called for a CLI-driven batch pipeline to process marketing data in CSV format through staged extract, validate, normalize, join, aggregate, analyze, and report steps. The system also computes KPIs, writes intermediate artifacts in Parquet and JSON formats, and supports partial execution with dependency checks. I added run metadata and inspection commands, plus HTML and Excel reporting outputs. The pipeline is fully containerized with Docker and uses mounted volumes for reproducible execution.
Built with
- Python
- pandas
- Docker