retail-etl-medallion-pipeline

Automate retail data processing by deploying an ETL pipeline that applies Medallion Architecture layers to structure inventory, sales, and supplier data. The pipeline uses TSQL, PySpark, and Airflow to manage data quality and automate workflows end-to-end.

Structuring retail ETL pipelines with Bronze, Silver, and Gold data quality layers ensures analytics readiness. This Medallion Architecture approach separates raw data ingestion from transformed analytics views, streamlining inventory management and sales reporting.

Yes, running these retail ETL automated workflows requires a SQL Server environment and a Python environment with specified libraries. The pipeline relies on TSQL for data transformations and PySpark for distributed processing.

Medallion Architecture improves retail data quality by progressively refining data through Bronze, Silver, and Gold layers. This structured refinement process ensures accurate and timely insights for supplier rebates and sales reporting.

Yes, you can use Airflow and PySpark for retail inventory management ETL. Airflow orchestrates the automated ETL workflows while PySpark handles large-scale data processing within the Medallion Architecture pipeline.