营销与写作

retail-etl-medallion-pipeline

reason-machines/data-skills

End-to-end retail ETL pipeline using Medallion Architecture (Bronze/Silver/Gold) with TSQL, PySpark, and Airflow for inventory, sales, and supplier data processing

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安装命令

npx skills add https://github.com/reason-machines/data-skills --skill retail-etl-medallion-pipeline

SKILL.md

Retail ETL Medallion Pipeline Skill

Skill by ara.so — Data Skills collection.

Overview

This project implements a production-grade Medallion Architecture ETL pipeline for retail/hypermarket data, handling complex business logic like inventory shrinkage, meat/poultry recipe conversions, supplier rebate tiers, and multi-branch sales consolidation. The architecture follows three data quality layers:

  • Bronze Layer: Raw data ingestion from CSV sources (sales, stock, products)
  • Silver Layer: Cleaned, standardized, and business-rule-applied data
  • Gold Layer: Aggregated, analytics-ready dimensional models

The pipeline processes:

  • Multi-branch sales transactions (Alex, Cairo, Giza)
  • Product catalogs with recipe/yield conversions
  • Stock/inventory tracking across locations
  • Supplier rebate calculations

Project Structure

Retail ETL Medallion Pipeline Skill

Skill by ara.so — Data Skills collection.

Overview

This project implements a production-grade Medallion Architecture ETL pipeline for retail/hypermarket data, handling complex business logic like inventory shrinkage, meat/poultry recipe conversions, supplier rebate tiers, and multi-branch sales consolidation. The architecture follows three data quality layers:

  • Bronze Layer: Raw data ingestion from CSV sources (sales, stock, products)
  • Silver Layer: Cleaned, standardized, and business-rule-applied data
  • Gold Layer: Aggregated, analytics-ready dimensional models

The pipeline processes:

  • Multi-branch sales transactions (Alex, Cairo, Giza)
  • Product catalogs with recipe/yield conversions
  • Stock/inventory tracking across locations
  • Supplier rebate calculations

Project Structure