Retail Etl Medallion Pipeline

This builds a complete three-layer data warehouse for retail operations with all the messy real-world stuff: inventory shrinkage calculations, meat yield conversions for recipes, supplier rebate tiers, and multi-branch consolidation. It's TSQL stored procedures organized into bronze (raw CSV ingestion), silver (business rules and quality scoring), and gold (aggregated metrics like turnover ratios and reorder alerts) layers. You get the full pipeline from Docker Compose setup through each transformation stage, plus Power BI dashboards. Useful if you're building a retail analytics system from scratch and want a working reference implementation instead of just architectural diagrams. The procedures are verbose but show practical patterns for handling perishables, stock discrepancies, and branch-level reporting.

skills.sh installs: 1.3K
GitHub stars: 2
last updated: Jul 14, 2026

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Install

$ npx -y skills add aradotso/data-skills --skill retail-etl-medallion-pipeline --agent claude-code

Installs into .claude/skills of the current project.

Files

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: