Retail Demand Pipeline

Python ETL-style pipeline for validating order data, producing curated demand metrics, and forecasting run-rate trends.

Why This Exists

This repo is shaped like analytics engineering work where noisy source data needs to become trustworthy KPI outputs for operators and planners.

What This Demonstrates

• validation and rejection handling for messy input records
• region/product revenue cuts and strongest-day reporting
• monthly run-rate style forecasting from curated outputs

Architecture

1. raw CSV orders are validated into accepted and rejected sets
2. curation logic computes daily, regional, and product-level metrics
3. summary outputs package operational insights for downstream use

Run It

python -m unittest tests.test_pipeline
python src/pipeline.py --input data/orders.csv --output out/summary.json

Verification

Use the explicit test module and regenerate the summary artifact through the CLI.