A Governed, AI-Ready Data Supply Chain for Retail
A US-based multi-channel retailer needed a single trusted data foundation across marketplaces, e-commerce, marketing, ERP, support and product systems. We built a governed data supply chain that turned fragmented operational data into analytics-ready and AI-ready intelligence.
The retailer was operating across disconnected platforms including Amazon Vendor Central, Wayfair, Shopify, marketing tools, reviews, support, advertising and Sage 300 ERP. Reporting was manual, inconsistent and lacked a trusted view of sales, pricing, stock and customer activity.
We consolidated ten source domains into a unified SQL Server platform. Each source lands in its own schema, while curated Gold-layer tables provide reliable, business-ready data for reporting, analytics and downstream AI workloads.
Medallion architecture: Bronze, Silver and Gold layers create traceable, standardised and business-ready data outputs.
Airflow orchestration: Domain-based DAGs manage scheduling, retries, monitoring and pipeline ownership.
Incremental extraction: Watermark-based loads pull only new or changed records, reducing cost and source-system load.
End-to-end lineage: ETL timestamps at every tier make records traceable for audit, validation and incident response.
Portable deployment: Docker-based environments support consistent production deployment and safe local development.
The retailer moved from fragmented, channel-by-channel reporting to a single governed and auditable data supply chain across marketplaces, e-commerce, marketing, ERP and support. Reporting became consistent, while the curated Gold layer created a clean foundation for analytics, predictive modelling and agentic AI use cases.
Sandeep Bhalekar · Databricks Partner · bhalekar.ai
Enterprise AI strategy, build, governance and architecture for regulated and high-volume environments.
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