Supply Chain Data Platform — Azure Data Engineering
Challenge
A leading multinational consumer goods (CPG) company struggled with fragmented data across multiple ERP systems, warehouses, and logistics partners, leading to poor visibility into supply chain operations. This resulted in frequent stockouts, delayed shipments, and inefficient inventory management, costing the business millions in lost revenue and excess holding costs annually. The primary objectives were to create a unified view of end-to-end supply chain KPIs, enable real-time decision-making, and reduce operational inefficiencies by 30% within the first year.
Manual reporting processes took days to compile, hindering proactive responses to demand fluctuations and supply disruptions. Legacy systems lacked scalability for growing data volumes from IoT sensors and e-commerce channels, exacerbating silos between sales, procurement, and logistics teams.
Solution
We designed a modern data engineering platform using Microsoft Azure as the core tech stack, featuring Azure Data Lake for centralized storage, Azure Data Factory for automated ETL pipelines, and Azure Synapse Analytics for scalable warehousing to ingest and process data from 20+ disparate sources including ERPs, IoT devices, and third‑party logistics APIs. Key features included real-time data pipelines for supply chain KPIs (e.g., case fill rate, on-time delivery), data quality frameworks with automated validation, and a unified BI dashboard powered by Power BI for role-based access across teams.
Tech Stack
- Storage & Processing: Azure Data Lake, Azure Synapse Analytics
- ETL & Orchestration: Azure Data Factory, dbt
- Streaming: Azure Event Hubs
- Visualization: Power BI
- Infrastructure: Azure Kubernetes Service (AKS) for scalability
Implementation
Our cross-functional team of 8—including 3 data engineers, 2 architects, PM, and domain experts—collaborated via Agile sprints with bi-weekly demos. Technical highlights included migrating 5TB of historical data to Azure Synapse with zero downtime, implementing Azure Data Factory pipelines for 50+ daily workflows, and integrating Azure Event Hubs for real-time IoT streaming. Challenges like data schema mismatches were resolved through automated reconciliation rules, ensuring 99.5% pipeline uptime.
Results & Impact
- Case Fill Rate Improvement: 25% increase — reduced stockouts and improved customer satisfaction across 10+ warehouses.
- On-Time Delivery: 22% uplift — enabled proactive routing optimizations via real-time visibility.
- Inventory Optimization: 15% reduction in excess stock — alongside 80% faster reporting.
- Insight Velocity: 10x faster KPI access — dashboards refreshed in minutes instead of days, empowering weekly reviews.
Technologies We Use
Azure Synapse Analytics
Azure Data Factory
Power BI Dashboards
Azure Data Bricks
