Unified Inventory & Customer Data Foundation
Case Study
How a European Fashion Retailer Built a Real-Time Data Platform for Inventory, Analytics and AI
A fast-growing European fashion retailer operating hundreds of stores alongside a large e-commerce business had accumulated data across ERP, POS, WMS, e-commerce, marketplaces and marketing platforms. Critical business decisions were still based on batch data, while different teams maintained their own definitions of revenue, sales, availability and margin.
Dateonic designed a Databricks-based data foundation that unified transactional and analytical data, introduced governed data products and created a common layer for BI, forecasting and AI.
Turnover
12 months
Industry
E-commerce | Retail
Techonology:
Databricks, Delta Lake, MLflow, Unity Catalog
Building a Single Source of Truth
The new platform ingested data from POS, e-commerce, ERP, warehouse and logistics systems into a governed Databricks environment. Batch and streaming workloads were handled through a common architecture, allowing the retailer to move away from separate pipelines for different analytical use cases.
Making Inventory Data Real-Time
Sales and inventory events were processed continuously, creating a much more accurate view of product availability across stores and digital channels. This enabled downstream inventory analytics, replenishment and availability use cases without waiting for overnight processing.
Preparing the Platform for AI
The foundation was designed around reusable data products rather than individual dashboards. Governed customer, product, order and inventory datasets could be consumed by BI, data science and ML workloads without rebuilding the underlying pipelines.
Business Impact
- Near real-time inventory visibility
- Unified POS and e-commerce data
- Reduced dependency on overnight batch processing
- Consistent business definitions across teams
- Foundation for demand forecasting and AI
- Governed access through Unity Catalog