Retail Data Mesh for Omnichannel Analytics

Challenge

A major retailer with 500+ stores needed to unify data from online, mobile, and physical stores to enable real-time personalization and inventory optimization. Data was scattered across multiple systems with no unified view.

Solution

We implemented a data mesh architecture that enables real-time analytics across all channels while maintaining domain ownership and data quality.

Key Components

• Federated Query Engine: Trino connecting 15+ data sources
• Real-time Streaming: Kafka-based data ingestion with sub-second latency
• Domain Data Products: Each channel owns their data with standardized contracts
• AI-Driven Insights: Machine learning models for personalization and forecasting

Data Domains

• E-commerce: Online transactions, browsing behavior, cart abandonment
• Mobile App: App usage, push notifications, location data
• Physical Stores: POS transactions, inventory, foot traffic
• Supply Chain: Vendor data, logistics, warehouse operations
• Customer Service: Support tickets, chat logs, satisfaction scores

Results

• Real-time personalization with 25% increase in conversion rates
• Unified customer view across all touchpoints
• Dynamic inventory optimization reducing stockouts by 40%
• Faster insights with 80% reduction in time-to-analytics

Technology Stack

• Query Engine: Trino with real-time streaming capabilities
• Storage: Apache Iceberg with time-travel and schema evolution
• Streaming: Apache Kafka with Trino connectors
• ML Platform: MLflow with federated model training
• Visualization: Custom dashboards with real-time updates

Business Impact

The data mesh enabled:

• Personalized customer experiences across all channels
• Optimized inventory management reducing costs by $2M annually
• Faster product launches with unified analytics
• Data-driven decision making at all levels of the organization