Unified data platform combining lakehouse architecture with retail capabilities for inventory, personalization, supply chain, and omnichannel analytics
Integrates point-of-sale transactions, e-commerce clickstreams, inventory systems, supply chain data, customer loyalty programs, and third-party market data into unified lakehouse for 360-degree retail analytics
Enables use cases including personalized recommendations, dynamic pricing optimization, fraud detection, demand forecasting, store layout optimization, and omnichannel customer journey analysis across physical and digital touchpoints
Supports compliance with retail regulations (PCI DSS, GDPR, CCPA) through built-in data governance, access controls, and audit trails while scaling to handle seasonal demand spikes and flash sales
What is Lakehouse for Retail?
Lakehouse for Retail is Databricks’ first industry-specific Lakehouse. It helps retailers get up and running quickly through solution accelerators, data sharing capabilities, and a partner ecosystem.
Lakehouse for Retail is the culmination of technologies, partners, tools, and industry initiatives to drive stronger collaboration around data + AI. It is made up of four fundamental building blocks:
Unified Data + AI Platform: Delivers critical capabilities required to run modern retail on a single platform:
Make data-informed decisions in real-time
Deliver more accurate analysis with powerful AI
Leverage a variety of data types on one unified platform
Partner Solutions: Customers can confidently adopt Lakehouse for Retail by adopting partner-built use case solutions created on Lakehouse for Retail.
Driving Industry Data Sharing & Collaboration: Drive secure and open data sharing as well as collaboration to unlock innovation with partners.
Tools to Accelerate: Databricks and its partners have invested in a variety of retail solution accelerators to help customers quickly adopt and drive results with Lakehouse.
Why are retailers turning to Lakehouse for Retail?
Over the last two years, retailers have struggled with the massive shift to e-commerce and with shifting consumers' preferences and needs. To address these challenges, retailers have built the following solutions into their strategy:
Operate in real-time: Companies must be able to rapidly ingest data at scale and make insights available across the value chain in real-time.
Eliminate technical roadblocks: Allows organizations to perform fine-grained analysis for all products within their tight service level agreements.
Use multimodal data quickly and efficiently for analysis: Only 5-10% of a company’s data is structured. Tapping into the other 90% of data helps businesses better understand the environment around them and make better decisions.
Gain an inexpensive and open method of collaboration: For data and analysis, collaboration is critical to ensure open interaction and innovation for all partners in the value chain. Enhanced collaboration also improves the speed of operations, builds richer analytics, and reduces the cost of alignment across the value chain.
Real-time access to data. Moving from batch-oriented access, analysis, and compute will allow data to be “always-on”, which drives real-time decisions and business intelligence. Real-time use cases, such as demand forecasting, personalization, on-shelf availability, arrival time prediction, and order picking & consolidation, provide value to the organization through improved supply chain agility, reduced cost to serve, optimized product availability, and stocking replenishment.
Long-term benefits:
Retail has always been about collaboration - but most of that collaboration didn’t involve data sharing or data collaboration. Lakehouse for Retail is changing this. Data sharing between retailers, suppliers, agencies, and distributors, in an open and secure environment, opens up additional fine-grained use cases, therefore promoting additional consumption.
