Germany’s leading retailer modernized its data and AI on Dremio, processing petabytes daily, migrating 100,000+ ML models to the cloud, and reducing ingestion costs.
The Agentic Lakehouse for Retail
Unify fragmented retail data, accelerate AI-driven personalization, and activate first-party data without ETL, data duplication, or vendor lock-in.
Trusted by leading retail and consumer companies
BENEFITS
Built for modern retail data teams
Dremio gives retail data teams the fastest path to trusted AI and analytics, unifying POS, loyalty, e-commerce, and supply chain data without duplication, ETL, or lock-in. Merchandising analysts, data scientists, and AI agents get governed access to a single source of truth, without waiting on data engineering.
Fastest Path to Retail AI and Analytics
Unifies customer and business data into a single governed layer, enabling accurate AI-driven insights like personalization, forecasting, and inventory optimization.
Dive into the AI Semantic Layer →
All Your Retail Data, Where It Lives
Query all retail data in place without ETL, reducing costs and enabling unified access across systems through a single SQL interface.
Learn about Dremio's Intelligent query engine →
Governance and Privacy You Can Trust
Provides centralized governance with fine-grained controls and automated compliance, ensuring secure and privacy-ready data access across all workloads.
Review our certifications →
USE CASES
Retail Use Cases
Find the use case for your team below. Dremio connects data teams, merchandising leaders, and AI agents to the same governed, always-current retail data foundation.
Merchandising and loyalty teams build precise segments on unified POS, e-commerce, loyalty, and CRM data, without waiting 24–72 hours for pipelines to run. Dremio federates all customer touchpoints into a single query layer so teams and AI agents share the same governed record. Segment build time: 48 hours → under 2 hours.
Supply chain and store operations teams get a real-time inventory view across stores, distribution centers, and e-commerce fulfillment, without centralizing WMS, OMS, and POS data into a warehouse copy. Dremio queries in place so BOPIS commitments, out-of-stock decisions, and replenishment triggers are based on current stock, not yesterday’s batch.
ML engineers and planning teams build demand forecasting models on unified historical sales, promotional calendars, supplier lead times, and external signals through a single SQL layer without ETL. The AI Semantic Layer makes product hierarchies, seasonality definitions, and channel taxonomies immediately available to forecasting models and agentic workflows.
E-commerce teams get sub-second access to behavioral, transactional, and product catalog data to power real-time recommendations and dynamic pricing, directly from the lakehouse without a separate feature store. Autonomous Reflections accelerate high-frequency queries automatically, based on actual usage patterns.
Marketing analytics teams get a unified first-party data layer across paid and owned channels for multi-touch attribution and media mix modeling. Polaris Catalog enforces PII consent controls at query time so new first-party sources go from onboarding to campaign-ready in days, not weeks.
CUSTOMER STORIES
Trusted by retail and consumer
data teams worldwide
Amazon’s SCOT Finance Analytics team used Dremio to speed up decisions on billions of records, eliminating 60 hours of work per project.
North America’s largest roofing distributor uses Dremio to deliver self-service analytics to 1,200+ users, eliminating Tableau slowdowns.
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FAQs
Frequently Asked Questions
Get common questions answered about Solutions for Retail.
Yes. Dremio federates POS, OMS, WMS, and e-commerce data through a single SQL query layer without extracting or centralizing it. Merchandising and supply chain teams query live operational data alongside historical Iceberg tables in one interface, with no pipeline to maintain.
Polaris Catalog enforces consent-based access policies and CCPA opt-out requests at the Iceberg table level, propagating deletions across all downstream query paths without pipeline changes. This means new opt-outs and CPRA deletion rights are satisfied at the data platform level, without touching individual dashboards or downstream applications.
Yes. Zero-ETL Federation connects directly to existing warehouses, data lakes, and legacy systems without moving data. Most financial institutions reach production within weeks. TD Securities unified data discovery across 75+ systems without replacing existing infrastructure.
Yes. Dremio connects to CDPs alongside POS, loyalty, and e-commerce data through a single federated query layer, so marketing analytics teams can build audience segments and attribution models on unified first-party data without extracting customer profiles from the CDP into a separate warehouse copy.
Dremio replaces warehouse-copy jobs by querying data directly from your cloud data lake, with Autonomous Reflections providing automatic, usage-based acceleration that matches warehouse query performance without data loading costs. Retail teams typically reduce compute spend 30-60% while maintaining or improving analyst query experience across high-transaction workloads.
Yes. Dremio queries current inventory data from WMS, OMS, and POS systems in place without waiting for batch processing cycles. Store operations and supply chain teams get live BOPIS availability, replenishment triggers, and out-of-stock signals based on current stock, not yesterday’s warehouse snapshot.
Yes. Dremio connects to all major BI tools via ODBC/JDBC and Arrow Flight SQL. Analysts continue using their existing reporting tools while Dremio governs data access, accelerates queries, and ensures every dashboard draws from the same governed semantic layer across all retail data sources.
