Case Study: Leading Home Improvement Retailer achieves faster, governed analytics and AI readiness with AtScale

How a Leading Home Improvement Retailer Scaled Self-Service Analytics and Enabled Enterprise AI with AtScale’s Semantic Layer

A leading home improvement retailer modernizing its analytics stack faced challenges with legacy OLAP technology, inconsistent metrics across teams, slow development cycles, and growing demand for governed self-service access in Excel and support for AI and natural language querying. After migrating to Google BigQuery, the company still needed a better way to make enterprise data usable, consistent, and scalable for business users.

The retailer implemented AtScale’s semantic layer on BigQuery to centralize metric definitions, enable cloud-scale OLAP without data movement, and provide governed access through tools like Excel and API-based natural language query. With AtScale, the company achieved faster time to insight, stronger governance, and broader adoption, including 80% of queries completing in under 1 second, a 20+ TB semantic cube, and hundreds of daily Excel users accessing trusted enterprise metrics.