Case Study: Columbia achieves 48x faster ETL and 70% reduction in pipeline creation time with Databricks

Moving to the cloud ushers in a new era of data-driven retailing

Columbia Sportswear, a data-driven retail enterprise integrating data across wholesale and retail brands, faced slow, costly legacy ETL and analytics systems that couldn’t scale for both batch and real-time use cases. The Information Management team struggled to build pipelines quickly, with ETL jobs taking weeks and infrastructure complexity limiting access for analysts, data scientists and business users.

By moving to Azure Databricks and Delta Lake, Columbia built high-performance, scalable ETL pipelines with ACID guarantees, caching and auto-indexing, and exposed curated data to Power BI, notebooks and their warehouse. The migration cut pipeline creation time by 70% and sped ETL from 4 hours to 5 minutes (48x), enabling broad self-service access and faster data-driven decisions across forecasting, recommendations and customer insights.

Columbia

Lara Minor

Senior Enterprise Data Manager