# How Columbia uses Databricks

**70%**: “achieving a 70% reduction in ETL pipeline creation time”

As published on [databricks.com](https://www.databricks.com/customers/columbia). Captured by usedby on 2026-10-02.

- Company: [Columbia](https://www.usedby.ai/companies/columbia.md)
- Tool: [Databricks](https://www.usedby.ai/tools/databricks.md)
- Industry: [Fashion & Apparel](https://www.usedby.ai/companies/industry/fashion-apparel.md)
- Teams: Enterprise Information Management, business analysts, data scientists

## What the story says

Columbia's enterprise information management team moved to Azure Databricks and Delta Lake to build ETL pipelines that support both batch and real-time workloads. The curated data feeds analysts, data scientists and business units across the company for reporting, model training and forecasting.

Summary written by usedby from the source page, in English. The figures are those of Databricks and Columbia, not ours.

> Databricks has helped Columbia’s EIM team accelerate ETL and data preparation, achieving a 70% reduction in ETL pipeline creation time while reducing the amount of time to process ETL workloads from 4 hours to only 5 minutes, 48x improvement.

- **48x**: “reducing the amount of time to process ETL workloads from 4 hours to only 5 minutes, 48x improvement”

> One of the benefits of this platform is how fast people can come up to speed on it. All that data is coming in, and more business units are using it across the enterprise in a self-service manner that was not possible before,
>
> Lara Minor, Senior Enterprise Data Manager, Columbia Sportswear

## What usedby checked

We compared the story with its live page on 2026-10-03.

- Checked: the figure 70% is printed word for word on the page, near the name of Columbia.
- Checked: the passage quoted above is copied word for word from the page, near the name of Columbia.
- Checked: Columbia uses Databricks. Confirmed line. Latest check across sources: 2026-10-02.
- Not checked: the result itself. We quote it; we did not measure it.

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Source: https://www.usedby.ai/case-studies/columbia-sportswear-databricks · How we check: https://www.usedby.ai/methodology