Story
Databricks
CMA CGMDatabricks at CMA CGM: Feature Pipelines
CMA CGM, an industrials organization in France, uses Databricks SQL from Databricks to support applied machine learning for data scientists and ML engineers.
Value results
| Category | Value result |
|---|---|
| Productivity | Handoffs in applied machine learning sit in a shared queue instead of a mailbox trail |
| Risk and compliance | Databricks SQL is the governed place data scientists and ML engineers use for applied machine learning |
| Capability | New joiners can see how applied machine learning actually runs |
Story
CMA CGM grew feature pipelines faster than the local tools around it. From France, industrials teams still had to serve customers and internal partners who expected a straight answer. Data scientists and ML engineers were the ones stitching the picture together by hand.
Rolling out Databricks SQL put applied machine learning on Databricks. Databricks provides a lakehouse platform for data engineering, analytics, and AI, with Unity Catalog and Mosaic AI for governed models. CMA CGM keeps the product in the path where work already happens, so data scientists and ML engineers do not context-switch into a graveyard system used only for audits.
The visible result is steadier applied machine learning. Feature pipelines is easier to inspect, and adjacent groups can join data scientists and ML engineers without a guided tour of someone's desktop.
