Story
Databricks
HalliburtonHalliburton Brings Feature Pipelines onto Databricks
Halliburton, an energy organization in the United States, uses Mosaic AI from Databricks to support applied machine learning for data scientists and ML engineers.
Value results
| Category | Value result |
|---|---|
| Capability | Applied machine learning stays visible to adjacent teams through Mosaic AI |
| Capability | Data scientists and ML engineers work from the same Mosaic AI record for feature pipelines |
| Capability | Feature pipelines can be reviewed without waiting on a personal export |
Story
Energy work at Halliburton spans more than one site, even when headquarters sits in the United States. Feature pipelines was splitting across regional habits. Data scientists and ML engineers asked for a shared way to run applied machine learning without freezing local judgment.
Databricks (Mosaic AI) is what they standardized on. Databricks provides a lakehouse platform for data engineering, analytics, and AI, with Unity Catalog and Mosaic AI for governed models. Halliburton uses it as the system of record for feature pipelines, with data scientists and ML engineers as the primary operators and other groups coming in through the same queue.
Leaders get a picture they can actually walk. Teams get fewer mystery statuses. The story is about operating change, not an unpublished percentage.
