Story
DatabricksHow DCOH Runs Applied Machine Learning on Unity Catalog
DCOH, an information technology organization in the United States, uses Unity Catalog from Databricks to support applied machine learning for data scientists and ML engineers.
Value results
| Category | Value result |
|---|---|
| Capability | Data scientists and ML engineers work from the same Unity Catalog record for feature pipelines |
| Capability | Feature pipelines can be reviewed without waiting on a personal export |
| Capability | Named workflow replaces ad hoc routing for feature pipelines |
Story
Information Technology work at DCOH 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 (Unity Catalog) 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. DCOH 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 The story is about operating change, not an unpublished percentage.
