Story
Databricks
CenteneCentene Brings Feature Pipelines onto Databricks
Centene, a health care organization in the United States, uses Mosaic AI from Databricks to support applied machine learning for data scientists and ML engineers.
Databricks is how Centene keeps feature pipelines visible to people who have to act on it.
“Health Care work at Centene spans more than one site, even when headquarters sits in the United States.”
“Data scientists and ML engineers asked for a shared way to run applied machine learning without freezing local judgment.”
Independent write-up. Figures come from public sources or are illustrative.
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
Health Care work at Centene 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. Centene 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 The story is about operating change, not an unpublished percentage.
