Story
Intel Extends Delta Lake Across Applied Machine Learning
Intel, an information technology organization in the United States, uses Delta Lake from Databricks to support applied machine learning for data scientists and ML engineers.
Value results
| Category | Value result |
|---|---|
| Productivity | Fewer stalled items because feature pipelines has a clear owner |
| Risk and compliance | Delta Lake 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
Intel did not need another dashboard that nobody opened. It needed applied machine learning to move. In the United States, data scientists and ML engineers already knew where feature pipelines went wrong: too many copies, too little ownership, and a close process that waited on the loudest inbox.
Delta Lake from Databricks is now in that path. Databricks provides a lakehouse platform for data engineering, analytics, and AI, with Unity Catalog and Mosaic AI for governed models. The company treats it as production tooling for applied machine learning, which is why data scientists and ML engineers live in it rather than exporting from it once a quarter.
Intel can show how feature pipelines is handled today. That is the value: a repeatable way to run applied machine learning on software the rest of the industry already recognizes.