Story
Teradata
HikmaHikma Brings Feature Pipelines onto Teradata
Hikma, a health care organization in the United Kingdom, uses VantageCloud from Teradata 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 | VantageCloud 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
Inside Hikma, applied machine learning used to depend on whoever still had the latest file. That pattern is common in health care groups working out of the United Kingdom. Data scientists and ML engineers needed a system that would still make sense after the original project team moved on.
Hikma uses VantageCloud from Teradata as the working layer for feature pipelines. Teradata provides a connected multi-cloud data platform for large-scale analytics and mixed workload warehousing. The practical change is simple: applied machine learning has a home, and reviews happen there instead of in a forwarded thread.
Nothing in this writeup invents a savings number. What Hikma gets from Teradata is a durable place to run applied machine learning and a way for data scientists and ML engineers to see the same feature pipelines at the same time.
