Story
Teradata
ImpervaImperva Uses VantageCloud for Feature Pipelines
Imperva, an information technology organization in the United States, uses VantageCloud from Teradata 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 VantageCloud 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
Inside Imperva, applied machine learning used to depend on whoever still had the latest file. That pattern is common in information technology groups working out of the United States. Data scientists and ML engineers needed a system that would still make sense after the original project team moved on.
Imperva 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 Imperva 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.
