Story
Teradata at X: Feature Pipelines
X, a communication services organization in the United States, uses Teradata AI Unlimited from Teradata to support applied machine learning for data scientists and ML engineers.
A Teradata AI Unlimited rollout at X took applied machine learning out of inboxes and into a named queue.
“From the United States, communication services teams still had to serve customers and internal partners who expected a straight answer.”
“Teradata provides a connected multi-cloud data platform for large-scale analytics and mixed workload warehousing.”
Independent write-up. Figures come from public sources or are illustrative.
Value results
| Category | Value result |
|---|---|
| Capability | Data scientists and ML engineers work from the same Teradata AI Unlimited 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
X grew feature pipelines faster than the local tools around it. From the United States, communication services teams still had to serve customers and internal partners who expected a straight answer. Data scientists and ML engineers were the ones stitching the picture together by hand.
Rolling out Teradata AI Unlimited put applied machine learning on Teradata. Teradata provides a connected multi-cloud data platform for large-scale analytics and mixed workload warehousing. X keeps the product in the path where work already happens, so data scientists and ML engineers do not context-switch into a graveyard system used only for audits.
The visible result is steadier applied machine learning. Feature pipelines is easier to inspect, and adjacent groups can join data scientists and ML engineers without a guided tour of someone's desktop.