Story
MongoDB
FoxconnMongoDB at Foxconn: Feature Pipelines
Foxconn, an information technology organization in Taiwan, uses Relational Migrator from MongoDB 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 Relational Migrator 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
Foxconn grew feature pipelines faster than the local tools around it. From Taiwan, information technology 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 Relational Migrator put applied machine learning on MongoDB. MongoDB provides a developer data platform, with Atlas as the managed service for document, search, and vector workloads. Foxconn 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.
