Story
Informatica
EONEON Extends Data Quality Across Applied Machine Learning
EON, a utilities organization in Germany, uses Data Quality from Informatica to support applied machine learning for data scientists and ML engineers.
EON folded Data Quality into applied machine learning so data scientists and ML engineers share one view of feature pipelines.
“Data scientists and ML engineers needed a system that would still make sense after the original project team moved on.”
“Informatica is an enterprise data management platform for integration, quality, catalog, and master data across clouds.”
Independent write-up. Figures come from public sources or are illustrative.
Value results
| Category | Value result |
|---|---|
| Productivity | Fewer stalled items because feature pipelines has a clear owner |
| Productivity | Handoffs in applied machine learning sit in a shared queue instead of a mailbox trail |
| Risk and compliance | Data Quality is the governed place data scientists and ML engineers use for applied machine learning |
Story
Inside EON, applied machine learning used to depend on whoever still had the latest file. That pattern is common in utilities groups working out of Germany. Data scientists and ML engineers needed a system that would still make sense after the original project team moved on.
EON uses Data Quality from Informatica as the working layer for feature pipelines. Informatica is an enterprise data management platform for integration, quality, catalog, and master data across clouds. 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 EON gets from Informatica 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.
