Story
Dataiku@
Siemens Digital Industries
Siemens Digital Industries Uses MLOps for Feature Pipelines
Siemens Digital Industries, an information technology organization in Germany, uses MLOps from Dataiku to support applied machine learning for data scientists and ML engineers.
Information Technology teams at Siemens Digital Industries treat Dataiku as the working layer for applied machine learning.
“Inside Siemens Digital Industries, applied machine learning used to depend on whoever still had the latest file.”
“Data scientists and ML engineers needed a system that would still make sense after the original project team moved on.”
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 MLOps 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 Siemens Digital Industries, applied machine learning used to depend on whoever still had the latest file. That pattern is common in information technology 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.
Siemens Digital Industries uses MLOps from Dataiku as the working layer for feature pipelines. Dataiku is a universal AI platform that lets data teams and analysts collaborate on pipelines, models, and governed AI applications. 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 Siemens Digital Industries gets from Dataiku 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.
