Story
Confluent
Fortune BrandsFortune Brands Brings Feature Pipelines onto Confluent
Fortune Brands, an industrials organization in the United States, uses Flink on Confluent from Confluent to support applied machine learning for data scientists and ML engineers.
Value results
| Category | Value result |
|---|---|
| Capability | Feature pipelines can be reviewed without waiting on a personal export |
| Capability | Named workflow replaces ad hoc routing for feature pipelines |
| Capability | Applied machine learning stays visible to adjacent teams through Flink on Confluent |
Story
Inside Fortune Brands, applied machine learning used to depend on whoever still had the latest file. That pattern is common in industrials 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.
Fortune Brands uses Flink on Confluent from Confluent as the working layer for feature pipelines. Confluent is the data streaming platform built around Apache Kafka, used to move events between applications in real time. 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 Fortune Brands gets from Confluent 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.
