Story
Confluent
TableauTableau Standardizes Feature Pipelines on Confluent
Tableau, an information technology organization in the United States, uses Apache Kafka from Confluent to support applied machine learning for data scientists and ML engineers.
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 | Apache Kafka is the governed place data scientists and ML engineers use for applied machine learning |
Story
Tableau is based in the United States and runs information technology operations at a scale where feature pipelines cannot live in side channels. Data scientists and ML engineers were reconciling competing copies of the same work, which slowed applied machine learning and hid who owned the next step.
The company runs applied machine learning on Confluent, with Apache Kafka as the product data scientists and ML engineers actually open. Confluent is the data streaming platform built around Apache Kafka, used to move events between applications in real time. For Tableau, that means data scientists and ML engineers can open one workflow, see feature pipelines, and let neighboring teams join without inventing a parallel stack.
Public materials confirm the companies and products. They do not always publish a single verified KPI for this pairing, so the outcome here is operational: clearer ownership, fewer stalled handoffs, and a shared record for feature pipelines.
