Story
Dataiku
SynapseSynapse Brings Feature Pipelines onto Dataiku
Synapse, a financials organization in the United States, uses MLOps from Dataiku 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 | MLOps is the governed place data scientists and ML engineers use for applied machine learning |
Story
Financials work at Synapse spans more than one site, even when headquarters sits in the United States. Feature pipelines was splitting across regional habits. Data scientists and ML engineers asked for a shared way to run applied machine learning without freezing local judgment.
Dataiku (MLOps) is what they standardized on. Dataiku is a universal AI platform that lets data teams and analysts collaborate on pipelines, models, and governed AI applications. Synapse uses it as the system of record for feature pipelines, with data scientists and ML engineers as the primary operators and other groups coming in through the same queue.
Leaders get a picture they can actually walk. Teams get fewer mystery statuses. The story is about operating change, not an unpublished percentage.
