Story
Snowflake
KubotaKubota Brings Feature Pipelines onto Snowflake
Kubota, an industrials organization in Japan, uses Cortex AI from Snowflake 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 | Cortex AI is the governed place data scientists and ML engineers use for applied machine learning |
Story
Industrials work at Kubota spans more than one site, even when headquarters sits in Japan. 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.
Snowflake (Cortex AI) is what they standardized on. Snowflake is a cloud data platform that separates storage and compute so organizations can share, analyze, and govern data across clouds. Kubota 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 The story is about operating change, not an unpublished percentage.
