Story
Snowflake
UnileverHow Unilever Runs Applied Machine Learning on Snowpark
Unilever, a consumer staples organization in the United Kingdom, uses Snowpark from Snowflake to support applied machine learning for data scientists and ML engineers.
Value results
| Category | Value result |
|---|---|
| Capability | Data scientists and ML engineers work from the same Snowpark 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
Consumer Staples work at Unilever spans more than one site, even when headquarters sits in the United Kingdom. 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 (Snowpark) 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. Unilever 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 The story is about operating change, not an unpublished percentage.
