Story
Snowflake
HersheyHershey Runs Applied Machine Learning with Snowflake
Hershey, a consumer staples organization in the United States, uses Horizon Catalog from Snowflake to support applied machine learning for data scientists and ML engineers.
Consumer Staples teams at Hershey treat Snowflake as the working layer for applied machine learning.
“In the United States, data scientists and ML engineers already knew where feature pipelines went wrong: too many copies, too little ownership, and a close process that waited on the loudest inbox.”
“Snowflake is a cloud data platform that separates storage and compute so organizations can share, analyze, and govern data across clouds.”
Independent write-up. Figures come from public sources or are illustrative.
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 | Horizon Catalog is the governed place data scientists and ML engineers use for applied machine learning |
Story
Hershey did not need another dashboard that nobody opened. It needed applied machine learning to move. In the United States, data scientists and ML engineers already knew where feature pipelines went wrong: too many copies, too little ownership, and a close process that waited on the loudest inbox.
Horizon Catalog from Snowflake is now in that path. Snowflake is a cloud data platform that separates storage and compute so organizations can share, analyze, and govern data across clouds. The company treats it as production tooling for applied machine learning, which is why data scientists and ML engineers live in it rather than exporting from it once a quarter.
Hershey can show how feature pipelines is handled today. That is the value: a repeatable way to run applied machine learning on software the rest of the industry already recognizes.
