Story
Snowflake
Duke EnergyDuke Energy Extends Unistore Across Applied Machine Learning
Duke Energy, a utilities organization in the United States, uses Unistore from Snowflake to support applied machine learning for data scientists and ML engineers.
Unistore became the place Duke Energy uses to train and ship models on the same lakehouse the business already trusts.
“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 |
|---|---|
| Capability | Feature pipelines can be reviewed without waiting on a personal export |
| Capability | Named workflow replaces ad hoc routing for feature pipelines |
| Capability | Applied machine learning stays visible to adjacent teams through Unistore |
Story
Duke Energy 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.
Unistore 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.
Duke Energy 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.
