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Databricks@Hellmann Worldwide Logistics

Hellmann Worldwide Logistics Adopts Databricks for Applied Machine Learning

Hellmann Worldwide Logistics, an industrials organization in Germany, uses Delta Lake from Databricks to support applied machine learning for data scientists and ML engineers.

Value results

CategoryValue result
CapabilityData scientists and ML engineers work from the same Delta Lake record for feature pipelines
CapabilityFeature pipelines can be reviewed without waiting on a personal export
CapabilityNamed workflow replaces ad hoc routing for feature pipelines

Story

Hellmann Worldwide Logistics did not need another dashboard that nobody opened. It needed applied machine learning to move. In Germany, 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.

Delta Lake from Databricks is now in that path. Databricks provides a lakehouse platform for data engineering, analytics, and AI, with Unity Catalog and Mosaic AI for governed models. 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.

Hellmann Worldwide Logistics 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.

Relationship map

Hellmann Worldwide Logistics uses Databricks, IBM, Anthropic, Zoom, Adobe, New Relic, OpenAI, Palantir. Shared with AstraZeneca, Biogen, Grammarly, Hotels.com, Konica Minolta. Industry: Industrials. Value: Capability. Drag nodes, filter types, or expand a node to follow more commonalities.

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