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Snowflake@Beckhoff

Snowflake Supports Applied Machine Learning at Beckhoff

Beckhoff, an industrials organization in Germany, uses Snowflake Data Cloud from Snowflake to support applied machine learning for data scientists and ML engineers.

Value results

CategoryValue result
InsightApplied machine learning stays visible to adjacent teams through Snowflake Data Cloud
CapabilityFeature pipelines can be reviewed without waiting on a personal export
CapabilityNamed workflow replaces ad hoc routing for feature pipelines

Story

Beckhoff is based in Germany and runs industrials operations at a scale where feature pipelines cannot live in side channels. Data scientists and ML engineers were reconciling competing copies of the same work, which slowed applied machine learning and hid who owned the next step.

The company runs applied machine learning on Snowflake, with Snowflake Data Cloud as the product data scientists and ML engineers actually open. Snowflake is a cloud data platform that separates storage and compute so organizations can share, analyze, and govern data across clouds. For Beckhoff, that means data scientists and ML engineers can open one workflow, see feature pipelines, and let neighboring teams join without inventing a parallel stack.

Public materials confirm the companies and products. They do not always publish a single verified KPI for this pairing, so the outcome here is operational: clearer ownership, fewer stalled handoffs, and a shared record for feature pipelines.

Relationship map

Beckhoff uses Snowflake, Adobe, Grafana Labs, Atlassian, GitLab, Check Point, Netskope. Shared with Aviva, FIS, HelloFresh, Jeld-Wen, Matillion. Industry: Industrials. Value: Insight, Capability. Drag nodes, filter types, or expand a node to follow more commonalities.

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