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Teradata@EOG Resources

EOG Resources Adopts Teradata for Applied Machine Learning

EOG Resources, an energy organization in the United States, uses QueryGrid from Teradata to support applied machine learning for data scientists and ML engineers.

Value results

CategoryValue result
CapabilityNamed workflow replaces ad hoc routing for feature pipelines
CapabilityApplied machine learning stays visible to adjacent teams through QueryGrid
CapabilityData scientists and ML engineers work from the same QueryGrid record for feature pipelines

Story

Inside EOG Resources, applied machine learning used to depend on whoever still had the latest file. That pattern is common in energy groups working out of the United States. Data scientists and ML engineers needed a system that would still make sense after the original project team moved on.

EOG Resources uses QueryGrid from Teradata as the working layer for feature pipelines. Teradata provides a connected multi-cloud data platform for large-scale analytics and mixed workload warehousing. The practical change is simple: applied machine learning has a home, and reviews happen there instead of in a forwarded thread.

Nothing in this writeup invents a savings number. What EOG Resources gets from Teradata is a durable place to run applied machine learning and a way for data scientists and ML engineers to see the same feature pipelines at the same time.

Relationship map

EOG Resources uses Teradata, Okta, Qualtrics, Sage, Confluent. Shared with 6sense, ABB, ACS Group, Activision Blizzard, Advantest. Industry: Energy. Value: Capability. Drag nodes, filter types, or expand a node to follow more commonalities.

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