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storyUnited StatesEnergyProductivityRisk and complianceCapability

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Confluent@EOG Resources

EOG Resources Uses Flink on Confluent for Feature Pipelines

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

Value results

CategoryValue result
ProductivityHandoffs in applied machine learning sit in a shared queue instead of a mailbox trail
Risk and complianceFlink on Confluent is the governed place data scientists and ML engineers use for applied machine learning
CapabilityNew joiners can see how applied machine learning actually runs

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 Flink on Confluent from Confluent as the working layer for feature pipelines. Confluent is the data streaming platform built around Apache Kafka, used to move events between applications in real time. 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 Confluent 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 Confluent, Teradata, Okta, Qualtrics, Sage. Shared with 1Password, Abbott Laboratories, AbbVie, Accenture, AES. Industry: Energy. Value: Productivity, Risk and compliance, Capability. Drag nodes, filter types, or expand a node to follow more commonalities.

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