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storySwitzerlandConsumer DiscretionaryProductivityRisk and complianceCapability

Story

Confluent@On Holding

How On Holding Runs Applied Machine Learning on Apache Kafka

On Holding, a consumer discretionary organization in Switzerland, uses Apache Kafka 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 complianceApache Kafka 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

Consumer Discretionary work at On Holding spans more than one site, even when headquarters sits in Switzerland. Feature pipelines was splitting across regional habits. Data scientists and ML engineers asked for a shared way to run applied machine learning without freezing local judgment.

Confluent (Apache Kafka) is what they standardized on. Confluent is the data streaming platform built around Apache Kafka, used to move events between applications in real time. On Holding uses it as the system of record for feature pipelines, with data scientists and ML engineers as the primary operators and other groups coming in through the same queue.

Leaders get a picture they can actually walk. Teams get fewer mystery statuses. The story is about operating change, not an unpublished percentage.

Relationship map

On Holding uses Confluent, Anthropic, Dropbox, Unity, New Relic, Teradata, Intuit, Proofpoint, UiPath, Siemens Digital Industries Software, Google Cloud, Shopify. Shared with 1Password, Abbott Laboratories, AbbVie, Accenture, AES. Industry: Consumer Discretionary. Value: Productivity, Risk and compliance, Capability. Drag nodes, filter types, or expand a node to follow more commonalities.

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