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Data quality is an operating responsibility

Make quality failures visible to the people who can act on them.

Data platforms & engineering illustrative scene

A pipeline can complete while its output is incomplete or unsuitable. Define quality expectations with the consumer: freshness, coverage, meaning and permitted use.

Make checks actionable. Identify who investigates a failure, whether downstream processing pauses and how corrected data is replayed.

Keep quality evidence close to the data product. A maintained contract is more useful than a one-time clean-up with no owner.

A clearer next step

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