Never seen a data quality issue that wasn't actually an ownership problem

Back to Devoured - July 02, 2026

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Never seen a data quality issue that wasn't actually an ownership problem

Data enterprise Medium

Data quality is almost always an organizational failure of ownership rather than a technical failure of software or infrastructure.

What: When metrics are consumed across multiple teams without explicit governance, trust breaks down; the remedy is establishing clear decision rights and version control for every metric.

Why it matters: Engineers often over-index on testing tools, ignoring the human reality that if no one is responsible for a data definition, it will inevitably become stale and unreliable.

Takeaway: Audit your critical dashboards today: if there is no single person listed as the 'owner' with the authority to change the calculation logic, declare one immediately.

Original article

Data quality failures are usually ownership failures: when multiple teams consume the same metric but no single person controls its definition, calculation, and change process, trust erodes and fixes stay temporary. The practical remedy is explicit metric governance: one named owner, clear decision rights, version/change control, and enforceable quality rules tied to the metric.

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