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1.2.0

Data quality validation patterns for daily checks and anomaly follow-up.

76 downloads
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Data Quality Operations

Use when dataset freshness/completeness checks must be run consistently.

Inputs to Gather

  • Primary target (service, team, or dataset)
  • Current impact and urgency
  • Assigned owner and deadline

Core Commands

  • dq profile --dataset <name>
  • dq validate --rule-set <id>
  • dq anomaly --open --metric <name>
  • workflow checklist --from templates/checklist.md
  • workflow report --from templates/report.md

Operating Notes

  • Prefer explicit owner assignment before action.
  • Keep timeline notes concise and timestamped.
  • Save output artifacts for audit and handoff.
  • This version adds a structured report template for post-task summaries.

Version marker: data-quality-operations 1.2.0

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ZIP package — ready to use

Skill Info

Creator
JiaranI
Downloads
76
Published
Mar 15, 2026
Updated
Mar 16, 2026