Audit

Data quality & governance audit checklist

Interactive audit to assess dataset completeness, lineage, metadata, access controls, governance policies, stewardship, and corrective actions. Scored sections, evidence fields, owner assignments, priority flags, and saved responses for tracking and follow-up.

Interactive Tool

Data quality & governance audit checklist

Use this structured audit to evaluate the data assets that support your analyses and experiments. Score each area, record evidence, nominate an owner for corrective actions, and capture recommended fixes and due dates. Saved submissions help prioritize remediation and improve reproducibility.

Enter date of audit (YYYY-MM-DD).
Person completing this audit.
Unique name, file path, table name, or system ID for the dataset under review.
0 = missing/unknown, 5 = complete and validated.
1.0 10.0
Describe missing fields, sampling gaps, or records with nulls and link to sample files or queries.
Person responsible for remediation.
Concrete next steps, timeline, and dependencies.
Assess whether data source, transformations, and pipeline are documented and traceable.
1.0 10.0
Links to lineage diagrams, pipeline code, or transformation logs.
Evaluate presence and quality of field descriptions, units, formats, and data dictionaries.
1.0 10.0
Assess whether access is appropriate, logged, and follows least privilege.
1.0 10.0
Consider data retention, classification, regulatory controls, and approved usage.
1.0 10.0
Is there a designated steward, and are roles & SLAs defined?
1.0 10.0
Are automated checks, thresholds, or alerts in place to detect issues?
1.0 10.0
0 = negligible, 5 = critical risk that could invalidate results.
1.0 10.0
Select priority for remediation.
Summarize top issues, owners, and suggested timeline for remediation.
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