# Data Validation Data Quality Checks

> Sub-skill of data-validation: Data Quality Checks (+3).

- Skill: `vamseeachanta/data-validation-data-quality-checks` (Agent Skill)
- Install (CLI): `npx skillmds@latest add vamseeachanta/data-validation-data-quality-checks`
- Raw SKILL.md: https://api.skillmd.com/api/skills/vamseeachanta/data-validation-data-quality-checks/raw
- Safety review: PASS (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Data & Analytics
- Author: vamseeachanta (https://skillmd.com/u/vamseeachanta)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/vamseeachanta/data-validation-data-quality-checks

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# Data Quality Checks (+3)

## Data Quality Checks


- [ ] **Source verification**: Confirmed which tables/data sources were used. Are they the right ones for this question?
- [ ] **Freshness**: Data is current enough for the analysis. Noted the "as of" date.
- [ ] **Completeness**: No unexpected gaps in time series or missing segments.
- [ ] **Null handling**: Checked null rates in key columns. Nulls are handled appropriately (excluded, imputed, or flagged).
- [ ] **Deduplication**: Confirmed no double-counting from bad joins or duplicate source records.
- [ ] **Filter verification**: All WHERE clauses and filters are correct. No unintended exclusions.


## Calculation Checks


- [ ] **Aggregation logic**: GROUP BY includes all non-aggregated columns. Aggregation level matches the analysis grain.
- [ ] **Denominator correctness**: Rate and percentage calculations use the right denominator. Denominators are non-zero.
- [ ] **Date alignment**: Comparisons use the same time period length. Partial periods are excluded or noted.
- [ ] **Join correctness**: JOIN types are appropriate (INNER vs LEFT). Many-to-many joins haven't inflated counts.
- [ ] **Metric definitions**: Metrics match how stakeholders define them. Any deviations are noted.
- [ ] **Subtotals sum**: Parts add up to the whole where expected. If they don't, explain why (e.g., overlap).


## Reasonableness Checks


- [ ] **Magnitude**: Numbers are in a plausible range. Revenue isn't negative. Percentages are between 0-100%.
- [ ] **Trend continuity**: No unexplained jumps or drops in time series.
- [ ] **Cross-reference**: Key numbers match other known sources (dashboards, previous reports, finance data).
- [ ] **Order of magnitude**: Total revenue is in the right ballpark. User counts match known figures.
- [ ] **Edge cases**: What happens at the boundaries? Empty segments, zero-activity periods, new entities.


## Presentation Checks


- [ ] **Chart accuracy**: Bar charts start at zero. Axes are labeled. Scales are consistent across panels.
- [ ] **Number formatting**: Appropriate precision. Consistent currency/percentage formatting. Thousands separators where needed.
- [ ] **Title clarity**: Titles state the insight, not just the metric. Date ranges are specified.
- [ ] **Caveat transparency**: Known limitations and assumptions are stated explicitly.
- [ ] **Reproducibility**: Someone else could recreate this analysis from the documentation provided.