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.