Data Quality Audit Report
Dataset: [schema.table_name] |
Assessed by: [Name] |
Date: [YYYY-MM-DD] |
Rows assessed: [N]
Overall Quality Score
Verdict: PASS — approved for production use
Check Results
1. Completeness — Null Audit
| Column | Null % | Threshold | Status | Notes |
|---|
| [column_name] | [0%] | [0%] | PASS | |
| [column_name] | [8%] | [5%] | WARN | [Investigate source] |
| [column_name] | [35%] | [20%] | FAIL | [Pipeline enrichment missing] |
2. Uniqueness — Duplicate Detection
| Check | Count | % | Status | Notes |
|---|
| Full-row duplicates | [0] | [0%] | PASS | |
| Key duplicates (order_id) | [0] | [0%] | PASS | |
3. Consistency — Referential Integrity
| Relationship | Orphan rows | Orphan % | Status |
|---|
| orders.customer_id → customers.id | [0] | [0%] | PASS |
4. Accuracy / Validity — Value Range Validation
| Column | Rule | Violations | Status | Notes |
|---|
| [revenue] | min: 0 | [3] | FAIL | [3 negative values — investigate] |
| [status] | allowed: [active, trial, churned] | [0] | PASS | |
5. Timeliness — Freshness
| Timestamp column | Latest record | Lag | SLA | Status |
|---|
| [updated_at] | [2024-01-15 03:00 UTC] | [1.2h] | [25h] | PASS |
Findings & Recommendations
| # | Severity | Dimension | Finding | Recommendation | Owner |
|---|
| 1 |
CRITICAL |
Accuracy |
[3 negative revenue values — order IDs: X, Y, Z] |
[Investigate pipeline; verify if refunds or data errors] |
[Data Eng] |
| 2 |
MEDIUM |
Completeness |
[geo_region 8% null — above 5% threshold] |
[Acceptable for enrichment field; document expected null rate] |
[Analytics] |
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