data-quality-assessment

Five Quality Dimensions

Score each dimension 1-5 when evaluating any data source or pipeline:

1. Completeness - What percentage of expected records and fields are present?

• Null rate per column
• Missing record detection (expected vs actual row counts)
• Required field coverage
• Score 5: <1% nulls in required fields. Score 1: >20% missing data.

2. Accuracy - Does the data reflect reality?

• Cross-field validation (age matches birth date, totals match line items)
• Reference data matching (codes exist in terminology tables)
• Statistical outlier detection
• Score 5: <0.1% error rate verified against gold standard. Score 1: Known systematic errors unresolved.

3. Timeliness - Is the data fresh enough for its intended use?

• Data freshness (time since last update vs SLA)
• Pipeline latency (ingestion to availability)