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A professional-level summary covering key definitions, frameworks, and exam-relevant points.
Data Validation Rule Types
| Rule Type | What It Checks | Example |
|---|---|---|
| Format | Data conforms to expected format | Email must match pattern: [email protected] |
| Range | Numeric value within acceptable bounds | Age: 0–150; Discount: 0–100% |
| Referential integrity | Foreign key exists in referenced table | Customer ID in orders must exist in customers |
| Business rule | Data conforms to business logic | End date must be ≥ start date |
| Consistency | Related values are logically consistent | If status = "Closed," then close date must be populated |
| Uniqueness | No duplicate values where required | National ID must be unique per person |
CDMP Exam Relevance
Data validation is tested in the Data Quality knowledge area (11% of the CDMP exam). Key exam topics include: the types of validation rules and what each checks, the difference between validation (preventive) and cleansing (corrective), the role of validation in ETL processes and data entry systems, and the relationship between validation and data quality dimensions (accuracy, completeness, consistency, validity). Data validation is also relevant to Data Architecture questions about system design and data quality controls.
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