In short
Data quality is commonly measured on dimensions such as accuracy, completeness, consistency, timeliness, validity and uniqueness.
Key takeaways
- Validity means values follow the defined rules, such as a date in the right format.
- Uniqueness means no duplicate records.
- Poor data quality undermines both reporting and analytics.
Where it's tested
ISC: Data Management & Governance — study notes, a five-minute revision sheet and practice questions.
Practise: 3 questions
Question 1 of 3 · 0 answered
Which dimension of data quality is violated when the same customer appears three times in a master file under slightly different names?