CDMP Data Quality Study Guide
How organisations define, measure and improve data that is fit for purpose. This page gives you a concise orientation before you move into deeper revision and practice.
What to focus on
- Data quality dimensions
- Rules, metrics and thresholds
- Issue management and root cause analysis
- Monitoring and continuous improvement
How to study this area
Start by learning the purpose of the discipline and the business problem it solves. Then separate concepts that are easy to confuse, especially roles, artefacts, lifecycle stages and governance responsibilities. Finally, test the distinction in scenario-based questions rather than relying on definition recall alone.
When two options both sound reasonable, look for the answer that best matches the role, level of abstraction, sequence or accountability described in the question.
Use questions to expose gaps
Reading creates familiarity; questions test whether you can retrieve and apply the concept. Data Shawarma's interactive practice area filters questions by chapter so you can immediately check this topic.
Practise Data Quality
Open the companion, choose Practice and filter to the relevant chapter.
Open practice questions