CDMP-Practitioner Exam Information and Outline
Certified Data Management Professional - Practitioner
Syllabus Update Checked on: November 10, 2026
CDMP-Practitioner Exam Syllabus & Study Guide
Before you start practicing with our exam simulator, it is essential to understand the
official CDMP-Practitioner exam objectives. This course outline serves as your roadmap.
The information below reflects the 2026 syllabus defined by
DAMA.
Below are complete topics detail with latest syllabus and course outline, that will help you good knowledge about exam objectives and topics that you have to prepare. These contents are covered in questions and answers pool of exam.
- Exam Format
- Fundamentals exam: 100 multiple-choice questions in 90 minutes, open book (DMBOK2); Practitioner requires score of 70%+ plus two specialist exams
- Data Management Process
- Data management principles and framework (DAMA Wheel)
- Data Governance (11%)
- Governance organization, policies, stewardship and metrics
- Data Modelling and Design (11%)
- Conceptual, logical and physical models; normalization
- Data Quality (11%)
- Data quality dimensions, profiling and improvement cycle
- Metadata Management (11%)
- Business, technical and operational metadata
- Master and Reference Data Management (10%)
- MDM architectures, matching and golden records
- Data Warehousing and Business Intelligence (10%)
- Dimensional modelling, ETL and BI
- Data Architecture (6%)
- Enterprise data models and data flows
- Data Security (6%)
- Classification, access control, privacy regulations
- Data Integration and Interoperability (6%)
- ETL/ELT, replication, APIs and event-driven integration
- Data Storage and Operations (6%)
- Database administration, backup and recovery
- Document and Content Management (6%)
- Records management and retention
- Big Data and Data Science (2%)
- Data lakes, analytics and machine learning
- Data Ethics (2%)
- Ethical handling of data
- Data Management Maturity Assessment (2%)
- Maturity models and assessment
- Data Handling and Organizational Change (2%)
- Change management for data initiatives