Choose Your Reading Style
A professional-level summary covering key definitions, frameworks, and exam-relevant points.
Complete CDMP Knowledge Area Guide
| Knowledge Area | Weight | Key Concepts Tested |
|---|---|---|
| Data Governance | 11% | Framework, roles, policies, stewardship, operating models |
| Data Modeling & Design | 11% | Conceptual/logical/physical models, normalisation, star/snowflake |
| Metadata Management | 11% | Business/technical/operational metadata, data catalogs, repositories |
| Data Quality | 11% | Six dimensions, profiling, root cause, stewardship, improvement cycle |
| Reference & Master Data | 10% | MDM styles, golden records, reference data, survivorship rules |
| Data Warehousing & BI | 10% | Kimball vs Inmon, star/snowflake, OLAP, SCD types, ETL |
| Data Architecture | 6% | Enterprise architecture, data models, roadmaps, standards |
| Data Storage & Operations | 6% | Database types, DBMS, backup, recovery, performance |
| Data Security | 6% | Classification, access control, privacy, encryption, compliance |
| Data Integration & Interoperability | 6% | ETL/ELT, data virtualisation, SOA, APIs, data hubs |
| Document & Content Management | 6% | Unstructured data, ECM, records management, content lifecycle |
Study Time Allocation
For a 3-month study plan targeting Master level (80%+), the recommended time allocation is: Data Governance (15%), Data Modeling (15%), Metadata Management (15%), Data Quality (15%), Reference & Master Data (10%), Data Warehousing & BI (10%), and the remaining six areas (20% total, approximately 3.3% each). Adjust based on your diagnostic exam results — spend more time on areas where you scored below 70%.
CDMP Exam Relevance
This knowledge area breakdown is the foundation of any effective CDMP study plan. Candidates who study all 11 areas proportional to their exam weight consistently outperform those who focus only on their areas of interest or professional experience. The CDMP rewards breadth of knowledge across the entire DMBOK.