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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Metadata Management | 8% | - Metadata lifecycle - Types of metadata - Metadata repositories |
| Topic 2: Data Architecture | 12% | - Data modeling and design - Enterprise data architecture - Architecture components and layers |
| Topic 3: Data Governance | 15% | - Compliance and ethics - Governance framework and policies - Data stewardship |
| Topic 4: Data Modeling and Design | 10% | - Modeling standards and methods - Conceptual, logical, physical models |
| Topic 5: Data Integration and Interoperability | 10% | - Data exchange standards - Integration patterns - ETL and ELT processes |
| Topic 6: Reference and Master Data | 5% | - Definitions and purpose - Management processes |
| Topic 7: Data Management Concepts | 10% | - Data management roles and responsibilities - Definitions and principles - DAMA-DMBOK framework |
| Topic 8: Data Quality | 12% | - Quality dimensions - Data cleansing - Assessment and improvement |
| Topic 9: Data Security | 10% | - Access control - Security principles - Privacy and protection |
| Topic 10: Data Storage and Operations | 8% | - Database operations - Data lifecycle management - Storage technologies |
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NEW QUESTION # 536
A Data Management Maturity Assessment (DMMA) can be used to evaluate data management overall, or it can be used to focus on a single Knowledge Area or even a single process.
Answer: A
NEW QUESTION # 537
Data warehousing describes the operational extract, cleaning, transformation, control and load processes that maintain the data in a data warehouse.
Answer: A
NEW QUESTION # 538
The first two steps of the Reference data Change request process, as prescribed DMBOk2, include:
Answer: C,D
NEW QUESTION # 539
The categories of the Data Model Scorecard with the highest weightings include:
Answer: C,D,E
NEW QUESTION # 540
Customer relationship management systems manage Master Data about customers.
Answer: A
NEW QUESTION # 541
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