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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Governance | 15% | - Governance framework and policies - Data stewardship - Compliance and ethics |
| Topic 2: Data Security | 10% | - Access control - Security principles - Privacy and protection |
| Topic 3: Data Storage and Operations | 8% | - Database operations - Storage technologies - Data lifecycle management |
| Topic 4: Data Architecture | 12% | - Enterprise data architecture - Architecture components and layers - Data modeling and design |
| Topic 5: Reference and Master Data | 5% | - Definitions and purpose - Management processes |
| Topic 6: Data Management Concepts | 10% | - Definitions and principles - DAMA-DMBOK framework - Data management roles and responsibilities |
| Topic 7: Data Modeling and Design | 10% | - Conceptual, logical, physical models - Modeling standards and methods |
| Topic 8: Metadata Management | 8% | - Metadata lifecycle - Types of metadata - Metadata repositories |
| Topic 9: Data Quality | 12% | - Data cleansing - Quality dimensions - Assessment and improvement |
| Topic 10: Data Integration and Interoperability | 10% | - Integration patterns - Data exchange standards - ETL and ELT processes |
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NEW QUESTION # 437
Volume refers to the amount of dat
a. Big Data often has thousands of entities or elements in billions of records.
Answer: A
NEW QUESTION # 438
Effectiveness metrics for a data governance programme includes: achievement of goals and objectives; extend stewards are using the relevant tools; effectiveness of communication; and effectiveness of education.
Answer: A
NEW QUESTION # 439
Well prepared records have characteristics such as:
Answer: B,C,D
NEW QUESTION # 440
Archiving is the process of moving data off immediately accessible storage media and onto media with lower retrieval performance.
Answer: A
NEW QUESTION # 441
The number of entities in a relationship is the arity of the relationship. The most common are:
Answer: B,C,D
NEW QUESTION # 442
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