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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Modeling and Design | 10% | - Modeling standards and methods - Conceptual, logical, physical models |
| Topic 2: Data Governance | 15% | - Compliance and ethics - Data stewardship - Governance framework and policies |
| Topic 3: Data Storage and Operations | 8% | - Data lifecycle management - Database operations - Storage technologies |
| Topic 4: Metadata Management | 8% | - Types of metadata - Metadata repositories - Metadata lifecycle |
| Topic 5: Data Management Concepts | 10% | - Data management roles and responsibilities - DAMA-DMBOK framework - Definitions and principles |
| Topic 6: Data Integration and Interoperability | 10% | - Data exchange standards - Integration patterns - ETL and ELT processes |
| Topic 7: Data Architecture | 12% | - Architecture components and layers - Data modeling and design - Enterprise data architecture |
| Topic 8: Data Security | 10% | - Privacy and protection - Access control - Security principles |
| Topic 9: Data Quality | 12% | - Assessment and improvement - Quality dimensions - Data cleansing |
| Topic 10: Reference and Master Data | 5% | - Definitions and purpose - Management processes |
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NEW QUESTION # 67
A data warehouse deployment with multiple ETL, storage and querying tools often suffers due to the lack of:
Answer: A
NEW QUESTION # 68
Reference and Master data definition: Managing shared data to meet organizational goals, reduce risks associated with data redundancy, ensure higher quality, and reduce the costs of data integration.
Answer: B
NEW QUESTION # 69
The four main types of NoSQL databases are:
Answer: A,C,D,F
NEW QUESTION # 70
Wat data architecture designs represent should be clearly documented. Examples include:
Answer: B,C,D,F
NEW QUESTION # 71
Those responsible for the data-sharing environment have an obligation to downstream data consumers to provide high quality data.
Answer: B
NEW QUESTION # 72
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