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| Section | Weight | Objectives |
|---|---|---|
| Data Quality | 12% | - Quality dimensions - Data cleansing - Assessment and improvement |
| Reference and Master Data | 5% | - Definitions and purpose - Management processes |
| Data Architecture | 12% | - Data modeling and design - Architecture components and layers - Enterprise data architecture |
| Data Security | 10% | - Security principles - Access control - Privacy and protection |
| Data Integration and Interoperability | 10% | - Data exchange standards - Integration patterns - ETL and ELT processes |
| Data Modeling and Design | 10% | - Modeling standards and methods - Conceptual, logical, physical models |
| Data Governance | 15% | - Governance framework and policies - Data stewardship - Compliance and ethics |
| Data Storage and Operations | 8% | - Database operations - Data lifecycle management - Storage technologies |
| Metadata Management | 8% | - Types of metadata - Metadata repositories - Metadata lifecycle |
| Data Management Concepts | 10% | - Definitions and principles - DAMA-DMBOK framework - Data management roles and responsibilities |
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NEW QUESTION # 711
Controlling data availability requires management of user entitlements and of structures that technically control access based on entitlements.
Answer: B
NEW QUESTION # 712
The most important reason to implement operational data quality measurements is to inform data consumers about levels of data effectiveness.
Answer: A
NEW QUESTION # 713
The accepted tenets of bioethics provide a starting point for the principles of data ethics. Which of the following tenets of bioethics is NOT included in the DMBOK2 Chapter on Data Handling Ethics?
Answer: B
Explanation:
The DMBOK2 includes all listed bioethics tenets in its data handling ethics framework. The DAMA- DMBOK states: "Data handling ethics draws from bioethics principles, including Non-Maleficence, Justice, Respect for Persons, and Beneficence, to guide ethical data practices" (DMBOK2, Chapter 14: Data Handling Ethics, p. 559). Since all are included, "None of these" (B) is correct.
Reference:DAMA-DMBOK2, Chapter 14: Data Handling Ethics, Section 2.2, p. 559.
NEW QUESTION # 714
Business activity information is one of the types of data that can be modelled.
Answer: A
NEW QUESTION # 715
Which of the following is one of the Data Architecture artifacts usually captured within development projects, and then standardized and managed by data architects?
Answer: A
Explanation:
The correct answer is C. DAMA states that data models and other Data Architecture artifacts are commonly captured within development projects and are then standardized and managed by data architects. This reflects the incremental nature of enterprise architecture: individual projects create useful data structures and specifications, while the architecture function evaluates which artifacts should become reusable enterprise assets. Data models are therefore the best answer because conceptual, logical, and physical models created during projects can be aligned with enterprise standards and incorporated into broader architectural repositories. An enterprise data model and a Data Architecture roadmap are important enterprise-level artifacts, but the question asks specifically for artifacts usually captured within development projects and subsequently standardized. "Company-wide architectural blueprints" is too general, while business models belong primarily to the business architecture domain.
NEW QUESTION # 716
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