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| Section | Objectives |
|---|---|
| Reference and Master Data | |
| Data Governance | |
| Document and Content Management | |
| Metadata Management | |
| Data Security | |
| Data Modeling and Design | |
| Data Storage and Operations | |
| Data Warehousing and Business Intelligence | |
| Data Quality Management | |
| Data Integration and Interoperability | |
| Data Architecture |
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NEW QUESTION # 664
There are numerous methods of implementing databases on the cloud. The most common are:
Answer: A,B,D
NEW QUESTION # 665
Validity, as a dimension of data quality, refers to whether data values are consistent with a defined domain of values.
Answer: B
NEW QUESTION # 666
SSD is the abbreviation for Solid State Dimension.
Answer: A
NEW QUESTION # 667
A project scope requires the collection, exchange, and reporting of data from multiple in-house custom systems. Documents gathered include business concepts, existing database schemas, XSDs, and reporting layouts. How many models of each layer of abstraction can be expected?
Answer: E
Explanation:
In data modeling, there are three levels of abstraction: conceptual, logical, and physical. For a project involving multiple systems, the DAMA-DMBOK explains: "Conceptual models are high-level and few in number, focusing on business entities and relationships. Logical models provide more detail, mapping to multiple systems or schemas, and physical models are the most numerous, tailored to specific database implementations" (DMBOK2, Chapter 5: Data Modeling and Design, p. 177). Since each system may have its own physical schema (physical model) and multiple systems may share logical models, while a single or few conceptual models cover the enterprise, the number of models typically follows: physical > logical > conceptual.
Options A and B don't address modeling layers; D assumes only one model per layer, which is unrealistic for multiple systems; and E reverses the hierarchy. Thus, C is correct.
Reference:DAMA-DMBOK2, Chapter 5: Data Modeling and Design, Section 3.2, p. 177.
NEW QUESTION # 668
Which of these is NOT a component of an enterprise wide data strategy?
Answer: E
NEW QUESTION # 669
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