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| Section | Objectives |
|---|---|
| Data Quality Assessment | - Data Profiling Techniques - Data Quality Metrics and KPIs |
| Data Quality Fundamentals | - Definition of Data Quality - Data Quality Dimensions (Accuracy, Completeness, Consistency, Timeliness, Validity, Uniqueness) |
| Data Quality Improvement | - Data Cleansing Methods - Root Cause Analysis |
| Data Quality Operations | - Monitoring and Reporting - Data Quality Tools and Technologies |
| Data Quality Management | - Roles and Responsibilities (Data Stewardship) - Data Quality Governance |
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NEW QUESTION # 24
A business case for adding a new master data management solution is dependent on achieving greater value from:
Answer: E
NEW QUESTION # 25
Who does the DMBoK consider to be generally responsible for developing business glossary content?
Answer: E
Explanation:
DAMA-DMBOK2 assigns primary responsibility for business glossary content to Business Data Stewards.
Business Data Stewards are typically subject-matter experts who understand how data is defined, created, interpreted, and consumed within their business domain. DMBOK2 explicitly states that Data Stewards are generally responsible for business glossary content and identifies Business Data Stewards as professionals who work with stakeholders to define and control data.
A business glossary is not simply a technical dictionary. It establishes agreed business terminology, definitions, synonyms, business rules, responsible stewards, and relationships between business concepts.
This makes stewardship involvement essential because definitions must reflect operational and business meaning rather than merely database structures.
Data Architects may contribute candidate definitions and structural context from subject-area and conceptual models, but they do not generally own the business meaning. Business users provide valuable input, while Coordinating Data Stewards help reconcile definitions across domains, yet the normal accountability remains with Business Data Stewards.
This relationship is particularly important for Data Quality. Quality rules depend on unambiguous definitions of data elements. If "Customer," "Active Account," or "Order Date" has inconsistent meanings, measurements of completeness, accuracy, and validity cannot be consistently interpreted.
Reference Topics: DAMA-DMBOK2 Chapter 3 - Develop a Business Glossary; Business Data Stewardship; Metadata Management; Chapter 13 - Data Quality Rules and Business Definitions.
NEW QUESTION # 26
The role of Metadata in Data Management is:
Answer: D
Explanation:
The broad role of Metadata is to help organizations understand their data, systems, and workflows. Metadata provides the context required to interpret data correctly and connect business meaning with technical implementation and operational processing. This answer is also explicitly identified in DAMA-oriented certification material.
Business metadata explains concepts, definitions, rules, ownership, stewardship, and terminology. Technical metadata describes tables, columns, datatypes, interfaces, transformations, and system structures. Operational metadata captures information about processing, execution, schedules, and usage. Together, these categories explain what information means, where it resides, how it moves, and how it is used.
Metadata can certainly improve decision-making, support Big Data solutions, group concepts, and assist reporting, but those are secondary outcomes. Option C expresses its enterprise-wide role most comprehensively.
Its connection to Data Quality is fundamental. Quality cannot be assessed consistently without metadata explaining the intended meaning and acceptable characteristics of a data element. Lineage allows a defect to be traced to its origin, while business definitions establish the context for accuracy and validity measurements.
Reference Topics: DAMA-DMBOK2 Metadata Management - Business, Technical and Operational Metadata; Data Lineage; Business Glossary; Chapter 13 - Data Quality Rules and Metadata Dependencies.
NEW QUESTION # 27
Two departments use the term "Active Customer" but apply different definitions. Which Data Management capability should be addressed first?
Answer: D
Explanation:
The immediate requirement is Business Glossary governance. The issue is semantic: two departments use the same term but assign different meanings to it.
A governed business glossary establishes agreed terminology, definitions, synonyms, related concepts, ownership, and usage context. Resolving the definition does not necessarily mean forcing every business process to use one operational rule; there may be legitimate variants. The critical requirement is that those variants be explicitly named and documented so consumers understand the distinction.
Metadata Management provides the structures needed to preserve and distribute these definitions. DAMA's public Metadata Management guidance identifies business glossaries and data dictionaries as core mechanisms for improving shared understanding.
This semantic clarity is fundamental to Data Quality. A completeness or accuracy score for "Active Customer" is meaningless if departments measure different populations under the same label.
After the definition is governed, technical metadata should link the glossary concept to physical fields, calculations, reports, and quality rules.
Reference Topics: DAMA-DMBOK2 - Business Glossary; Metadata Management; Data Stewardship; Semantic Consistency; Data Quality Rules.
NEW QUESTION # 28
Integrating data security with document and content management knowledge areas, guides the implementation of:
Answer: C
Explanation:
Document and Content Management focuses on information stored outside conventional relational databases, including documents, images, multimedia, email, and other semi-structured or unstructured assets. Integrating this knowledge area with Data Security therefore guides the implementation of appropriate access and authorization controls for unstructured data.
DAMA's framework treats security as a cross-cutting discipline rather than something applicable only to database tables. Organizational documents can contain personally identifiable information, intellectual property, contracts, financial records, or other confidential material and therefore require the same disciplined approach to authentication, authorization, classification, retention, and monitoring as structured data. DAMA- aligned references explicitly identify appropriate access and authorization to unstructured data as the relevant interaction between these knowledge areas.
Metadata is also important because document classifications, ownership, retention category, confidentiality level, and permitted audiences provide the information needed to enforce controls.
Option A refers to structured data and therefore misses the specific contribution of Document and Content Management. Fitness-for-purpose measurement belongs primarily to Data Quality, while data-mart privacy addresses a narrower structured analytical environment.
Reference Topics: DAMA-DMBOK2 Chapter 7 - Data Security; Chapter 9 - Document and Content Management; Unstructured Data; Access Control; Authorization; Information Classification.
NEW QUESTION # 29
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