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| Section | Objectives |
|---|---|
| Data Quality Assessment | - Data Quality Metrics and KPIs - Data Profiling Techniques |
| Data Quality Management | - Data Quality Governance - Roles and Responsibilities (Data Stewardship) |
| Data Quality Operations | - Data Quality Tools and Technologies - Monitoring and Reporting |
| 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 |
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NEW QUESTION # 61
Database monitoring tools measure key database metrics, such as:
Answer: D
Explanation:
DAMA-DMBOK2 identifies capacity, availability, cache performance, and user statistics as representative metrics captured by database-monitoring tools. Database monitoring is an operational control mechanism used by Database Administrators and platform teams to understand whether database infrastructure is available, adequately sized, responsive, and being used as expected. DMBOK2 explicitly describes monitoring tools as automating the observation of metrics such as capacity, availability, cache performance, and user statistics.
Capacity metrics indicate resource consumption and future growth requirements. Availability measures whether data services remain accessible when required. Cache-performance measures help identify inefficient access patterns and bottlenecks, while user statistics provide information about workload and database consumption.
The other choices mix design concepts, CRUD operations, or Data Quality concepts with operational monitoring measures. For example, normalization is a modelling technique rather than a routine runtime performance metric. Similarly, "create, read, update, delete" describes basic data operations rather than monitoring indicators.
Although database performance and Data Quality are distinct disciplines, poor operational performance can affect Data Quality dimensions such as timeliness and availability. Monitoring therefore supports the technical environment in which governed, reliable information is delivered to users and applications.
Reference Topics: DAMA-DMBOK2 - Data Storage and Operations; Database Operations; Capacity and Availability Management; Monitoring; Chapter 13 - Timeliness and Operational Fitness for Purpose.
NEW QUESTION # 62
An MDM hub receives three customer records that have been confirmed to represent the same person. Before creating the mastered representation, what process determines which source values should populate each attribute?
Answer: A
Explanation:
The process is Survivorship. After records have been matched and determined to represent the same entity, survivorship rules determine which attribute values should populate the mastered or preferred representation.
For example, the organization may select the most recently verified telephone number, prioritize a government-verified legal name, or prefer addresses originating from a designated Customer Relationship Management system. Different attributes can use different survivorship rules.
Survivorship is not simply "choose the newest value." The appropriate method may consider source trust, verification status, recency, completeness, confidence scores, stewardship decisions, or combinations of these factors.
The rules must be governed because they determine what the organization subsequently treats as trusted master data. Metadata should record the rule, selected source, lineage, and effective date so the mastered record remains explainable.
DAMA identifies Reference and Master Data Management as responsible for maintaining consistency in core entities such as customers, products, and locations and for supporting trusted shared information.
The Data Quality dimensions involved commonly include Accuracy, Consistency, Currency, Completeness, and Uniqueness.
Reference Topics: DAMA-DMBOK2 Chapter 10 - Master Data Management; Matching; Survivorship; Golden Record; Chapter 13 - Consistency and Accuracy.
NEW QUESTION # 63
A company requires every system to use the same ISO country-code list managed centrally. This is primarily an example of:
Answer: C
Explanation:
This is Reference Data Management. Country codes represent a controlled set of values used to classify or contextualize other data. Managing them centrally helps ensure that all systems interpret the same codes consistently.
Without centralized governance, one system might use GB, another UK, and another proprietary numeric values. Those differences create mapping complexity, failed integrations, inaccurate aggregation, and inconsistent reporting.
Reference Data Management establishes authoritative sources, stewardship, allowed values, mappings, effective dates, distribution processes, and change control. DAMA's public framework describes Reference and Master Data Management as ensuring consistency in core shared information across organizational units.
The Data Quality dimensions most directly supported are Validity and Consistency. Validity ensures values belong to an approved domain; consistency ensures equivalent concepts are represented compatibly across systems.
Metadata should document the standard, meaning, owner, and version of each reference domain.
Reference Topics: DAMA-DMBOK2 Chapter 10 - Reference Data; Controlled Code Sets; Authoritative Sources; Chapter 13 - Validity and Consistency.
NEW QUESTION # 64
Who does the DMBoK consider to be generally responsible for developing business glossary content?
Answer: A
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 # 65
The DMBoK 'Environmental Factors hexagon' shows the relationship between:
Answer: C
Explanation:
The DAMA-DMBOK2 Environmental Factors Hexagon illustrates the relationship between People, Process, and Technology. It provides a visual key for interpreting the Knowledge Area Context Diagrams and emphasizes that effective Data Management depends on the coordinated interaction of these three dimensions.
DMBOK2 places Goals and Principles at the center of the hexagon because they guide how people perform activities and how technology is selected and used. People-related factors include roles, responsibilities, organization, and culture. Process-related factors include activities, techniques, and methods. Technology- related factors include tools and the mechanisms that support Data Management deliverables.
This model is especially relevant to Data Quality. A profiling or cleansing platform alone cannot establish sustainable quality. The organization also needs accountable Data Owners and Data Stewards, repeatable issue-management and improvement processes, business-defined rules, and governance mechanisms.
Conversely, well-designed processes will fail if supporting technologies cannot monitor or enforce required controls.
Option A relates more closely to the structure of DMBOK Knowledge Area Context Diagrams. The DAMA Wheel represents the Knowledge Areas, while the Environmental Factors Hexagon specifically emphasizes the People-Process-Technology relationship.
Reference Topics: DAMA-DMBOK2 Chapter 1 - DAMA-DMBOK Framework; Environmental Factors Hexagon; People, Process and Technology; Chapter 13 - Data Quality Organization, Processes and Tools.
NEW QUESTION # 66
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