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69. Frage
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?
Antwort: B
Begründung:
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.
70. Frage
An Orders table contains an order whose Customer_ID does not exist in the Customer table. Which Data Quality dimension is most directly violated?
Antwort: A
Begründung:
The primary issue is Data Integrity, specifically referential integrity. The Orders record references a Customer_ID that does not correspond to an existing Customer record, meaning the relationship defined by the data model has been violated.
Integrity concerns whether structural relationships and constraints among data elements remain valid. In relational environments, this commonly includes primary-key uniqueness, foreign-key relationships, mandatory relationships, and cardinality constraints.
A customer identifier could be syntactically valid and populated, yet still fail integrity because no corresponding parent entity exists. This illustrates why integrity is different from completeness or validity.
The DMBOK2 dimension model explicitly associates integrity with unique identifiers, cardinality, and referential integrity concepts.
Remediation should determine why the orphan record occurred. Potential causes include incorrect load sequencing, deletion of the parent record, integration failure, transformation defects, or absence of database constraints.
Metadata and Data Modeling establish the expected relationship; Data Quality controls then measure whether operational data conforms to it.
Reference Topics: DAMA-DMBOK2 Chapter 13 - Data Integrity; Referential Integrity; Chapter 5 - Relationships and Keys; Data Integration Controls.
71. Frage
HTTPS:// indicates that the website is:
Antwort: B
Begründung:
An address beginning with HTTPS indicates that the website uses an encrypted security layer for communications between the client and server. DAMA-DMBOK2 explicitly identifies HTTPS as a security technology and states that the https:// prefix indicates that a website is equipped with an encrypted security layer.
HTTPS uses TLS to protect information while it is transmitted across the network. Its principal security objectives include confidentiality of the communication channel, integrity of transmitted information, and authentication of the server through digital certificates. This is especially important when transmitting credentials, personal information, payment details, or other sensitive data.
HTTPS does not indicate what database technology the website uses, whether a content management system is installed, whether third-party cookies are present, or whether language-translation functionality exists.
Those characteristics are independent of transport-layer encryption.
From a Data Management standpoint, encryption in transit is one component of a broader Data Security framework. Sensitive data must also be protected at rest, appropriately classified, access-controlled, monitored, and governed throughout its lifecycle.
Data Quality also benefits indirectly because integrity protection helps prevent unauthorized alteration of values during transmission.
Reference Topics: DAMA-DMBOK2 Chapter 7 - HTTPS; Encryption; Data in Transit; Authentication; Confidentiality; Integrity.
72. Frage
An organization changes the definition of "Net Revenue". Before implementing the change, it wants to identify every report, transformation, and analytical model that depends on the existing definition. Which capability is most important?
Antwort: D
Begründung:
The required capability is Metadata lineage and impact analysis. Changing a business definition can affect far more than the glossary entry itself. The organization needs to know which physical fields, transformation rules, ETL jobs, calculations, reports, dashboards, analytical models, and downstream datasets depend on the current definition.
Lineage shows where data originates and how it flows and transforms. Impact analysis follows those relationships forward to determine what will be affected by a proposed change.
This prevents a common Data Quality failure in which a definition changes in one area while downstream systems continue applying the old interpretation. The result can be technically correct calculations that are semantically inconsistent.
A governed change should therefore update the business glossary, transformation metadata, Data Quality rules, reporting definitions, and affected documentation in a coordinated manner. Appropriate Data Stewards and Data Owners should approve the new meaning and effective date.
DAMA's framework describes Metadata Management as enabling understanding through definitions, lineage, and usage across systems, while the revised Chapter 13 explicitly strengthens the Data Quality-Metadata relationship.
Reference Topics: DAMA-DMBOK2 - Metadata Management; Data Lineage; Impact Analysis; Business Glossary; Data Quality Consistency.
73. Frage
Who does the DMBoK consider to be generally responsible for developing business glossary content?
Antwort: D
Begründung:
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.
74. Frage
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