Authentic DAMA Certification Exam DQ-1220 Questions Answers

DAMA-DMBOK2 defines Data Governance as the exercise of authority and control over the management of data assets. This definition distinguishes governance from the operational execution of Data Management. Independent literature describing DAMA's framework uses the same core formulation, and the DAMA Wheel places Data Governance across the other knowledge areas through this authority-and-control function.

Governance establishes decision rights, accountability, policies, standards, stewardship, issue escalation, compliance expectations, and mechanisms for monitoring whether data is being managed appropriately. It determines who is authorized to make decisions and what rules must be followed; individual Data Management knowledge areas then execute the corresponding operational activities.

Option E is closer to the broad definition of Data Management, because it refers to planning, implementation, and control across the information lifecycle. Option A describes an assessment or maturity activity. Option B describes selected governance benefits rather than its definition, while option C characterizes a collection of functions.

For Data Quality, governance provides the authority needed to define critical data, approve quality requirements and thresholds, assign accountability, prioritize remediation, and enforce standards. Without this authority structure, profiling may identify defects but the organization may lack the decision mechanisms required to correct their underlying causes.

Reference Topics: DAMA-DMBOK2 Chapter 3 — Data Governance Definition; Authority and Control; Policies and Standards; Chapter 13 — Data Quality Governance.

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The metric demonstrates Validity because it measures whether address values conform to a defined format or standard.

Validity checks whether data satisfies specified rules concerning datatype, pattern, permitted values, ranges, or structures. Postal formatting rules might require approved postcode structure, valid country-code syntax, or required address components.

The metric does not prove that the address belongs to the correct customer. A perfectly formatted address may still be factually wrong. That would be an Accuracy problem.

DAMA-aligned government guidance defines validity in terms of conformity to expected format, type, range, and other predefined rules.

A mature address-quality program may combine validity with verification against authoritative postal reference data, duplication checks, completeness rules, and currency monitoring.

Quality scorecards should therefore label the metric precisely rather than calling the result a generic "accuracy score."

Reference Topics: DAMA-DMBOK2 Chapter 13 — Validity; Accuracy; Data Quality Metrics; Address Quality; Reference Data.

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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.

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