최근 DAMA인증 DQ-1220시험이 IT업계에서 제일 높은 인지도를 가지고 있습니다.바라만 보지 마시고DAMA인증 DQ-1220시험에 도전해보세요. PassTIP 의 DAMA인증 DQ-1220덤프로 시험준비공부를 하시면 한방에 시험패스 가능합니다. DAMA인증 DQ-1220덤프로 자격증취득에 가까워지고 나아가서는 IT업계에서 인정을 받는 열쇠를 소유한것과 같다고 할수 있습니다.
| Certification Vendor: | DAMA International |
|---|---|
| Exam Name: | Data Quality |
| Exam Number: | DQ-1220 |
| Exam Duration: | 90 minutes |
| Exam Format: | Scenario-Based, Multiple Choice |
| Certificate Validity Period: | 3 years |
| Passing Score: | 70% |
| Available Languages: | English |
| Related Certifications: | DMF-1220 Data Management Fundamentals CDMP Associate DG-1220 Data Governance CDMP Master CDMP Fellow |
| Real Exam Qty: | 70-100 |
| Exam Price: | $311 USD (member), $411 USD (non-member) |
| Recommended Training: | DAMA DMBOK Guide Official CDMP Study Resources |
| Exam Registration: | DAMA Official Registration Testing Partner: Kryterion |
| Sample Questions: | DAMA DQ-1220 Sample Questions |
| Exam Way: | In-person at authorized test centers or remote online proctored |
| Pre Condition: | Recommended: DMF-1220 (Data Management Fundamentals) or equivalent knowledge; 2+ years of data management experience |
| Official Syllabus URL: | https://dama.org/certification/cdmp/ |
DAMA인증 DQ-1220시험취득 의향이 있는 분이 이 글을 보게 될것이라 믿고PassTIP에서 출시한 DAMA인증 DQ-1220덤프를 강추합니다. PassTIP의DAMA인증 DQ-1220덤프는 최강 적중율을 자랑하고 있어 시험패스율이 가장 높은 덤프자료로서 뜨거운 인기를 누리고 있습니다. IT인증시험을 패스하여 자격증을 취득하려는 분은PassTIP제품에 주목해주세요.
DAMA DQ-1220 시험은 데이터 품질 분야의 경력을 추구하는 데 관심이있는 개인뿐만 아니라 이미 현장에서 일하고 있으며 자신의 숙련도를 보여 주려고하는 사람들을위한 것입니다. 시험은 또한 데이터 품질 인력의 기술을 평가하고 개선을위한 영역을 식별하려는 조직에도 유용합니다.
질문 # 44
Critical Data is most often used in:
정답：D
설명：
All of these is correct because DAMA-DMBOK2 defines criticality according to the business use and impact of the data rather than by a particular technical characteristic. Critical Data Elements are commonly associated with regulatory, financial, or management reporting; operational business needs; measurement of product quality and customer satisfaction; and strategic initiatives such as competitive differentiation. DAMA's revised Chapter 13 also explicitly adds and clarifies the concept of Critical Data Elements within the Data Quality framework.
The purpose of identifying critical data is prioritization. Organizations cannot apply identical levels of profiling, monitoring, stewardship, remediation, and control to every data element. Data whose failure could create substantial operational, financial, legal, regulatory, customer, or reputational impact receives greater management attention.
For example, values feeding regulatory reports require stringent accuracy and traceability; operational data may require high availability and timeliness; customer-satisfaction measures require reliable and consistent inputs; and strategically important data can affect competitive decisions. Current DAMA-aligned material confirms these same usage categories for Critical Data Elements.
Once Critical Data Elements are identified, they should be linked to business definitions, Data Owners and Stewards, quality dimensions, measurable rules, lineage, authoritative sources, thresholds, and issue- management processes.
Reference Topics: DAMA-DMBOK2 Chapter 13 - Critical Data Elements; Business Drivers; Data Quality Requirements; Prioritization; Data Governance; Metadata Management.
질문 # 45
Project costs will increase faster by adding to the data model than adding to the process model because:
정답：C
설명：
Each additional data item creates obligations across multiple lifecycle processes, which is why option D is the most complete answer. DAMA-DMBOK2 treats data as an asset that must be managed throughout an interconnected lifecycle rather than merely stored in a database. Activities include creation or acquisition, validation, integration, transformation, storage, maintenance, access, use, protection, retention, archiving, and disposal.
Consequently, introducing another meaningful data element may require changes to data models, metadata repositories, interfaces, mappings, business rules, validation controls, security classifications, quality measurements, lineage documentation, reporting logic, retention rules, and stewardship responsibilities. The cost is therefore cumulative across several management processes.
Option A identifies only migration. Option B reduces the impact to storage, which is usually a minor component. Option C applies only where a warehouse is involved. Option E identifies one legitimate consideration-security-but security is only one part of the complete management obligation.
The Data Quality implication is substantial. Every additional Critical Data Element may require explicit definitions of validity, completeness, accuracy, timeliness, and consistency, together with monitoring and issue-management procedures. This demonstrates why organizations should avoid collecting data indiscriminately and should manage data according to genuine business value and requirements.
Reference Topics: DAMA-DMBOK2 Chapter 1 - Data Lifecycle; Data as an Asset; Chapter 5 - Data Modeling; Chapter 13 - Data Quality Requirements and Monitoring.
질문 # 46
Which DMBoK knowledge area is most likely responsible for a high percentage of returned mail?
정답：D
설명：
A high percentage of returned mail is primarily a Data Quality problem. Returned correspondence frequently results from inaccurate, incomplete, obsolete, incorrectly formatted, or otherwise unusable address data. The operational symptom therefore indicates that address information is failing to meet its intended business purpose.
Published versions of this DAMA question identify Data Quality as the intended knowledge area. The underlying principle aligns directly with DMBOK2 Chapter 13: quality is assessed relative to the requirements of the business process consuming the data.
Several quality dimensions may contribute. Accuracy concerns whether the address correctly represents the customer's actual location. Completeness concerns missing apartment numbers, postal codes, or address components. Validity evaluates whether values conform to accepted formats and domains. Currency addresses whether a previously correct address has become obsolete. Consistency can also be involved where address information differs between systems.
Reference and Master Data Management may provide customer-master consolidation and standardized geographic reference values, but the direct defect represented by returned mail is poor-quality address data.
A mature response should involve profiling returned-mail records, determining defect patterns and root causes, establishing address-quality rules, correcting affected records, and introducing preventive validation at capture.
Reference Topics: DAMA-DMBOK2 Chapter 13 - Fitness for Purpose; Accuracy; Completeness; Validity; Currency; Profiling; Root-Cause Analysis.
질문 # 47
Data governance represents:
정답：E
설명：
DAMA-DMBOK2 explicitly states that Data Governance represents an inherent separation of duty between oversight and execution. It illustrates the principle through an analogy with financial governance: an auditor exercises oversight over financial processes without personally executing financial management. Similarly, Data Governance ensures that data is properly managed but does not itself perform every operational Data Management activity.
This separation is fundamental because governance must retain sufficient independence to establish rules, monitor compliance, resolve conflicts, assign accountability, and evaluate whether operational teams are managing data according to approved policies and standards.
Option B describes activities in which governance and Data Quality practitioners may collaborate, but it is not the defining governance principle. Option D is also incorrect because federated governance is only one possible operating model; DMBOK2 also recognizes centralized and replicated approaches. Option E describes an organizational implementation, not the conceptual distinction.
Within Data Quality Management, this means that governance may approve quality policies, Critical Data Elements, acceptable thresholds, stewardship structures, and escalation procedures, while DQ analysts and operational teams perform profiling, cleansing, monitoring, and remediation.
Maintaining this division reduces conflicts of interest and establishes accountability for whether data- management activities achieve agreed business objectives.
Reference Topics: DAMA-DMBOK2 Chapter 3 - Essential Concepts; Oversight versus Execution; Governance Operating Models; Chapter 13 - Data Quality Governance and Operational Responsibilities.
질문 # 48
An address-validation service reports that 96% of customer addresses conform to an approved postal format.
What does this metric demonstrate most directly?
정답：A
설명：
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.
질문 # 49
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DQ-1220최고품질 덤프자료: https://www.passtip.net/DQ-1220-pass-exam.html