많은 사이트에서DAMA 인증DQ-1220 인증시험대비자료를 제공하고 있습니다. 그중에서 Itexamdump를 선택한 분들은DAMA 인증DQ-1220시험통과의 지름길에 오른것과 같습니다. Itexamdump는 시험에서 불합격성적표를 받으시면 덤프비용을 환불하는 서비스를 제공해드려 아무런 걱정없이 시험에 도전하도록 힘이 되어드립니다. Itexamdump덤프를 사용하여 시험에서 통과하신 분이 전해주신 희소식이 Itexamdump 덤프품질을 증명해드립니다.
| Section | Objectives |
|---|---|
| Data Quality Management | - Roles and Responsibilities (Data Stewardship) - Data Quality Governance |
| Data Quality Improvement | - Root Cause Analysis - Data Cleansing Methods |
| Data Quality Fundamentals | - Definition of Data Quality - Data Quality Dimensions (Accuracy, Completeness, Consistency, Timeliness, Validity, Uniqueness) |
| Data Quality Operations | - Monitoring and Reporting - Data Quality Tools and Technologies |
| Data Quality Assessment | - Data Profiling Techniques - Data Quality Metrics and KPIs |
DAMA인증 DQ-1220시험을 패스하여 자격증을 취득하여 승진이나 이직을 꿈구고 있는 분이신가요? 이 글을 읽게 된다면DAMA인증 DQ-1220시험패스를 위해 공부자료를 마련하고 싶은 마음이 크다는것을 알고 있어 시장에서 가장 저렴하고 가장 최신버전의 DAMA인증 DQ-1220덤프자료를 강추해드립니다. 높은 시험패스율을 자랑하고 있는DAMA인증 DQ-1220덤프는 여러분이 승진으로 향해 달리는 길에 날개를 펼쳐드립니다.자격증을 하루 빨리 취득하여 승진꿈을 이루세요.
질문 # 67
The need to manage data movement efficiently is a primary driver for:
정답：A
설명：
The need to manage data movement efficiently is a primary business driver for Data Integration and Interoperability (DII). DAMA-DMBOK2 states this directly. Modern organizations operate hundreds or thousands of databases, applications, files, services, data stores, external interfaces, and analytical platforms.
Data must continually move among these environments, often across organizational boundaries.
Without disciplined integration management, data movement becomes fragmented, expensive, difficult to monitor, and highly dependent on duplicated point-to-point interfaces. DII addresses this problem by establishing controlled mechanisms for extraction, transformation, messaging, replication, orchestration, APIs, data virtualization, and other forms of information exchange.
From a Data Quality perspective, every movement of data presents an opportunity either to preserve quality or to damage it. Source-to-target mappings must maintain semantic meaning, transformations must be controlled, reference values must remain consistent, and lineage must show how values were altered.
Metadata Management therefore records mappings, interface definitions, transformation rules, and lineage.
Master Data Management uses integration mechanisms to distribute governed master and reference data consistently between systems.
Data Warehousing is a major consumer of integration capabilities, but the broader discipline whose explicit driver is efficient movement across systems is Data Integration and Interoperability.
Reference Topics: DAMA-DMBOK2 Chapter 8 - Business Drivers; Data Integration and Interoperability; Data Movement; Chapter 13 - Consistency, Integrity and Transformation Quality.
질문 # 68
The implementation of a 'Master Data Repository', which is integrated across the enterprise, is an example of which integration approach?
정답：E
설명：
An enterprise Master Data Repository serving multiple applications is a classic Hub-and-Spoke integration pattern. In this architecture, shared information is consolidated physically or virtually in a central hub, while participating applications interact with that hub rather than building a separate direct interface to every other application.
DAMA-DMBOK2 explicitly identifies Master Data Management hubs, Data Warehouses, Data Marts, and Operational Data Stores as familiar examples of data hubs. The hub-and-spoke model reduces the proliferation of point-to-point interfaces and can provide a consistent enterprise view of shared data.
This architecture is particularly appropriate for MDM because customer, product, supplier, location, or other master entities often need to be standardized, matched, governed, and redistributed across many systems. The central hub can apply survivorship rules, reference mappings, stewardship decisions, and quality controls before distributing trusted values.
Replication and Change Data Capture are techniques for moving or detecting changes in data, but neither describes the overall interaction topology. Publish-subscribe may operate alongside an MDM hub as a distribution mechanism, but the enterprise repository itself represents the hub within a hub-and-spoke architecture.
Reference Topics: DAMA-DMBOK2 Chapter 8 - Hub-and-Spoke; Integration Interaction Models; Chapter
10 - Master Data Management; Enterprise Master Data Hub; Data Quality Consistency.
질문 # 69
In data security, which of the following is not one of the four A's:
정답：B
설명：
Agile is not one of the four A's of Data Security. DAMA security guidance groups core security processes around Access, Audit, Authentication, and Authorization. These capabilities collectively control who can interact with information resources, establish identity, determine permitted actions, and provide evidence of activity for monitoring and accountability. DAMA-aligned security references identify these four concepts directly.
Authentication confirms the identity of a user or system. Authorization determines what an authenticated identity is permitted to do. Access concerns the actual ability to obtain or interact with data and services.
Audit provides traceability by recording and reviewing relevant activities.
Agile, by contrast, is an approach to iterative delivery and project or product development. It may influence how security controls are implemented within development lifecycles, but it is not itself one of the foundational security-control categories identified in this model.
Data Security and Data Quality are separate but related disciplines. Unauthorized modifications can compromise accuracy and integrity, while weak auditability can prevent organizations from identifying how data was altered. Appropriate security controls therefore help preserve the reliability of governed information.
Metadata classification also supports these controls by identifying sensitive data and linking it to access and protection requirements.
Reference Topics: DAMA-DMBOK2 Chapter 7 - Data Security; Access; Authentication; Authorization; Audit; Data Governance; Chapter 13 - Integrity and Controlled Data Modification.
질문 # 70
A goal of reference and master data management is for data to ensure shared data is:
정답：C
설명：
DAMA-DMBOK2 explicitly identifies a core goal of Reference and Master Data Management as ensuring that shared Master and Reference Data is complete, consistent, current, and authoritative across organizational processes.
Complete means required shared entities and attributes are sufficiently populated for their intended use.
Consistent means equivalent data has compatible meaning and representation wherever it is consumed.
Current means the information reflects an acceptably recent state. Authoritative means the organization recognizes a trusted source or governed process for determining the accepted value.
These characteristics are particularly important because Master and Reference Data is reused widely. An incorrect Product classification, Customer identifier, Country code, or Supplier status can therefore propagate defects across many systems and business processes.
DAMA also emphasizes that shared Master and Reference Data belongs to the organization rather than to a single application or department. This creates a strong requirement for enterprise stewardship and governance.
Reference and Master Data Management consequently interacts directly with Chapter 13. MDM can consolidate and distribute shared data, but it does not guarantee quality automatically. Matching, survivorship, validation, standardization, stewardship, and continuous monitoring are required to ensure the resulting records remain trustworthy.
Reference Topics: DAMA-DMBOK2 Chapter 10 - Reference and Master Data Management Goals; Shared Data; Authoritative Sources; Stewardship; Chapter 13 - Completeness, Consistency and Currency.
질문 # 71
Periodic archiving of transaction data from a production CRM system is critical for:
정답：E
설명：
Periodic archiving is critical for maintaining database performance. As a production CRM accumulates historical transactions, active tables and indexes can become increasingly large. This increases storage consumption, backup duration, index-maintenance overhead, and the quantity of data that database engines must process during operational queries.
DAMA-DMBOK2 treats archiving as an important Data Storage and Operations activity. Historical information that remains subject to retention requirements but is no longer frequently needed for operational processing can be moved to suitable archival storage. DAMA-aligned guidance for this scenario specifically links periodic transaction archiving with maintaining production database performance.
Archiving is not the same as arbitrary deletion. Retention policies, legal obligations, recovery requirements, auditability, and business value determine how long data must remain accessible and where it should be stored. The archive must also be recoverable and appropriately secured.
Data Quality implications include maintaining integrity and traceability during migration to the archive.
Records should remain complete, relationships should be preserved, and metadata should indicate retention status and archival location.
Providing reporting sources or managing deleted customers may be secondary considerations, but neither is the principal purpose described in the question.
Reference Topics: DAMA-DMBOK2 Chapter 6 - Data Storage and Operations; Archiving; Database Performance; Retention; Chapter 13 - Integrity and Historical Data.
질문 # 72
......
IT자격증을 많이 취득하여 IT업계에서 자신만의 단단한 자리를 보장하는것이 여러분들의 로망이 아닐가 싶습니다. Itexamdump의 완벽한 DAMA인증 DQ-1220덤프는 IT전문가들이 자신만의 노하우와 경험으로 실제DAMA인증 DQ-1220시험문제에 대비하여 연구제작한 완벽한 작품으로서 100%시험통과율을 보장합니다.
DQ-1220최신버전 덤프공부문제: https://www.itexamdump.com/DQ-1220.html