If you can own the certification means that you can do the job well in the area so you can get easy and quick promotion. The latest DQ-1220 quiz torrent can directly lead you to the success of your career. Our materials can simulate real operation exam atmosphere and simulate exams. The download and install set no limits for the amount of the computers and the persons who use DQ-1220 Test Prep. So we provide the best service for you as you can choose the most suitable learning methods to master the DQ-1220 exam torrent. Believe us and if you purchase our product it is very worthy.
| Section | Weight | Objectives |
|---|---|---|
| Data Quality Governance | 15% | - Policies and Procedures - Continuous Monitoring - Data Stewardship - Data Quality Roles and Responsibilities |
| Data Quality Improvement | 20% | - Standardization - Validation Rules - Data Cleansing Techniques - Data Enrichment |
| Data Quality Assessment and Measurement | 25% | - Profiling Techniques - Benchmarking - Root Cause Analysis - Metrics and KPIs |
| Data Quality Fundamentals | 20% | - Data Quality in the Data Lifecycle - Dimensions of Data Quality (completeness, accuracy, consistency, timeliness, validity) - Definition of Data Quality |
| Data Quality Frameworks and Standards | 20% | - ISO 8000 (Data Quality) - DAMA DMBOK Framework - Other Industry Standards |
We have thousands of satisfied customers around the globe so you can freely join your journey for the Data Quality (DQ-1220) certification exam with us. Real4dumps also guarantees that it will provide your money back if in any case, you are unable to pass the DAMA DQ-1220 Exam but the terms and conditions are there that you must have to follow.
NEW QUESTION # 110
The search function associated with a document management store is failing to return known artefacts. This is due to a failure of:
Answer: E
Explanation:
A document-management search function depends heavily on metadata to identify, index, classify, and retrieve stored content. If known artefacts exist in the repository but cannot be found through search, inadequate or incorrectly maintained metadata is the most direct explanation.
DAMA-DMBOK2 distinguishes document content from the metadata that describes it. Typical descriptive metadata includes title, author, subject, keywords, document type, creation date, classification, and other characteristics used by retrieval mechanisms. Administrative and structural metadata may additionally support lifecycle management, versioning, access control, and relationships among document components. Without sufficiently accurate and complete metadata, the repository may physically contain a document while users remain unable to discover it.
This is also a Data Quality problem. Metadata itself is data and must satisfy quality expectations such as completeness, validity, consistency, and accuracy. A missing subject classification, incorrect document type, or inconsistent keyword convention can directly reduce findability.
Public access is neither required nor desirable for all documents, especially where confidential information exists. Business Intelligence is unrelated to basic document discovery, and Data Quality metrics alone do not make a document searchable unless the underlying metadata is correctly populated.
Reference Topics: DAMA-DMBOK2 - Document and Content Management; Metadata Management; Descriptive Metadata; Search and Retrieval; Chapter 13 - Metadata Quality and Fitness for Purpose.
NEW QUESTION # 111
Database monitoring tools measure key database metrics, such as:
Answer: C
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 # 112
According to the ISO/IEC 42010:2007 Software and Systems Engineering -Architecture Description, which of the following describes the definition of architecture:
Answer: C
Explanation:
The correct definition is the fundamental organisation of a system, and the principles governing its design and evolution. DAMA-DMBOK2 incorporates the ISO/IEC 42010 architectural concept when establishing the theoretical basis for Data Architecture.
The fuller ISO formulation describes architecture in terms of the fundamental organization of a system embodied in its components, their relationships to one another and to the environment, together with the principles governing design and evolution. DAMA uses this concept to distinguish true architecture from a collection of diagrams or implementation specifications.
Option E is therefore incomplete: architectural artifacts document architecture, but the artifacts themselves are not the architecture. Option C focuses too narrowly on implementation and maintenance, while options B and D describe potential objectives or constraints rather than the definition.
Applied to enterprise data, this means architecture establishes the high-level organization of data assets, information flows, platforms, relationships, and guiding principles by which the data environment evolves.
Data Quality benefits because architectural principles establish where authoritative information originates, how it moves, how duplication is controlled, and where governance and quality controls must operate.
Reference Topics: DAMA-DMBOK2 Chapter 4 - Architecture Definition; ISO/IEC 42010; Enterprise Data Architecture; Architectural Principles; Chapter 13 - Quality by Design.
NEW QUESTION # 113
Which of the following is a directive that codifies principles and management intent into fundamental rules governing the creation, acquisition, integrity, security, quality, and use of data and information?
Answer: D
Explanation:
The definition describes Data Policies. DAMA-DMBOK2 states that data policies are directives that translate organizational principles and management intent into fundamental rules controlling how data is created, acquired, protected, maintained, assured for quality, and used.
The distinction between governance and policy is important. Data Governance is the broader authority and decision-making framework. Policies are one of the principal instruments produced or sponsored through that framework. They define what must or must not occur. Standards and procedures subsequently translate those policies into specific implementation requirements and operational methods.
For Data Quality, a policy might require business-critical data to have designated ownership, documented definitions, measurable quality rules, monitored thresholds, and formal remediation processes. The detailed thresholds themselves may reside in standards or rule repositories rather than in the high-level policy.
Metadata Management makes policy operational by documenting definitions, classifications, ownership, lineage and applicable quality rules. Master Data Management applies those policies to shared business entities and controlled reference values. Data Stewards then monitor compliance and escalate violations through governance mechanisms.
Data asset valuation is concerned with determining economic value, while Data Management encompasses the complete discipline. Neither provides the specific "directive" definition stated in the question.
Reference Topics: DAMA-DMBOK2 Chapter 3 - Data Policies; Governance Principles; Standards and Procedures; Chapter 13 - Data Quality Governance; Metadata and Master Data interactions.
NEW QUESTION # 114
The main difference between a System of Record and a System of Reference is:
Answer: D
Explanation:
DAMA-DMBOK2 distinguishes the two concepts according to origination versus authoritative consumption.
A System of Record (SoR) is an authoritative system in which data is created, captured, or maintained according to defined rules and expectations. A System of Reference (SoRef) is an authoritative location from which consumers obtain reliable information for transactions or analysis even though that information may have originated elsewhere.
Therefore, option A expresses the essential distinction most accurately. For example, an operational CRM may be the System of Record for customer data because customer information is captured and maintained there. An MDM hub or enterprise data-sharing platform can subsequently become the System of Reference used by other applications, even though the original data was created in the CRM.
This distinction is important for Data Quality and lineage. Consumers need to know where values originated, where authoritative corrections are performed, which system distributes trusted values, and which stewardship process governs conflicts between sources. Metadata should therefore record source lineage, system roles, transformations, and authoritative status.
Option D is incorrect because "System of Record" and "System of Reference" do not correspond respectively to master data and reference data categories. Either architectural role can participate in managing different categories of enterprise data.
Reference Topics: DAMA-DMBOK2 Chapter 10 - System of Record and System of Reference; Trusted Sources; MDM Architecture; Metadata Lineage; Chapter 13 - Data Quality and Reference/Master Data Management.
NEW QUESTION # 115
......
Just like the old saying goes, motivation is what gets you started, and habit is what keeps you going. A good habit, especially a good study habit, will have an inestimable effect in help you gain the success. The DQ-1220 Study Materials from our company will offer the help for you to develop your good study habits. If you buy and use our study materials, you will cultivate a good habit in study.
Knowledge DQ-1220 Points: https://www.real4dumps.com/DQ-1220_examcollection.html