VCEEngine is a dumps pdf provider that ensures you pass the DAMA braindumps exam with high rate. You may wonder how we can guarantee the high pass rate. You can rest assured that the DQ-1220 braindumps questions and learning materials are created by our IT teammates who have rich experience in the DQ-1220 Top Questions. And we constantly keep the updating of vce dumps to ensure the accuracy of questions and answers.
| Section | Weight | Objectives |
|---|---|---|
| Data Quality Fundamentals | 20% | - Data Quality in the Data Lifecycle - Definition of Data Quality - Dimensions of Data Quality (completeness, accuracy, consistency, timeliness, validity) |
| Data Quality Frameworks and Standards | 20% | - ISO 8000 (Data Quality) - Other Industry Standards - DAMA DMBOK Framework |
| Data Quality Assessment and Measurement | 25% | - Root Cause Analysis - Benchmarking - Metrics and KPIs - Profiling Techniques |
| Data Quality Governance | 15% | - Policies and Procedures - Data Quality Roles and Responsibilities - Data Stewardship - Continuous Monitoring |
| Data Quality Improvement | 20% | - Validation Rules - Standardization - Data Enrichment - Data Cleansing Techniques |
>> DQ-1220 Relevant Answers <<
There is considerate and concerted cooperation for your purchasing experience on our DQ-1220 exam braindumpsaccompanied with patient staff with amity. You can find DQ-1220 simulating questions on our official website, and we will deal with everything once your place your order. You will find that you can receive our DQ-1220 training guide in just a few minutes, almost 5 to 10 minutes. And if you have any questions, you can contact us at any time since we offer 24/7 online service for you.
NEW QUESTION # 89
What is one of the Data Architecture artifacts which are usually captured within development projects, and then standardised and managed by data architects?
Answer: C
Explanation:
The correct answer is Data models. DAMA-DMBOK2 explicitly explains that data models and other Data Architecture artifacts are commonly created or captured within development projects and are subsequently standardized and managed by Data Architects.
Development projects routinely produce conceptual, logical, and physical representations of the data required by a solution. If each project develops those structures independently without architectural review, inconsistent terminology, duplicated entities, conflicting definitions, and incompatible relationship structures can accumulate across the enterprise. Data Architects therefore review project models, reconcile them with enterprise standards, and identify structures suitable for reuse.
An Enterprise Data Model is itself an important architectural artifact, but the wording of the question refers specifically to artifacts typically generated in individual development projects and later standardized. The DMBOK2 passage uses data models in precisely that context.
This process has a direct Data Quality benefit. Standardized models improve consistency of definitions, domains, keys, relationships, and constraints. They also provide metadata from which integrity, uniqueness, validity, and completeness rules can be derived.
Reference Topics: DAMA-DMBOK2 Chapter 4 - Data Architecture; Architectural Artifacts; Development Projects; Chapter 5 - Data Modeling and Design; Chapter 13 - Consistency and Integrity.
NEW QUESTION # 90
A business driver for the creation of a Data Quality Management program is:
Answer: E
Explanation:
A primary business driver for establishing a Data Quality Management program is to reduce the risks and costs associated with poor-quality data. DAMA-DMBOK2 treats low-quality data as a direct source of operational cost and organizational risk. The Chapter 13 business drivers include increasing the value of organizational data, reducing risks and costs caused by poor quality, improving efficiency and productivity, and protecting organizational reputation.
Poor-quality data generates both visible and hidden costs. Examples include rework, manual correction, incorrect invoices, failed customer interactions, regulatory exposure, inappropriate decisions, integration delays, missed opportunities, and reputational damage. DMBOK2 further emphasizes that low-quality data represents cost and risk rather than value, making Data Quality management necessary throughout the data lifecycle.
A formal DQ program addresses these consequences through defined requirements, profiling, measurement, root-cause analysis, corrective and preventive action, monitoring, and governance. The purpose is therefore broader than making the DQ team efficient or supporting a specific technology initiative such as warehouse consolidation.
The economic and risk-reduction argument also provides the strongest basis for executive sponsorship because improvements can be linked directly to measurable business outcomes.
Reference Topics: DAMA-DMBOK2 Chapter 13 - Business Drivers; Costs of Poor Data Quality; Risk Reduction; Data Quality Program; Data Quality Lifecycle.
NEW QUESTION # 91
Database monitoring tools measure key database metrics, such as:
Answer: E
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 # 92
Three source systems provide different telephone numbers for the same customer. An MDM hub selects one number according to approved source-priority rules. This is an example of:
Answer: B
Explanation:
The process is Survivorship. In Master Data Management, survivorship determines which value should become the preferred or authoritative representation when multiple source records contain conflicting values for the same attribute.
Rules may prioritize particular systems, use recency, trust scores, verification status, completeness, or combinations of factors. For example, a verified customer-service update might outrank an older marketing- system telephone number.
Survivorship occurs after or in conjunction with matching and entity resolution. The organization first determines that records from different sources represent the same real-world customer and then determines which attribute values should populate the mastered representation.
The process requires governance because the "best" value is a business decision, not merely a technical one.
Data Stewards should approve the rules, and metadata should record source priority, rule logic, and lineage.
DAMA's framework positions Reference and Master Data Management as the discipline responsible for ensuring consistent core entities across the organization.
Reference Topics: DAMA-DMBOK2 Chapter 10 - Master Data Management; Matching; Survivorship; Authoritative Values; Chapter 13 - Consistency and Accuracy.
NEW QUESTION # 93
The implementation of data architecture exposes the transformation of data as it moves across the landscape.
A common name for this concept is:
Answer: D
Explanation:
The concept described is Data Lineage. Data lineage records how data originates, moves, transforms, and is consumed across the information landscape. DAMA-oriented architecture guidance explicitly links implementation of Data Architecture with visibility into transformations occurring as data traverses systems and identifies this as lineage.
Lineage can operate at several levels. At a high level, it may identify that customer information moves from CRM into an integration platform, Master Data hub, warehouse, and reporting environment. At a detailed level, it may show that a particular report column derives from a specific source attribute through documented calculations, mappings, and transformation rules.
This capability is fundamental to Data Quality. When an incorrect result appears in a report, lineage helps analysts trace the defect upstream to the point where it originated or was introduced. It also supports root- cause analysis, impact assessment, regulatory traceability, change management, and reconciliation.
Metadata Management provides the repository structures needed to capture and maintain lineage. Data Governance determines which lineage must be documented and who is accountable for maintaining it.
ETL is one mechanism through which data may move and transform, but ETL is not the architectural concept describing the end-to-end history and derivation of the data.
Reference Topics: DAMA-DMBOK2 Chapter 4 - Data Architecture; Chapter 11 - Metadata Management; Data Lineage; Chapter 13 - Root-Cause Analysis and Data Quality Traceability.
NEW QUESTION # 94
......
with the development of science and technology, we can resort to electronic DQ-1220 exam materials, which is now a commonplace, and the electronic materials with the highest quality which consists of all of the key points required for the exam can really be considered as the royal road to learning. And you are sure to pass the DQ-1220 Exam as well as getting the related certification under the guidance of our DQ-1220 study guide which you can find in this website easily.
Sample DQ-1220 Questions Pdf: https://www.vceengine.com/DQ-1220-vce-test-engine.html