TestSimulate also offers the DQ-1220 web-based practice exam with the same characteristics as desktop simulation software but with minor differences. It is online DQ-1220 Certification Exam which is accessible from any location with an active internet connection. This DAMA DQ-1220 Practice Exam not only works on Windows but also on Linux, Mac, Android, and iOS. Additionally, you can attempt the DAMA DQ-1220 practice test through these browsers: Opera, Safari, Firefox, Chrome, MS Edge, and Internet Explorer.
| Section | Objectives |
|---|---|
| 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 Assessment | - Data Profiling Techniques - Data Quality Metrics and KPIs |
| Data Quality Management | - Roles and Responsibilities (Data Stewardship) - Data Quality Governance |
| Data Quality Operations | - Data Quality Tools and Technologies - Monitoring and Reporting |
>> Reliable DQ-1220 Test Book <<
Customers always attach great importance to the quality of DQ-1220 exam torrent. We can guarantee that our study materials deserve your trustee. We have built good reputation in the market now. After about ten yearsโ development, we have owned a perfect quality control system. All DQ-1220 exam prep has been inspected strictly before we sell to our customers. Generally, they are very satisfied with our DQ-1220 Exam Torrent. Also, some people will write good review guidance for reference. Maybe it is useful for your preparation of the DQ-1220 exam. In addition, you also can think carefully which kind of study materials suit you best. If someone leaves their phone number or email address in the comments area, you can contact them directly to get some useful suggestions.
NEW QUESTION # 53
The loading of country codes into a CRM is a classic:
Answer: C
Explanation:
Loading standardized country codes into a CRM is a classic example of Reference Data Integration. Country codes constitute controlled reference values used to classify or characterize other data. They differ from transactional information such as orders and payments and from master entities such as individual customers or products.
DAMA treats countries, currencies, geographic classifications, status codes, and similar controlled domains as typical Reference Data. The uploaded question therefore tests the distinction between integrating reusable code sets and integrating Master or Transaction Data. Published versions of the same DAMA item confirm Reference Data Integration as the intended answer.
In practice, an authoritative reference source may provide standardized country identifiers to CRM, ERP, MDM, analytical, and integration systems. Central management prevents different applications from independently inventing or changing equivalent codes.
This is also a Data Quality control. Reference integration improves Validity by restricting values to approved domains and Consistency by ensuring that different systems interpret equivalent countries identically. For example, an uncontrolled mixture of GB, UK, 826, and proprietary internal codes may create integration and reporting errors unless mappings are formally governed.
Metadata should document the authoritative source, code meaning, effective dates, mappings, ownership, and applicable standards.
Reference Topics: DAMA-DMBOK2 Chapter 10 - Reference Data; Code Sets; Reference Data Integration; Authoritative Sources; Chapter 13 - Validity and Consistency.
NEW QUESTION # 54
Which DMBoK knowledge area is most likely responsible for a high percentage of returned mail?
Answer: A
Explanation:
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.
NEW QUESTION # 55
The seven Vs of Big Data are:
Answer: C
Explanation:
Within the DMBOK2 framing used by this certification material, the expanded characteristics are Volume, Velocity, Variety/Variability, Viscosity, Volatility, and Veracity. Option E is therefore the only choice that correctly contains the DAMA terms represented in the question. DMBOK-oriented study material explains that the original three Vs-Volume, Velocity, and Variety-were expanded to include Variability, Viscosity, Volatility, and Veracity in the broader characterization.
Volume concerns data quantity; Velocity concerns the rate of creation and processing; Variety/Variability concerns differing structures and changing representations; Viscosity describes difficulty in using or integrating the data; Volatility concerns how quickly usefulness or meaning changes; and Veracity addresses credibility and trustworthiness.
These characteristics have direct Data Quality implications. Increased variety creates semantic and structural consistency challenges. Velocity reduces the time available for traditional validation. Volatility affects currency and timeliness. Veracity is directly concerned with reliability.
DAMA's key point is that Big Data does not reduce the need for management discipline. Its scale and complexity increase the need for metadata, governance, automated profiling, lineage, and statistically driven quality controls.
Reference Topics: DAMA-DMBOK2 Big Data and Data Science - Big Data Characteristics; Volume; Velocity; Variety/Variability; Viscosity; Volatility; Veracity; Chapter 13 - Scalable Data Quality.
NEW QUESTION # 56
Business continuity is an aspect of Governance. What should a business continuity plan include?
Answer: A
Explanation:
A Business Continuity Plan is fundamentally concerned with maintaining essential business operations when normal services are disrupted. Therefore, the correct response is that it outlines how the business will continue operating during an unplanned disruption.
Within the DAMA-DMBOK2 framework, continuity concerns interact particularly with Data Governance, Data Storage and Operations, Data Security, and operational metadata. The DMBOK2 index explicitly identifies Business Continuity Plans and associates them with operational resilience and recovery concepts. A continuity plan must address how critical processes, information assets, personnel, technology, dependencies, and recovery arrangements will sustain or restore required business capability. The established definition of a BCP likewise centers on continued operation during unplanned service disruption.
Option E is incomplete: identifying potential disruptions belongs to risk assessment and continuity planning, but merely listing disruptions does not explain how operations will continue. Options B and D concern communications rather than continuity itself.
From a Data Quality perspective, continuity controls also protect availability, timeliness, integrity, and reliability. Recovery arrangements must ensure that restored data is complete, current enough for business use, and reconciled against authoritative sources after disruption.
Reference Topics: DAMA-DMBOK2 - Data Governance; Data Storage and Operations; Business Continuity; Disaster Recovery; Backup and Recovery; Chapter 13 - Timeliness, Integrity and Fitness for Purpose.
NEW QUESTION # 57
A data lake and a data warehouse are the same concepts in so far as:
Answer: E
Explanation:
Although Data Lakes and Data Warehouses have materially different architectures, both support the broader objective of making organizational data available for reporting, analysis, analytics, and decision support.
Therefore, option B identifies their legitimate conceptual overlap.
A traditional Data Warehouse generally contains integrated, curated, structured data designed for repeatable Business Intelligence, reporting, and analytical workloads. A Data Lake typically retains larger volumes of raw or less-structured information and supports flexible processing, exploration, Data Science, and advanced analytics. Both can therefore participate in analytical data pipelines even though their approaches to schema, transformation, governance, and consumption differ.
They do not inherently duplicate every item of operational data. Nor must a Data Lake produce dimensional or star-schema models; that modeling approach is more closely associated with traditional warehouse implementations. Governance is required for both rather than being the defining difference between them.
From a Data Quality standpoint, warehouses typically apply substantial cleansing and conformity before consumption. Lakes may retain raw values and defer interpretation, which increases the importance of metadata, provenance, cataloging, profiling, and consumer awareness.
Reference Topics: DAMA-DMBOK2 - Data Warehousing and Business Intelligence; Big Data; Data Lakes; Analytical Data; Metadata; Chapter 13 - Data Preparation and Fitness for Purpose.
NEW QUESTION # 58
......
Currently DAMA products are important for enterprises information solutions, relative job opportunities are increasing more and more. DQ-1220 latest dumps vce will be useful. IT skills are regarded as an important standard for enterprises. No matter which field you work in, IT staff must keep on learning to keep up with the changes. DQ-1220 Latest Dumps vce will be a shortcut for DAMA certification and valid for your examinations.
Reasonable DQ-1220 Exam Price: https://www.testsimulate.com/DQ-1220-study-materials.html