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DAMA DQ-1220 (Data Quality) Certification Exam is a professional certification exam that validates the knowledge and skills of individuals working in the field of data quality management. Data Quality certification exam is designed for data professionals who are responsible for ensuring the accuracy, completeness, and consistency of organizational data. DQ-1220 exam covers a wide range of topics related to data quality management, including data profiling, data cleansing, data governance, and data quality measurement.
The DAMA DQ-1220 Exam covers various topics, including data quality concepts, data quality dimensions, data quality assessment, data profiling, data cleansing, data auditing, data quality metrics, and data quality management best practices. DQ-1220 exam also covers different data quality tools and technologies that are used to manage data quality.
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The DAMA DQ-1220 Exam covers a range of topics related to data quality, including data profiling, data cleansing, data enrichment, data governance, and data quality measurement. Data Quality certification is suitable for individuals who are involved in data management, data governance, data analysis, data architecture, and data quality assurance.
NEW QUESTION # 20
The goals of data storage and operations are:
Answer: C
Explanation:
DAMA-DMBOK2 states three principal goals for Data Storage and Operations: managing data availability throughout the lifecycle, ensuring the integrity of data assets, and managing the performance of data transactions. Option A corresponds directly to those goals.
Availability means that required data and database services are accessible when business processes need them. This requires capacity planning, backup and recovery, business continuity, monitoring, and resilient infrastructure.
Integrity means protecting data assets from corruption or inappropriate alteration and maintaining reliable technical structures. Operational controls such as recovery procedures, transaction management, and controlled changes contribute directly to integrity.
Performance concerns the efficiency and responsiveness of database transactions and related storage operations. Capacity, cache behaviour, indexing, workload patterns, and system resources must therefore be monitored.
Glossary management belongs primarily to Metadata Management, while authorized access is principally a Data Security responsibility. User experience is not one of the stated core objectives for this knowledge area.
The relationship to Data Quality is direct: technically corrupted or unavailable information cannot be fit for purpose even when its business definitions are correct.
Reference Topics: DAMA-DMBOK2 Chapter 6 - Goals and Principles of Data Storage and Operations; Availability; Integrity; Performance; Chapter 13 - Data Reliability and Timeliness.
NEW QUESTION # 21
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 # 22
A customer database contains postal addresses but lacks latitude and longitude. The organization adds geographic coordinates obtained from a trusted external service. This activity is an example of:
Answer: C
Explanation:
This is Data Enrichment. Enrichment enhances existing records by adding useful information derived from internal or external sources. The original postal address remains intact, while geographic coordinates are appended to make the customer record more useful for location analysis, logistics, service coverage, route planning, or segmentation.
Enrichment differs from cleansing. Cleansing corrects or standardizes defective data; enrichment adds information that was not previously present. A process may perform both-for example, standardizing an address before passing it to a geocoding service.
External enrichment introduces governance and quality considerations. The organization should assess source reliability, licensing and permitted usage, refresh frequency, match confidence, geographical precision, lineage, and whether enrichment values should be treated as authoritative or derived.
Metadata should record that latitude and longitude were obtained from an external geocoding process rather than directly supplied by the customer. Quality metrics may measure match rate, confidence, completeness, or positional accuracy.
DAMA identifies Data Quality Management as including error detection, cleansing, and enrichment strategies, while Metadata Management supports understanding of lineage, definitions, and usage.
Reference Topics: DAMA-DMBOK2 Chapter 13 - Data Enrichment; Cleansing; Profiling; Metadata Lineage; External Data Sources.
NEW QUESTION # 23
The seven Vs of Big Data are:
Answer: E
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 # 24
Compound authorization groups provide a means to:
Answer: C
Explanation:
Compound authorization groups allow access rights from multiple groups or roles to be combined so that an individual's effective permissions can be configured with greater precision. The user may inherit one set of privileges from an organizational role, another from a functional group, and additional permissions from a specialized operational responsibility. The resulting authorization can therefore be more granular than assigning every privilege individually.
DAMA's Data Security framework separates authentication-establishing identity-from authorization, which determines what an authenticated identity is permitted to access or perform. Group-based authorization is a practical mechanism for implementing those decisions. CDMP-oriented references for this specific item identify "precisely configure an individual's access to a system" as the intended answer.
The principle must nevertheless be governed carefully. Excessive overlapping group memberships can make effective permissions difficult to review and can create segregation-of-duties conflicts. Periodic access reviews, least-privilege design, role ownership, and audit trails are therefore necessary complementary controls.
Encryption addresses confidentiality of data in transit or storage and is unrelated to how permissions are assigned. Audit preparation may benefit from structured authorization, but it is not the principal purpose.
Reference Topics: DAMA-DMBOK2 Chapter 7 - Authorization; Access Control; Least Privilege; Security Roles; Audit and Monitoring.
NEW QUESTION # 25
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