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| Certification Vendor: | DAMA International |
|---|---|
| Exam Name: | DAMA Data Quality (DQ) Exam |
| Exam Number: | DQ-1220 |
| Related Certifications: | Certified Data Management Professional (CDMP) |
| Available Languages: | English |
| Exam Format: | Multiple Choice Questions |
| Recommended Training: | DAMA-DMBOK Knowledge Guide |
| Exam Registration: | DAMA International Official Website |
| Sample Questions: | DAMA DQ-1220 Sample Questions |
| Exam Way: | Online proctored or authorized testing centers depending on provider |
| Pre Condition: | No strict prerequisites; familiarity with DAMA-DMBOK recommended |
| Official Syllabus URL: | https://www.dama.org |
Since the software keeps a record of your attempts, you can overcome mistakes before the DQ-1220 final exam attempt. Knowing the style of the DAMA DQ-1220 examination is a great help to pass the test and this feature is one of the perks you will get in the desktop practice exam software.
DAMA DQ-1220 Certification Exam is a rigorous and comprehensive exam that tests a candidate’s understanding of data quality management concepts and practices. DQ-1220 exam consists of multiple-choice questions and covers a variety of topics such as data profiling, data cleansing, data governance, data quality measurement, and data quality improvement. DQ-1220 exam is designed to evaluate a candidate’s ability to apply their knowledge in real-world scenarios and to solve problems related to data quality management.
DAMA DQ-1220 Certification Exam covers a wide range of topics related to data quality management, including data profiling, data quality assessment, data cleansing, data governance, and data stewardship. DQ-1220 Exam is available in both online and in-person formats and is open to anyone interested in earning a credential in data quality management. Successful completion of the exam demonstrates an individual's ability to effectively manage data quality in a variety of organizational contexts, making them a valuable asset to any organization seeking to improve their data quality practices.
NEW QUESTION # 109
An effective Data Governance communication program should include the following:
Answer: B
Explanation:
An effective Data Governance communication program should employ multiple complementary communication mechanisms, making All answers correct. Governance changes how people define, create, use, approve, and resolve issues with data; consequently, sustained adoption requires more than publishing policies.
Regular newsletters keep stakeholders aware of progress, decisions, metrics, and upcoming activities. A Data Governance Portal provides a persistent location for policies, standards, stewardship information, glossaries, issue processes, and supporting materials. Custom training develops the capabilities required for individuals to understand their specific governance responsibilities. Informal networking events help establish relationships across business and technical groups, which is particularly important when resolving data ownership and definition conflicts.
DAMA-DMBOK2 treats communication and organizational change as core implementation considerations because governance depends on participation across functions rather than on a single technical team.
Published CDMP material for this item identifies the combined response-newsletters, portal, training, and networking-as the intended answer.
For Data Quality, communication ensures that quality definitions, issue-management procedures, stewardship responsibilities, thresholds, and remediation decisions are understood and consistently applied.
Reference Topics: DAMA-DMBOK2 Chapter 3 - Governance Communications; Organizational Change; Training; Data Governance Portal; Stewardship Engagement; Chapter 13 - Data Quality Culture.
NEW QUESTION # 110
The implementation of a 'Super Type - Sub Type' structure can use the following 2 options:
Answer: E
Explanation:
DAMA-DMBOK2 identifies two recognized approaches for resolving logical supertype-subtype abstractions when moving into physical database design: Subtype Absorption and Supertype Partition.
With Subtype Absorption, attributes belonging to subtype entities are incorporated into the table representing the supertype. Attributes that apply only to particular subtypes may consequently be nullable. This approach reduces the number of physical tables but can introduce sparsity and requires explicit rules to ensure subtype- specific attributes remain semantically valid.
With Supertype Partition, the attributes belonging to the supertype are carried into separate physical tables representing each subtype. This can simplify subtype-specific processing but introduces duplication of common structures and requires disciplined metadata and modelling control.
The choice has direct consequences for Data Quality. Subtype absorption requires validity and completeness rules to distinguish legitimate nulls from missing data. Supertype partition requires consistency controls to ensure shared attributes retain identical definitions and constraints across subtype tables. Metadata repositories should document subtype discriminators, attribute definitions, constraints, and inheritance rules.
DMBOK2 therefore treats the transformation as a deliberate physical modelling decision rather than the generic "merge/split" terminology presented in the distractors.
Reference Topics: DAMA-DMBOK2 Chapter 5 - Physical Data Modeling; Resolve Logical Abstractions; Chapter 13 - Validity, Completeness and Consistency; Metadata Management.
NEW QUESTION # 111
Achieving security risk reduction in an organisation begins with developing what?
Answer: A
Explanation:
Effective security risk reduction begins by understanding what data exists, how sensitive or critical it is, and where it resides. A classification model provides this foundation by classifying data concepts according to protection requirements and linking those concepts to their physical implementations. The certification material reflects this DAMA principle directly.
Data cannot be protected proportionately if the organization does not know whether it represents public information, internal operational information, personally identifiable information, financial data, intellectual property, regulated information, or another sensitive category. Classification allows the organization to apply appropriate controls according to risk rather than treating every data asset identically.
Once classification is established, security teams can define access requirements, encryption needs, monitoring, retention controls, masking, authorization policies, and other safeguards. Metadata is essential because classifications must ultimately be connected to actual databases, files, attributes, interfaces, and repositories.
A firewall alone does not provide data-level protection, and role classification by itself addresses only one dimension of security. Similarly, an Enterprise Data Model describes organizational data structures but does not replace security classification.
Reference Topics: DAMA-DMBOK2 Chapter 7 - Data Security; Data Classification; Risk Reduction; Sensitive Data Discovery; Metadata Management; Chapter 13 - Integrity and Controlled Use.
NEW QUESTION # 112
The Family Name of a Person is recorded in a system. The column name is Pname. Pname is an example of:
Answer: C
Explanation:
Pname is Metadata because it is the name assigned to a database column and therefore describes the structure in which the actual Family Name values are stored. A value such as Smith or Patel would be data; Pname is structural information describing that data.
DAMA-DMBOK2 defines Metadata broadly as information about data and data-related processes. Technical metadata includes physical database characteristics such as table names, column names, datatypes, lengths, indexes, constraints, and related structural properties. The interpretation of Pname as metadata is also consistent with the published version of this exact certification question.
The fact that Pname may be an unclear abbreviation does not change its classification. It may represent a poor naming convention from a usability or governance perspective, but technically it remains metadata. A stronger physical name might be FamilyName, while the metadata repository could additionally map that field to the authoritative business glossary term.
This distinction matters to Data Quality because rules are frequently attached to metadata objects. For example, the Family Name attribute might have completeness, permitted-character, maximum-length, and standardization requirements.
Effective Metadata Management connects the technical column to its business meaning, system lineage, stewardship, and applicable Data Quality controls.
Reference Topics: DAMA-DMBOK2 Chapter 11 - Technical Metadata; Database Metadata; Business Glossary; Chapter 13 - Data Quality Rules and Metadata.
NEW QUESTION # 113
Integrating data security with document and content management knowledge areas, guides the implementation of:
Answer: D
Explanation:
Document and Content Management focuses on information stored outside conventional relational databases, including documents, images, multimedia, email, and other semi-structured or unstructured assets. Integrating this knowledge area with Data Security therefore guides the implementation of appropriate access and authorization controls for unstructured data.
DAMA's framework treats security as a cross-cutting discipline rather than something applicable only to database tables. Organizational documents can contain personally identifiable information, intellectual property, contracts, financial records, or other confidential material and therefore require the same disciplined approach to authentication, authorization, classification, retention, and monitoring as structured data. DAMA- aligned references explicitly identify appropriate access and authorization to unstructured data as the relevant interaction between these knowledge areas.
Metadata is also important because document classifications, ownership, retention category, confidentiality level, and permitted audiences provide the information needed to enforce controls.
Option A refers to structured data and therefore misses the specific contribution of Document and Content Management. Fitness-for-purpose measurement belongs primarily to Data Quality, while data-mart privacy addresses a narrower structured analytical environment.
Reference Topics: DAMA-DMBOK2 Chapter 7 - Data Security; Chapter 9 - Document and Content Management; Unstructured Data; Access Control; Authorization; Information Classification.
NEW QUESTION # 114
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