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DAMA DQ-1220 Exam is ideal for professionals who are looking to advance their careers in the field of data quality management. DQ-1220 exam is designed for data quality analysts, data quality engineers, data quality managers, and other professionals who are responsible for ensuring the accuracy, completeness, and consistency of data across an organization. Data Quality certification provides a competitive advantage to individuals seeking to demonstrate their expertise in this field.
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DAMA DQ-1220 (Data Quality) Exam is a certification exam that is designed to test an individual's knowledge and understanding of data quality. It is a globally recognized certification that validates the expertise of professionals in the field of data quality management. DQ-1220 exam is conducted by the Data Management Association (DAMA) International, which is a global community of data management professionals.
To prepare for the DAMA DQ-1220 Exam, individuals can take data quality management courses, participate in data quality management projects, and join professional organizations such as the Data Management Association (DAMA). Moreover, individuals should review and understand the DAMA DQ-1220 exam preparation guide and sample questions, ensuring that they have understood all topics in the exam.
NEW QUESTION # 99
Descriptive metadata describes a resource, enabling its identification and retrieval.
Answer: E
Explanation:
DAMA-DMBOK2 distinguishes descriptive, structural, and administrative metadata when discussing metadata classifications used outside conventional IT contexts. Descriptive metadata identifies and describes a resource sufficiently to enable discovery and retrieval. DMBOK2 gives title, author, and subject as explicit examples of descriptive metadata.
A book's author, title, and subject therefore answer practical discovery questions: What is the resource? Who created it? What is it about? These attributes allow catalogues, repositories, search tools, and users to identify and retrieve the required resource.
Option A is principally structural metadata. DMBOK2 specifically identifies the number of pages and chapters as examples describing relationships within or among the components of a resource. Option D represents administrative metadata because version numbers and archive dates help manage the resource throughout its lifecycle.
The distinction is important to Data Quality because metadata itself must have appropriate completeness, consistency, currency, and accuracy. Incorrect descriptive metadata can make a valid data asset effectively undiscoverable or lead users to select an inappropriate source.
Metadata Management therefore supports Data Quality by giving data consumers reliable definitions, context, provenance, ownership, lineage, and usage information.
Reference Topics: DAMA-DMBOK2 Metadata Management - Descriptive Metadata; Structural Metadata; Administrative Metadata; Metadata Quality; Chapter 13 - Data Quality and Metadata Management.
NEW QUESTION # 100
What is one of the Data Architecture artifacts which are usually captured within development projects, and then standardised and managed by data architects?
Answer: D
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 # 101
A CRM contains separate records for "Jonathan Smith", "Jon Smith", and "J. Smith". Investigation confirms that all three records represent the same customer. Which Data Quality dimension is primarily affected?
Answer: B
Explanation:
The primary issue is Uniqueness because more than one record represents the same real-world entity.
Uniqueness evaluates whether unintended duplicate instances exist within a dataset or across integrated datasets.
Duplicate customer records can arise because of spelling variation, abbreviations, different contact details, weak matching rules, or inconsistent identifier capture. Exact duplicate detection alone is therefore insufficient. Effective entity resolution frequently requires probabilistic or deterministic matching across names, addresses, identifiers, telephone numbers, and other attributes.
DAMA-aligned Data Quality frameworks define uniqueness in terms of avoiding duplicate representation of the same entity. They also recognize that duplicate records may differ in individual attribute values while still representing the same person or object.
The issue is closely related to Master Data Management. An MDM process may match the three source records, establish that they belong to one customer, and apply survivorship rules to construct an authoritative master representation.
The correct remediation should also address the source process that allowed duplicates to be created; otherwise cleansing will merely remove symptoms while new duplicates continue to appear.
Reference Topics: DAMA-DMBOK2 Chapter 13 - Uniqueness; Matching; De-duplication; Chapter 10 - Master Data Management; Entity Resolution.
NEW QUESTION # 102
HTTPS:// indicates that the website is:
Answer: E
Explanation:
An address beginning with HTTPS indicates that the website uses an encrypted security layer for communications between the client and server. DAMA-DMBOK2 explicitly identifies HTTPS as a security technology and states that the https:// prefix indicates that a website is equipped with an encrypted security layer.
HTTPS uses TLS to protect information while it is transmitted across the network. Its principal security objectives include confidentiality of the communication channel, integrity of transmitted information, and authentication of the server through digital certificates. This is especially important when transmitting credentials, personal information, payment details, or other sensitive data.
HTTPS does not indicate what database technology the website uses, whether a content management system is installed, whether third-party cookies are present, or whether language-translation functionality exists.
Those characteristics are independent of transport-layer encryption.
From a Data Management standpoint, encryption in transit is one component of a broader Data Security framework. Sensitive data must also be protected at rest, appropriately classified, access-controlled, monitored, and governed throughout its lifecycle.
Data Quality also benefits indirectly because integrity protection helps prevent unauthorized alteration of values during transmission.
Reference Topics: DAMA-DMBOK2 Chapter 7 - HTTPS; Encryption; Data in Transit; Authentication; Confidentiality; Integrity.
NEW QUESTION # 103
A form permits users to enter any text into a field that should contain an ISO country code. What is the strongest preventive Data Quality control?
Answer: D
Explanation:
The strongest preventive control is to restrict data entry to the approved country-code domain. Prevention at the point of creation is generally more effective and less costly than repeatedly correcting invalid values downstream.
A controlled drop-down list, validated API, or reference-domain lookup ensures that users can select only permitted codes. This directly supports Validity and improves Consistency across applications.
The rule should be linked to centrally governed Reference Data rather than hard-coded independently in each application. That allows changes to the permitted domain to be managed systematically.
Downstream cleansing remains useful for historical defects or external data, but it should not be the primary control when the organization controls the source-entry process.
DAMA's framework links Reference/Master Data Management to consistency of shared values and Chapter
13 to defining and monitoring Data Quality controls.
Reference Topics: DAMA-DMBOK2 Chapter 13 - Preventive Controls; Validity; Data Creation; Chapter
10 - Reference Data; Controlled Domains.
NEW QUESTION # 104
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