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| Section | Objectives |
|---|---|
| Topic 1: Data Quality Assessment | - Data Quality Metrics and KPIs - Data Profiling Techniques |
| Topic 2: Data Quality Management | - Data Quality Governance - Roles and Responsibilities (Data Stewardship) |
| Topic 3: Data Quality Fundamentals | - Definition of Data Quality - Data Quality Dimensions (Accuracy, Completeness, Consistency, Timeliness, Validity, Uniqueness) |
| Topic 4: Data Quality Operations | - Monitoring and Reporting - Data Quality Tools and Technologies |
| Topic 5: Data Quality Improvement | - Data Cleansing Methods - Root Cause Analysis |
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NEW QUESTION # 106
A search engine database is populated by a web crawler or spider software that usually processes as:
Answer: D
NEW QUESTION # 107
Reference data is often a list of code values with their full names. One example is:
Answer: E
Explanation:
Country codes associated with country names are a classic example of Reference Data. DAMA-DMBOK2 defines Reference Data as data used to characterize or classify other data or to relate organizational data to externally defined information. The simplest reference-data structure consists of a code and its corresponding description. DMBOK2 specifically uses geographic and standards-based examples, including country codes such as DE, US, and TR.
A code such as GB therefore acts as a standardized machine-processable value, while "United Kingdom" supplies the human-readable meaning. Such code lists are reused across applications, integrations, reporting platforms, Master Data systems, and analytical environments.
Reference Data quality is important because inconsistent code sets can create widespread downstream defects.
If different systems use incompatible country codes, the organization may experience failed integrations, incorrect aggregation, duplicate mappings, reporting discrepancies, and inconsistent interpretation. Data Governance should therefore establish authoritative sources and stewardship responsibilities for important reference domains.
Metadata Management records the meaning, provenance, permitted values, relationships, and mappings between code sets. Master Data Management frequently consumes these governed codes to classify master entities such as customers, suppliers, products, and locations.
The other choices describe relationships or transformations, but they do not represent the straightforward code- value/description list structure identified by DAMA.
Reference Topics: DAMA-DMBOK2 Chapter 10 - Reference and Master Data; Reference Lists; Code Sets; Authoritative Sources; Chapter 13 - Validity, Consistency and Integrity.
NEW QUESTION # 108
The process of translating plain text into complex codes to hide privileged information is:
Answer: D
Explanation:
The process is Encryption. DAMA-DMBOK2 defines encryption as converting readable plaintext into coded information so that privileged or sensitive content cannot be understood without the appropriate decryption mechanism. The DMBOK2 security section specifically describes encryption as translating plain text into complex codes to hide privileged information and also notes its use in protecting transmission integrity and validating identity.
Encryption supports confidentiality both at rest and in transit. Depending on implementation, organizations may use symmetric encryption, asymmetric or public-key encryption, hashing for particular integrity or authentication functions, and other cryptographic mechanisms.
The crucial distinction is that encryption deliberately changes the representation of information according to a cryptographic algorithm and key structure. Encapsulation, enhancement, elimination, and exaggeration are not substitutes for cryptographic protection.
Within the wider DAMA framework, encryption should be applied according to classification and risk.
Highly sensitive information may require stronger cryptographic controls, restricted key management, rotation procedures, and separation of duties.
Data Quality and Data Security intersect at integrity: unauthorized changes may produce inaccurate data even when availability remains unaffected. Security controls therefore protect not merely secrecy but the reliability and trustworthiness of managed information.
Reference Topics: DAMA-DMBOK2 Chapter 7 - Encryption; Confidentiality; Data Integrity; Cryptographic Controls; Security Classification.
NEW QUESTION # 109
A Data Quality rule states that every active supplier must have a valid tax identifier. Who should approve whether the rule is mandatory for the Supplier domain?
Answer: A
Explanation:
Whether the rule is mandatory is a business governance decision and should be approved through the appropriate Data Owner, Data Steward, or governance authority responsible for the Supplier domain.
A developer can implement a database constraint, but technical implementation does not establish business policy. The organization must determine whether every active supplier genuinely requires a tax identifier, whether exceptions exist by jurisdiction or supplier type, and what consequences should follow when the rule is violated.
The approved rule should be documented as metadata and linked to the relevant business term, physical fields, authoritative sources, threshold, and responsible steward.
This illustrates the separation between governance and execution. Governance defines and authorizes the requirement; operational and technical teams implement the validation and monitoring.
DAMA's public framework places Governance across the Data Management knowledge areas and Metadata Management as the mechanism for maintaining definitions, lineage, and usage context.
Reference Topics: DAMA-DMBOK2 Chapter 3 - Governance and Stewardship; Chapter 13 - Data Quality Rules; Metadata Management; Supplier Master Data.
NEW QUESTION # 110
Descriptive metadata describes a resource, enabling its identification and retrieval.
Answer: B
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 # 111
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