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DAMA DQ-1220 exam covers a wide range of topics related to data quality management, including data profiling, data cleansing, data validation, and data standardization. DQ-1220 exam also covers key concepts such as data governance, data privacy, and data security. DQ-1220 Exam is designed to test the candidate's ability to apply these concepts to real-world scenarios, making it an essential certification for professionals in the data management field.
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DAMA DQ-1220: Data Quality exam is a certification program designed to validate an individual's expertise in data quality management. DQ-1220 exam is offered by the Data Management Association International (DAMA) and is recognized globally as a standard for measuring data quality proficiency. DQ-1220 Exam is designed to test the candidate's knowledge of data quality concepts, principles, and best practices.
NEW QUESTION # 105
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 # 106
A customer moved house three months ago. The CRM still contains the customer's former address, although the record was originally correct when created. Which Data Quality dimension best describes the current problem?
Answer: C
Explanation:
The issue is Currency. Currency concerns whether data remains sufficiently aligned with the current real- world state. The address was accurate when originally captured, but reality changed and the system was not updated.
This distinction matters because Data Quality can degrade over time without any technical error being introduced. Customer addresses, employment details, product prices, organizational structures, regulatory classifications, and contact details all have varying rates of change. A dataset that was reliable last year may no longer be fit for operational use today.
DAMA's current Chapter 13 revision explicitly identifies Currency as one of the nine standard Data Quality dimensions. Related DAMA-derived guidance also notes that real-world information changes and can therefore become outdated even when it was initially correct.
Organizations should establish refresh expectations according to business use. A marketing mailing list may tolerate a different update interval from an emergency-contact database.
Metadata should document refresh frequency and source authority, while quality monitoring can identify records exceeding acceptable age thresholds.
Reference Topics: DAMA-DMBOK2 Chapter 13 - Currency; Accuracy; Timeliness; Data Aging; Monitoring; Fitness for Purpose.
NEW QUESTION # 107
Well executed metadata management enables:
Answer: C
Explanation:
The fundamental outcome of well-executed Metadata Management is a consistent understanding of data resources. DAMA-DMBOK2 states this directly: effective Metadata Management enables consistent understanding of data resources and supports more efficient development across organizational boundaries.
Metadata supplies context that raw data cannot provide by itself. It explains business meaning, technical structures, valid domains, calculations, transformations, ownership, lineage, systems of record, access restrictions, known quality issues, and update schedules. DMBOK2 also identifies Data Quality rules and measurement results as forms of business metadata.
Consequently, Metadata Management is broader than database design, dimensional reporting, authorization, or Data Modeling. Each of those activities consumes metadata, but none represents its complete objective.
This capability is essential to Data Quality. A dataset cannot be meaningfully evaluated for fitness for purpose unless users know what its fields mean, where the data originated, how values were transformed, which business rules apply, and which source is authoritative. Metadata therefore provides the semantic and technical framework required to define and interpret Data Quality measurements consistently.
DAMA's current DMBOK2 revision also explicitly strengthens the relationship between Data Quality and Metadata Management.
Reference Topics: DAMA-DMBOK2 Metadata Management - Goals and Principles; Business Metadata; Technical Metadata; Data Lineage; Chapter 13 - Data Quality and Metadata Management.
NEW QUESTION # 108
A search engine database is populated by a web crawler or spider software that usually processes as:
Answer: A
NEW QUESTION # 109
The goals of data storage and operations are:
Answer: B
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 # 110
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