Our DQ-1220 exam dumps provide you the best learning opportunity with employing minimum efforts while the results are pleasantly surprising beyond your expectations. The quality of our DQ-1220 praparation materials is outstanding and famous. We can claim that if you study with our DQ-1220 learning guide for 20 to 30 hours, then you are bound to pass the exam with confidence. Meanwhile, you will enjoy the study expecience for there are three different versions to choose from.
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Quality Concepts and Principles | 15% | - Data quality dimensions - Definition and importance of data quality - Data quality in DMBOK framework |
| Topic 2: Data Quality Strategy and Governance | 20% | - Data quality strategy and policy - Roles and responsibilities - Integration with data governance |
| Topic 3: Tools, Techniques and Implementation | 20% | - Business value and ROI - Data quality tools and technologies - Data quality in lifecycle management |
| Topic 4: Data Quality Improvement | 20% | - Root cause analysis - Data cleansing and standardization - Monitoring and continuous improvement |
| Topic 5: Data Quality Assessment and Profiling | 25% | - Assessment methods and tools - Data profiling techniques - Defining quality rules and metrics |
Our product boosts varied functions to be convenient for you to master the DQ-1220 training materials and get a good preparation for the exam and they include the self-learning, the self-assessment, stimulating the exam and the timing function. We provide 24-hours online on DQ-1220 Guide prep customer service and the long-distance professional personnel assistance to for the client. If clients have any problems about our DQ-1220 study materials they can contact our customer service anytime.
NEW QUESTION # 55
Emergency contact phone number would be found in which master data management program?
Answer: C
Explanation:
An emergency contact phone number belongs to the Employee master-data domain. Employee Master Data describes relatively stable information about employees that needs to be consistently identified and reused across organizational processes and systems. Contact details associated with an employee-including emergency-contact information-therefore fall naturally within an Employee MDM program rather than Product or Asset MDM.
The broader DAMA Master Data framework identifies employees as one of the recurring enterprise entities that may require coordinated management alongside customers, products, suppliers, locations, and similar core subjects. Published versions of this specific DAMA certification item likewise identify Employee as the correct domain.
Managing this information centrally or through coordinated master-data processes helps prevent conflicting phone numbers, obsolete emergency contacts, duplicate employee identities, and inconsistent values across Human Resources and other authorized systems.
The data is also sensitive personal information. Governance should therefore define ownership, access rights, retention rules, and permitted usage. Quality controls should address completeness, validity, currency, and accuracy, because outdated emergency-contact information may fail precisely when it is needed.
Metadata Management should record definitions and classifications so that "emergency contact phone number" is consistently distinguished from an employee's own mobile or work telephone number.
Reference Topics: DAMA-DMBOK2 Chapter 10 - Master Data Domains; Employee Master Data; Data Governance; Chapter 13 - Accuracy, Completeness and Currency.
NEW QUESTION # 56
Database monitoring tools measure key database metrics, such as:
Answer: C
Explanation:
DAMA-DMBOK2 identifies capacity, availability, cache performance, and user statistics as representative metrics captured by database-monitoring tools. Database monitoring is an operational control mechanism used by Database Administrators and platform teams to understand whether database infrastructure is available, adequately sized, responsive, and being used as expected. DMBOK2 explicitly describes monitoring tools as automating the observation of metrics such as capacity, availability, cache performance, and user statistics.
Capacity metrics indicate resource consumption and future growth requirements. Availability measures whether data services remain accessible when required. Cache-performance measures help identify inefficient access patterns and bottlenecks, while user statistics provide information about workload and database consumption.
The other choices mix design concepts, CRUD operations, or Data Quality concepts with operational monitoring measures. For example, normalization is a modelling technique rather than a routine runtime performance metric. Similarly, "create, read, update, delete" describes basic data operations rather than monitoring indicators.
Although database performance and Data Quality are distinct disciplines, poor operational performance can affect Data Quality dimensions such as timeliness and availability. Monitoring therefore supports the technical environment in which governed, reliable information is delivered to users and applications.
Reference Topics: DAMA-DMBOK2 - Data Storage and Operations; Database Operations; Capacity and Availability Management; Monitoring; Chapter 13 - Timeliness and Operational Fitness for Purpose.
NEW QUESTION # 57
A Data Quality incident affects several downstream systems. What should be determined before individual teams independently correct their copies?
Answer: B
Explanation:
The organization should determine the root cause and authoritative remediation point before multiple teams independently modify downstream copies.
If a defective value originates in a source system and is distributed to five downstream applications, correcting those five copies independently may provide temporary relief but leaves the upstream defect intact.
The incorrect value may simply be redistributed again.
Lineage should be used to trace the defect through source systems, transformations, integration layers, Master Data hubs, warehouses, and reports. Once the origin is understood, governance can determine which system or process is authoritative and where correction should occur.
This approach minimizes inconsistent local fixes and reduces the risk that different teams apply incompatible interpretations of the same issue.
DAMA's Chapter 13 revision explicitly strengthens the relationship between Data Quality and Metadata Management, Reference/Master Data Management, Modeling, and Data Integration. Those connections are precisely what enable cross-system issue resolution.
Downstream correction may still be required after the authoritative source is fixed, but it should be coordinated.
Reference Topics: DAMA-DMBOK2 Chapter 13 - Root-Cause Analysis; Issue Management; Metadata Lineage; Authoritative Sources; Data Integration.
NEW QUESTION # 58
An address-validation service reports that 96% of customer addresses conform to an approved postal format.
What does this metric demonstrate most directly?
Answer: C
Explanation:
The metric demonstrates Validity because it measures whether address values conform to a defined format or standard.
Validity checks whether data satisfies specified rules concerning datatype, pattern, permitted values, ranges, or structures. Postal formatting rules might require approved postcode structure, valid country-code syntax, or required address components.
The metric does not prove that the address belongs to the correct customer. A perfectly formatted address may still be factually wrong. That would be an Accuracy problem.
DAMA-aligned government guidance defines validity in terms of conformity to expected format, type, range, and other predefined rules.
A mature address-quality program may combine validity with verification against authoritative postal reference data, duplication checks, completeness rules, and currency monitoring.
Quality scorecards should therefore label the metric precisely rather than calling the result a generic "accuracy score." Reference Topics: DAMA-DMBOK2 Chapter 13 - Validity; Accuracy; Data Quality Metrics; Address Quality; Reference Data.
NEW QUESTION # 59
A dataset contains every required customer record, but 8% of the telephone numbers belong to different people. Which statement is correct?
Answer: A
Explanation:
The dataset can be complete while remaining inaccurate. Completeness measures whether the required records and values are present; Accuracy measures whether those values correctly represent reality.
If every customer has a telephone number, the field may achieve 100% completeness. However, if 8% of those numbers belong to other people, the values are inaccurate.
This distinction is one of the most important principles in Data Quality measurement. A populated field is not automatically trustworthy. Similarly, a syntactically valid value is not necessarily accurate.
DAMA-aligned guidance explicitly distinguishes these dimensions and notes that a complete dataset may still contain incorrect values.
The appropriate quality scorecard should therefore present completeness and accuracy separately rather than treating one as evidence of the other.
For high-risk customer contact processes, the business may define independent thresholds for both dimensions. Verification services, customer confirmation, authoritative sources, and exception handling may be needed to improve accuracy after basic completeness has already been achieved.
Reference Topics: DAMA-DMBOK2 Chapter 13 - Completeness; Accuracy; Data Quality Dimensions; Metrics; Fitness for Purpose.
NEW QUESTION # 60
......
It is universally acknowledged that DQ-1220 certification can help present you as a good master of some knowledge in certain areas, and it also serves as an embodiment in showcasing one’s personal skills. However, it is easier to say so than to actually get the DQ-1220 certification. We have to understand that not everyone is good at self-learning and self-discipline, and thus many people need outside help to cultivate good study habits, especially those who have trouble in following a timetable. Buy our DQ-1220 Exam Questions, we will help you pass the DQ-1220 exam without difficulty.
Valid Exam DQ-1220 Practice: https://www.itexamdownload.com/DQ-1220-valid-questions.html