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Sample CDMP-RMD Questions Answers | CDMP-RMD Reliable Test Tutorial

The Reference And Master Data Management Exam CDMP-RMD certification provides both novices and experts with a fantastic opportunity to show off their knowledge of and proficiency in carrying out a particular task. With the DAMA CDMP-RMD exam, you will have the chance to update your knowledge while obtaining dependable evidence of your proficiency. You can also get help from actual Reference And Master Data Management Exam CDMP-RMD Exam Questions and pass your dream Reference And Master Data Management Exam CDMP-RMD certification exam.

DAMA CDMP-RMD Exam Syllabus Topics:

Topic	Details
Topic 1	Reference Data Management (RDM) Lifecycle: The lifecycle of reference data management is covered in this topic.
Topic 2	Data Stewardship: The management of reference and master data by data stewards is the focal point of this topic. It addresses concepts such as accuracy, consistency, and quality of data.
Topic 3	Data Architecture: The design and implementation of data architecture for reference and master data are covered in detail in this topic. It addresses concepts including integration, standardization, and data modeling.
Topic 4	Master Data Management (MDM) Lifecycle: The phases of the MDM lifecycle such as planning, design, implementation, and continuous operation are covered in this section.

DAMA Reference And Master Data Management Exam Sample Questions (Q75-Q80):

NEW QUESTION # 75
The 'consumer of master data content received from a MDM platform can also be referred to as a:

A. Subscriber
B. Metadata repository
C. MDM platform
D. Single version of the truth
E. System of record

Answer: A

NEW QUESTION # 76
Which of the following is NOT a metric that c.tn be tied to Reference and Master Data Quality?

A. Data sharing usage
B. Service Level Agreements
C. Operational functions
D. Data sharing volume
E. The rate of change of data values

Answer: C

Explanation:
Metrics tied to Reference and Master Data Quality generally include:
* Data Sharing Usage: Measures how often master data is accessed and used across the organization.
* Rate of Change of Data Values: Tracks how frequently master data values are updated or modified.
* Service Level Agreements (SLAs): Monitors adherence to agreed-upon service levels for data availability, accuracy, and timeliness.
* Data Sharing Volume: Measures the volume of data shared between systems or departments.
* Excluded Metric - Operational Functions: While operational functions are important, they are not typically considered metrics for data quality. Operational functions refer to the various tasks and processes performed by systems and personnel but do not directly measure data quality.
* References:
* Data Management Body of Knowledge (DMBOK), Chapter 7: Master Data Management
* DAMA International, "The DAMA Guide to the Data Management Body of Knowledge (DMBOK)"

NEW QUESTION # 77
Key processing steps for successful MDM include the following steps with the exception of which processing step?

A. Data Model Management
B. Data Acquisition
C. Data Indexing
D. Entity Resolution
E. Data Sharing & Stewardship

Answer: C

Explanation:
Key processing steps for successful MDM typically include:
* Data Acquisition: The process of gathering and importing data from various sources.
* Data Sharing & Stewardship: Involves ensuring data is shared appropriately across the organization and that data stewards manage data quality and integrity.
* Entity Resolution: Identifying and linking data records that refer to the same entity across different data sources.
* Data Model Management: Creating and maintaining data models that define how data is structured and related within the MDM system.
* Excluded Step - Data Indexing: While indexing is a critical database performance optimization technique, it is not a primary processing step specific to MDM. MDM focuses on consolidating, managing, and ensuring the quality of master data rather than indexing, which is more about search optimization within databases.
* References:
* Data Management Body of Knowledge (DMBOK), Chapter 7: Master Data Management
* DAMA International, "The DAMA Guide to the Data Management Body of Knowledge (DMBOK)"

NEW QUESTION # 78
MDM matching algorithms benefit from all of the following data characteristics except for which of the following?

A. Structural heterogeneity of data elements
B. High level of comparability of the data elements
C. High validity of the data
D. Distinctiveness across the population of data
E. Low number of common data points

Answer: A

Explanation:
MDM matching algorithms benefit from various data characteristics but do not benefit from "Structural heterogeneity of data elements."
* Matching Algorithms:These are used in MDM to identify and link data records that refer to the same entity across different systems.
* Data Characteristics:
* Distinctiveness:Helps in accurately matching records.
* Common Data Points:Aids in the comparison process.
* Comparability:Facilitates effective matching.
* Validity:Ensures the data is accurate and reliable.
* Structural Heterogeneity:Different structures can complicate the matching process, making it harder to align data.
References:
* DAMA-DMBOK: Data Management Body of Knowledge, 2nd Edition.
* CDMP Study Guide

NEW QUESTION # 79
Master Data Curation is used for improving the overall quality of the data throughout the business by doing the following:

A. Providing a look up service for definitions
B. De-duplication of data.
C. Recording who owns the data
D. Performing a data audit
E. Creating a map of the enterprise data stores

Answer: B

Explanation:
Master Data Curation is a process aimed at improving the overall quality of data throughout the business.
Here's how:
* Data Quality Improvement:
* De-duplication: The process involves identifying and eliminating duplicate records to ensure a single, accurate version of each data entity.
* Data Cleaning: Removes inaccuracies and inconsistencies, enhancing the reliability of the data.
* Benefits of De-duplication:
* Accuracy: Ensures that each entity (e.g., customer, product) is represented only once, improving data accuracy and reducing redundancy.
* Operational Efficiency: Streamlines operations by eliminating duplicate records that can cause confusion and errors in business processes.
* References:
* Data Management Body of Knowledge (DMBOK), Chapter 7: Master Data Management
* DAMA International, "The DAMA Guide to the Data Management Body of Knowledge (DMBOK)"

NEW QUESTION # 80
......

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PASS GUARANTEED HIGH PASS-RATE DAMA - CDMP-RMD EXAM FORUM

Pass Guaranteed High Pass-Rate DAMA - CDMP-RMD Exam Forum