Dama Reference And Master Data Management Exam Practice Test

Answer : B

Master data and metadata are both used to aggregate data, but master data requires that the organization identifies or develops a trusted version of truth for each of its entities.

Trusted Version of Truth:

For effective master data management, an organization must establish a single, trusted version of truth for each master data entity (e.g., customer, product).

This involves harmonizing data from various sources, resolving duplicates, and ensuring consistency and accuracy.

Master Data:

Master data includes critical business information that provides context for business transactions and analysis. It must be consistent, accurate, and up-to-date to support operational and analytical processes.

Other Options:

Transaction Activity Data: Important for operational processes but not the focus for creating master data.

One Set of Data as Source and Target: Not sufficient for managing master data.

Specific Application Solutions: While useful, they do not ensure the creation of a trusted version of truth for master data.

Transaction Audit Data: Important for auditing but not central to master data creation.

DAMA-DMBOK (Data Management Body of Knowledge) Framework

CDMP (Certified Data Management Professional) Exam Study Materials

Answer : A

International Classification of Diseases (ICD) codes are a type of industry reference data.

ICD Codes:

Developed by the World Health Organization (WHO), ICD codes are used globally to classify and code all diagnoses, symptoms, and procedures recorded in conjunction with hospital care.

They are essential for health care management, epidemiology, and clinical purposes.

Industry Reference Data:

Industry reference data pertains to standardized data used within a particular industry to ensure consistency, accuracy, and interoperability.

ICD codes fall into this category as they are standardized across the healthcare industry, facilitating uniformity in data reporting and analysis.

Other Options:

Geographic Reference Data: Includes data like country codes, region codes, and GPS coordinates.

Computational Reference Data: Used in computational processes and algorithms.

Internal Reference Data: Data used internally within an organization that is not standardized across industries.

DAMA-DMBOK (Data Management Body of Knowledge) Framework

WHO ICD Documentation

Answer : D

An authoritative system where data consumers can obtain reliable data as an alternative to the system of record is known as a 'Trusted System.'

System of Record:

The system of record (SOR) is the authoritative data source for a particular data element or dataset. It ensures data integrity, accuracy, and consistency.

Trusted System:

A trusted system provides reliable data that consumers can use for transactions and analysis. It acts as a reference point and may serve as an alternative to the system of record.

It ensures that users have access to high-quality, consistent, and trustworthy data, which is essential for decision-making and operational processes.

Other Options:

System of Reference: Generally refers to a system used for lookup and reference purposes but not necessarily authoritative for transactions.

System of Origin: The original source of data before it is integrated into other systems.

Source System: Any system that contributes data to an enterprise system but is not specifically a trusted or authoritative source.

System of Use: The system where data is actively used and consumed for various business processes.

DAMA-DMBOK (Data Management Body of Knowledge) Framework

CDMP (Certified Data Management Professional) Exam Study Materials

Answer : A

Reference data and master data serve different purposes within an organization, and storing them in separate repositories can be beneficial for managing them effectively.

Reference Data:

Reference data is used to classify or categorize other data. Examples include code tables, taxonomies, and standard lists like country codes or industry classifications.

It is often less volatile and has a higher degree of standardization.

Master Data:

Master data refers to the core business entities that are essential for operations, such as customers, products, employees, and suppliers.

It is often more dynamic and requires frequent updates to ensure accuracy and consistency across systems.

Separate Repositories:

Storing reference and master data in separate repositories allows for tailored management strategies, governance, and security measures suited to their specific needs.

This approach can improve performance, data quality, and accessibility by reducing complexity and focusing resources on maintaining each type of data appropriately.

DAMA-DMBOK (Data Management Body of Knowledge) Framework

CDMP (Certified Data Management Professional) Exam Study Materials

Answer : E

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.

Data Management Body of Knowledge (DMBOK), Chapter 7: Master Data Management

DAMA International, 'The DAMA Guide to the Data Management Body of Knowledge (DMBOK)'

Answer : B

For effective Master Data Management, an organization must agree on a single, standard definition of master data. Here's why:

Consistency:

Single Definition: A standardized definition ensures consistency across different departments and systems.

Avoids Confusion: Prevents discrepancies and misunderstandings regarding what constitutes master data.

Data Quality and Governance:

Unified Approach: A single definition supports unified data governance policies and data quality standards.

Data Integration: Facilitates easier data integration and interoperability across various systems and processes.

Business Efficiency:

Aligned Objectives: Ensures all parts of the organization are aligned in their understanding and use of master data, leading to more efficient operations and decision-making.

Data Management Body of Knowledge (DMBOK), Chapter 7: Master Data Management

DAMA International, 'The DAMA Guide to the Data Management Body of Knowledge (DMBOK)'

Answer : A

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.

Data Management Body of Knowledge (DMBOK), Chapter 7: Master Data Management

DAMA International, 'The DAMA Guide to the Data Management Body of Knowledge (DMBOK)'