Dama Reference And Master Data Management Exam Questions

Master data metadata provides crucial information about the master data, offering context and supporting its management and use within the organization.

Who, What, and Where Context:

Metadata provides descriptive information about the master data, including details about who created or modified the data, what the data represents, and where it is used.

This contextual information is essential for understanding the origins, purpose, and usage of the master data.

Includes a Sample of Content:

While metadata might include examples or samples of the data, this is not its primary purpose.

Improving Fit-for-Purpose Choices:

Metadata helps improve the application and governance of master data by providing context and supporting data management decisions.

Securing the Content:

Metadata itself is not primarily focused on security, though it can support data governance and access control processes.

Technical or Business Perspectives:

Metadata can encompass both technical and business perspectives, providing a holistic view of the data's context and usage.

DAMA-DMBOK (Data Management Body of Knowledge) Framework

CDMP (Certified Data Management Professional) Exam Study Materials

Business entities are represented within an organization through various forms, primarily as data or records within information systems.

Technical Capabilities:

While technical capabilities support the management and usage of business entities, they are not the representation of the entities themselves.

Business Capabilities:

Business capabilities describe the functions and processes that an organization can perform, but they do not represent individual business entities.

Files:

Files can contain data or records, but they are not the direct representation of business entities.

Data/Records:

Business entities are captured and managed as data or records within databases and information systems.

These records contain the attributes and details necessary to uniquely identify and describe each business entity.

Domains:

Domains refer to specific areas of knowledge or activity but are not the direct representation of business entities.

DAMA-DMBOK (Data Management Body of Knowledge) Framework

CDMP (Certified Data Management Professional) Exam Study Materials

A catalog where products are organized by category is an example of a taxonomy. Here's why:

Definition of Taxonomy:

Classification System: Taxonomy refers to the practice and science of classification. It involves organizing items into hierarchical categories based on their relationships and similarities.

Example: In the context of a product catalog, taxonomy is used to classify products into categories and subcategories, making it easier to browse and find specific items.

Application in Product Catalogs:

Categorization: Products are grouped into logical categories (e.g., Electronics, Clothing, Home Appliances) and subcategories (e.g., Smartphones, Laptops, Televisions).

Navigation and Search: Helps users navigate the catalog efficiently and find products quickly by narrowing down categories.

Data Management Body of Knowledge (DMBOK), Chapter 9: Data Architecture

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

The three primary categories of components in a Master Data Management (MDM) framework are people, process, and technology. Here's a detailed breakdown:

People:

Roles and Responsibilities: Involves defining roles such as data stewards, data owners, and data governance committees who are responsible for managing and overseeing master data.

Skills and Training: Ensuring that the individuals involved have the necessary skills and training to manage master data effectively.

Process:

Data Governance: Establishing policies, procedures, and standards for managing master data to ensure its accuracy, consistency, and reliability.

Data Lifecycle Management: Processes for creating, maintaining, and retiring master data.

Technology:

MDM Tools and Platforms: Utilizing technology solutions to support the management of master data, including data integration, data quality, and data management platforms.

Infrastructure: Ensuring the necessary technical infrastructure is in place to support MDM activities.

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

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

An organization's master data can indeed be acquired from external third parties. Here's how and why:

Third-Party Data Acquisition:

Enrichment: External data sources can be used to enrich an organization's master data, providing additional details and context.

Accuracy and Completeness: Acquiring data from reputable third-party sources can enhance the accuracy and completeness of master data.

Use Cases:

Market Data: Organizations may purchase market data to complement their internal customer or product data.

Reference Data: Common reference data, such as postal codes or industry classifications, are often obtained from external providers.

Integration:

Data Integration: Master data acquired from third parties needs to be integrated into the organization's MDM system, ensuring it aligns with existing data standards and governance policies.

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

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