Dama CDMP-RMD Exam Actual Questions

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

ISO 22745 is an international standard for defining and exchanging master data.

ISO 22745:

This standard specifies the requirements for the exchange of master data, particularly in industrial and manufacturing contexts.

It includes guidelines for the structured exchange of information, ensuring that data can be shared and understood across different systems and organizations.

Standards for Master Data:

Standards like ISO 22745 help ensure consistency, interoperability, and data quality across different platforms and entities.

They provide a common framework for defining and exchanging master data, facilitating smoother data integration and management processes.

Other Options:

ETL: Refers to the process of Extract, Transform, Load, used in data integration but not a standard for defining master data.

Corporation-specific Methods: Many organizations may have their own methods, but standardized frameworks like ISO 22745 provide a common foundation.

No Standards: While not all organizations use master data, standards do exist for those that do.

ISO 22745 Documentation

DAMA-DMBOK (Data Management Body of Knowledge) Framework

CDMP (Certified Data Management Professional) Exam Study Materials

All organizations possess master data, even if it is not explicitly labeled as such. Here's why:

Definition of Master Data:

Core Business Entities: Master data refers to the critical entities around which business transactions are conducted, such as customers, products, suppliers, and accounts.

Business Operations: Every organization maintains records of these entities to support business operations, decision-making, and reporting.

Implicit Existence:

Unlabeled Data: Organizations may not explicitly label this data as ''Master Data,'' but it exists within various systems, databases, and spreadsheets.

Examples: Customer lists, product catalogs, employee records, and financial accounts.

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

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

Planned control activities are not considered master data. Here's why:

Master Data Examples:

Categories and Lists: Master data typically includes lists and categorizations that are used repeatedly across multiple business processes and systems.

Examples: Product categories, account codes, country codes, and currency codes, which are relatively stable and broadly used.

Planned Control Activities:

Process-Specific: Planned control activities pertain to specific actions and checks within business processes, often linked to operational or transactional data.

Not Repeated Data: They are not reused or referenced as a stable entity across different systems.

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

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

Every process within an MDM framework includes a degree of governance. Here's why:

Governance Definition:

Policies and Standards: Governance involves the establishment of policies, standards, and procedures to ensure data quality, consistency, and compliance.

Oversight: Provides oversight and accountability for data management practices.

MDM Processes:

Inherent Governance: All MDM processes, from data integration to data quality management, incorporate governance to ensure the integrity and reliability of master data.

Data Stewardship: Involves data stewards who oversee data governance activities, ensuring adherence to established standards and 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)'