Free Dama Reference And Master Data Management CDMP-RMD Exam Questions

Managing master data elements can be performed at multiple levels within an organization. This includes third-party providers such as Dun & Bradstreet (D&B) which can supply enriched and standardized master data. At the enterprise level, organizations manage master data centrally to ensure consistency and quality across all systems and processes. Within application suites such as ERP (Enterprise Resource Planning) systems, master data management ensures that data is consistent and accurate within and across different applications. Therefore, master data elements can be managed at all these points.

DAMA-DMBOK2 Guide: Chapter 10 -- Master and Reference Data Management

'The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling' by Ralph Kimball

Reference data plays a crucial role in financial trading. It includes data such as financial instrument identifiers, market data, currency codes, and regulatory classifications. Despite the dynamic nature of financial trades, reference data provides the necessary static information to execute and settle transactions. Industry estimates suggest that approximately 70% of the data used in financial transactions is reference data, underscoring its importance in the financial sector.

DAMA-DMBOK: Data Management Body of Knowledge (2nd Edition), Chapter 11: Reference and Master Data Management.

'The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling' by Ralph Kimball and Margy Ross.

Industry publications and whitepapers on reference data management in financial services.

The governance scope of an MDM program should be comprehensive, encompassing all aspects and stakeholders involved in the management and usage of master data.

Internal Data Subscribers to the Master Data:

Internal users and systems that consume master data must be governed to ensure they have access to accurate and consistent data.

Master Data Authored in the MDM User Interface:

Governance should include the processes and controls around how master data is created and maintained through the MDM interface.

External Third Parties Using Master Data:

External parties that use or access master data must be governed to ensure data security, privacy, and compliance with regulations.

Data Sources of the Master Data:

The sources from which master data is derived must be governed to ensure data quality, integrity, and consistency.

DAMA-DMBOK (Data Management Body of Knowledge) Framework

CDMP (Certified Data Management Professional) Exam Study Materials

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

Ensuring high-quality reference data is critical for maintaining data accuracy, consistency, and reliability across an organization. The best way to achieve this is through robust data governance and stewardship practices.

Government Sources:

While government sources can be reliable, they are not the only sources of high-quality reference data. Relying solely on them may limit the comprehensiveness of reference data.

Drop-Down Menus:

Drop-down menus can help prevent invalid data entry but do not address the overall quality and governance of reference data.

Data Governance and Stewardship:

Implementing data governance and stewardship ensures that reference data is managed according to defined policies, standards, and procedures.

Data governance involves establishing a framework for decision-making, accountability, and control over data management processes.

Data stewardship assigns responsibility for data quality, ensuring that data is accurate, consistent, and fit for purpose.

Standard Reference Data (ISO):

Using standard reference data from organizations like ISO can enhance data quality, but it should be part of a broader governance strategy.

External Data Providers:

External data providers can offer high-quality reference data, but relying solely on them without proper governance can lead to inconsistencies and data quality issues.

DAMA-DMBOK (Data Management Body of Knowledge) Framework

CDMP (Certified Data Management Professional) Exam Study Materials

Entities such as Customer, Product, and Employee are typical examples of master data that need to be managed.

Master Data Entities: These are the key data objects around which business transactions are conducted.

Examples:

Customer: Central to sales and service operations.

Product: Essential for inventory and sales management.

Employee: Critical for HR and payroll systems.

DAMA-DMBOK: Data Management Body of Knowledge, 2nd Edition.

CDMP Study Guide

A key point of a Master Data Management (MDM) program is that it must adapt and evolve over time. The statement that an MDM program 'can be effectively created and managed long-term using the same methodology' is not correct. MDM programs must continually evolve to address new data sources, changing business requirements, and advancements in technology. As data inventory grows and the data landscape changes, MDM methodologies and strategies need to be reassessed and updated to remain effective. This adaptability is crucial for maintaining data quality and relevance.

DAMA-DMBOK2 Guide: Chapter 10 -- Master and Reference Data Management

'Master Data Management and Data Governance' by Alex Berson, Larry Dubov

Taxonomic reference data involves categorizing and organizing data to enable structured access and retrieval. It facilitates content classification, allowing for efficient multi-level navigation, which is essential for Business Intelligence (BI) activities. By organizing data into a taxonomy, users can easily locate and analyze information, supporting better decision-making processes in BI.

DMBOK (Data Management Body of Knowledge), 2nd Edition, Chapter 11: Reference & Master Data Management.

DAMA-DMBOK Functional Framework, Function: Reference & Master Data Management.

Definitions and Context:

MDM Solution: This involves tools and processes to manage master data within an organization to ensure a single source of truth.

Onboarding Data Suppliers and Subscribers: This process involves integrating new data sources (suppliers) and distributing data to various applications or users (subscribers).

A key capability for onboarding is the flexibility in data format and transfer methods because different data suppliers may use various formats and protocols.

Ensuring flexibility allows the MDM system to easily adapt to different data sources and meet the needs of diverse data consumers, thereby facilitating quick and efficient onboarding.

DAMA-DMBOK: Data Management Body of Knowledge, 2nd Edition, Chapter 11: Master and Reference Data Management.

The Open Group, 'TOGAF Series Guide: The Data Management Capability Assessment Model (DCAM)'.

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