Most Recent Dama CDMP-RMD Exam Questions & Answers

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

Ownership is a crucial principle in managing Reference and Master Data. Here's an in-depth look at why:

Organizational Ownership:

Unified Responsibility: Reference and Master Data are assets that span across various functions and departments within an organization.

Consistency and Accuracy: Ensuring that data ownership is attributed to the organization prevents silos and ensures data is consistently accurate and available across all departments.

Data Governance: Proper governance frameworks ensure that data is managed in a way that meets the organization's needs and complies with relevant regulations and standards.

Avoiding Departmental Silos:

Cross-functional Use: Different departments use and rely on Reference and Master Data, so ownership by a single department can lead to conflicts and inconsistencies.

Holistic Management: Centralized ownership enables holistic data management practices, enhancing data quality and usability across the organization.

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

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

The centralized style is the easiest MDM style to implement data governance because it consolidates all master data into a single central repository. This centralization simplifies the application of data governance controls, ensuring consistent data quality, standards, and policies are applied across the organization.

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

Master Data Management and Data Governance by Alex Berson and Larry Dubov.

An Operational Level Agreement (OLA) is used for detailing collaboration principles, escalation, and dispute resolution processes between MDM and its data suppliers. Here's why:

Purpose of an OLA:

Collaboration Principles: Defines how MDM teams and data suppliers will collaborate, including roles, responsibilities, and communication protocols.

Escalation Processes: Outlines the steps for escalating issues when standard resolution mechanisms are insufficient, ensuring timely and effective problem resolution.

Dispute Resolution: Specifies methods for resolving disputes between parties, fostering a cooperative and constructive working relationship.

Other Documents:

Business Requirements Document: Defines business needs and requirements but doesn't typically focus on operational collaboration.

Metadata Catalog: Describes metadata and data dictionaries, not collaboration principles.

Warranty: Provides guarantees on products or services, irrelevant to operational collaboration.

Operations Run Book: Details operational procedures and workflows, not specifically focused on collaboration and dispute resolution.

Data Management Body of Knowledge (DMBOK), Chapter 8: Data Quality Management

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

Protecting and securing master data in a production environment can be achieved through various methods. Encryption ciphers, static masking, trust model technologies, and dynamic masking are all techniques used to safeguard data. However, usage agreements, while important for data governance and legal compliance, are not a technical method for securing data in the same way that the other options are. Usage agreements define the terms under which data can be accessed and used, but they do not directly protect the data itself.

DAMA-DMBOK2 Guide: Chapter 11 -- Data Security Management

'Data Masking: A Key Component of a Secure Data Management Strategy' by Anjali Kaushik