About
This focused course explores two essential disciplines from the DAMA-DMBOK® framework—Reference Data Management and Master Data Management—which are jointly addressed within a single functional area in the DAMA body of knowledge.
Reference data is “data that helps to make sense of other data,” such as code lists and hierarchies that provide context and classification (e.g. country codes, industry taxonomies). Master data, on the other hand, relates to core business entities such as customers, products, suppliers, and employees—and the governance of a trusted “golden copy” of that data across systems.
This course prepares participants for the DAMA International 32524 Reference and Master Data Management certification exam, providing the knowledge and tools to build effective, scalable, and governed RDM and MDM capabilities in modern organisations.
Where is this course available?
This course is available In-Person in Doha, Qatar, Dubai, Abu Dhabi in UAE & Riyadh in Saudi Arabia, Muscat in Oman and Amman in Jordan as well as being available Online Worldwide.
Learning Objectives
By the end of this course, participants will be able to:
Distinguish between reference data and master data, and explain their interdependencies
Understand how RDM and MDM support data consistency, quality, and integration across systems
Apply the DAMA-DMBOK® framework to govern, design, and maintain trusted master and reference datasets
Implement lifecycle management for reference and master data, including change control and versioning
Evaluate common RDM and MDM architecture patterns, tools, and implementation strategies
Align MDM and RDM practices with business goals, regulatory requirements, and data governance programmes
Be fully prepared to sit the DAMA International 32524 certification exam
Who Is This Training Course For?
This course is designed for professionals responsible for ensuring consistency and trust in enterprise-critical data.
Roles:
Data Governance Managers
Master Data Analysts and Architects
Data Stewards and Domain Owners
Enterprise and Information Architects
Compliance and Data Quality Specialists
CDMP® candidates pursuing RDM/MDM certification
Industries:
Finance and Banking
Healthcare and Life Sciences
Retail and E-commerce
Government and Public Sector
Manufacturing and Supply Chain
Energy and Utilities
Why Should You Take This DAMA RDM & MDM Course?
Learn how to establish a single source of truth for critical business data
Prepare for the DAMA International 32524 Specialist Exam with a practical and exam-aligned approach
Understand how RDM and MDM support digital transformation, analytics, compliance, and automation
Explore common MDM patterns (e.g. registry, consolidation, coexistence, centralised) and when to use them
Learn to manage hierarchies, taxonomies, and standardised values across systems
Build confidence in managing enterprise master and reference data in alignment with DAMA-DMBOK®
Prerequisites
There are no formal prerequisites for this course.
However, participants will benefit most if they:
Have a foundational understanding of data management concepts (e.g. through prior DAMA training or experience)
Are familiar with basic data modelling and data governance principles
Work with data structures, standards, or reporting functions involving key business entities
This course is ideal for professionals preparing for the 32524 DAMA Specialist certification or supporting RDM/MDM implementation projects in real-world environments.
Please note that MENA Executive Training is an independent training provider and is not affiliated with or endorsed by DAMA International. This course is intended solely to help participants prepare for the DAMA International certification examination.
Modules
Module 1: Introduction to Master and Reference Data
Definitions: What is Master Data? What is Reference Data?
Key differences and why both are critical for enterprise data management
Examples: customers, suppliers, products, industry codes, taxonomies
Overview of the DAMA-DMBOK® framework and the 32524 exam scope
Activities:
Classify examples as master or reference data
Group discussion: What is your organisation’s "golden record"?
Module 2: The Role of RDM & MDM in Enterprise Architecture
How RDM and MDM support analytics, operations, compliance, and governance
Centralisation vs. decentralisation: integration challenges
OLTP vs. OLAP systems and the role of core data entities
Activities:
Map master/reference data touchpoints across the data lifecycle
Identify risks of unmanaged RDM or MDM in your organisation
Module 3: Master Data Management Lifecycle
MDM lifecycle: create, update, retire, version
Core business entities and their attributes
Golden record creation and survivorship rules
Domains: Customer MDM, Product MDM, Supplier MDM
Activities:
Design a basic lifecycle workflow for a master data entity
Workshop: Assess your organisation’s current MDM maturity
Module 4: Reference Data Management Lifecycle
Types of reference data: controlled lists, taxonomies, hierarchies
Hierarchical reference data and their business meaning
Centralising and distributing reference data across systems
Managing externally sourced vs internally owned reference data
Activities:
Analyse a code list structure and identify maintenance needs
Create a versioning policy for a reference data domain
Module 5: Data Modelling for RDM & MDM
Modelling techniques: normalised and dimensional approaches
Managing relationships: entities, attributes, keys, and hierarchies
Handling slowly changing master data
Reference data modelling patterns
Activities:
Build a sample entity model for a product master
Review a reference data table and propose a relational structure
Module 6: Governance and Stewardship for RDM & MDM
Roles: Data Owners, Data Stewards, Domain Leads
Policies, standards, and governance structures
Stewardship tasks: validation, approval, escalation, audit
Activities:
Draft RACI chart for reference and master data processes
Role-play: steward review of a proposed master data change
Module 7: Metadata and Lineage in RDM/MDM Contexts
Metadata for master and reference data
Business glossaries vs technical metadata
Lineage and traceability: where did this data come from?
Managing metadata across platforms
Activities:
Build a basic metadata entry for a master data attribute
Trace the lineage of a reference data field across systems
Module 8: Tools and Technology Platforms
Overview of RDM/MDM platforms (e.g., Informatica MDM, SAP MDG, IBM InfoSphere, Oracle DRM)
On-prem vs cloud-native MDM tools
Capabilities: data modelling, integration, governance, workflow
Activities:
Evaluate MDM tool features in a comparison grid
Review a vendor case study or implementation video
Module 9: Implementation Strategies
MDM architectural patterns: registry, centralised, coexistence, consolidation
Phased vs. big bang rollout
Domain-driven MDM implementations
Common reference data integration patterns
Activities:
Develop a phased implementation plan for a selected domain
Identify key stakeholder groups and their adoption concerns
Module 10: Data Quality and Risk in RDM/MDM
Common quality issues: duplicates, missing values, outdated codes
Validation, enrichment, and cleansing practices
Risk management: auditability, regulatory compliance, consistency
Activities:
Run a quality assessment checklist on a sample dataset
Group exercise: Prioritise data issues by business risk
Module 11: Real-Time, Big Data, and AI-Driven MDM/RDM
Real-time integration and streaming updates to golden records
Reference data in big data environments (e.g., Hadoop, Spark)
Machine learning for entity resolution and classification
Activities:
Review an AI-powered matching tool or enrichment case study
Group discussion: Should your reference data be real-time? Why/why not?
Module 12: Case Studies and Industry Applications
Examples from healthcare, finance, retail, logistics, and public sector
Lessons learned from failed and successful implementations
MDM/RDM as enablers of digital transformation
Activities:
Analyse a case study and extract lessons for governance and tooling
Present your organisation’s current state and ideal future model
Module 13: Preparing for the DAMA 32524 Certification Exam
Summary of DAMA-DMBOK2 guidance on RDM/MDM
Practice questions and exam structure review
Tips for studying and succeeding in the exam
Activities:
Take a practice exam (40-question version)
Final Q&A and mock oral justification of an MDM strategy
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Gain an Official Data Management Global Certificate
Receive a LinkedIn Badge
Gain a Certificate After Completion
Highlight your achievement by adding this credential to your LinkedIn profile, CV, or résumé. Your digital certificate will be awarded upon successful completion of the programme, giving you a recognised credential to share with employers, colleagues, and clients.
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Exam Details
The 32524 certification exam is a DAMA International specialist-level qualification designed to validate your knowledge and understanding of Reference Data Management (RDM) and Master Data Management (MDM) as defined in the DAMA-DMBOK® framework.
It assesses the core competencies required to establish, govern, and maintain trusted master and reference data across an organisation.
This exam is ideal for data management professionals who are responsible for ensuring consistency, accuracy, and integrity of business-critical data such as customers, suppliers, products, and classification codes.
Exam Overview
Exam Code: 32524
Certification Body: DAMA International
Domain: Reference and Master Data Management (RDM & MDM)
Exam Type: Multiple-choice
Number of Questions: 100
Duration: 90 minutes
Passing Score: 70%
Question Coverage
Based on the RDM/MDM chapter of the DAMA-DMBOK2
Includes both conceptual knowledge and practical understanding
Covers:
Lifecycle management
Data quality
Governance and stewardship
Architecture patterns
Metadata and modelling
Integration with business processes and other systems
Difficulty Distribution
60% Associate level: definitions, purpose, DMBOK-aligned principles
20% Practitioner level: practical application, tool usage, lifecycle scenarios
20% Master level: strategic design, enterprise alignment, data governance integration
Key Topics Covered
Differences and interrelationships between reference data and master data
Reference data hierarchies, code lists, and taxonomies
Golden record creation and master data consolidation
Data stewardship roles and responsibilities
Master data modelling best practices
RDM and MDM governance frameworks
Lifecycle management: creation, updates, versioning, and retirement
Handling slowly changing master data
Common MDM implementation patterns: registry, hub, coexistence, consolidation
Metadata and lineage for master/reference datasets
Tool evaluation: platforms for MDM and RDM (Informatica, SAP, IBM, Oracle, etc.)
Course Study Options
In-Person Training
12 Locations in Middle East. View
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