MDMS0: DMBOK and CDMP Preparation: Master and Reference Data Management Specialist Learning Plan
In the four-course DMBOK and CDMP Preparation: Master and Reference Data Specialist Learning Plan, instructor Christopher Bradley provides a comprehensive foundation in master and reference data management, along with the knowledge, methods, and techniques required to analyze, mature and implement master and reference data management solutions. Delving into the distinctions between master and reference data, and the critical role these data types play in organizations, the curriculum covers essential topics like master data management (MDM) architecture, components, and benefits, as well as the relationship of MDM/RDM to other data disciplines, such as data quality, data governance, and data modeling - preparing participants to tackle real-world data challenges and excel in managing any organization's information assets.
Today’s organizations are compelled by the data-centric landscape to identify, manage, and leverage shared data effectively. Given that accurate, consistent, and accessible data is essential for informed decision-making, efficient operations, and competitive advantage, master and reference data management is the cornerstone of any data-driven organization. This training conveys a deep understanding of its importance, various architectural approaches, and practical and effective implementation strategies that align efforts with broader data governance and data quality initiatives.
In the four-course DMBOK and CDMP Preparation: Master and Reference Data Specialist Learning Plan, instructor Christopher Bradley provides a comprehensive foundation in master and reference data management, along with the knowledge, methods, and techniques required to analyze, mature and implement master and reference data management solutions. Delving into the distinctions between master and reference data and the critical role these data types play in organizations, the curriculum covers essential topics like master data management (MDM) architecture, components, and benefits, as well as the relationship of MDM/RDM to other data disciplines, such as data quality, data governance, and data modeling, preparing participants to tackle real-world data challenges and excel in managing any organization's information assets.
The training presents methods and practices for addressing key master and reference data challenges. It is grounded in the industry standard DAMA International Data Management Body of Knowledge (DMBOK).
The training also prepares attendees to take the Certified Data Management Professional (CDMP) Master and Reference Data Specialist exam that is necessary for the attainment of the Practitioner and Master levels. The DAMA International-endorsed learning plan was developed with DAMA International, DATAVERSITY, and Christopher Bradley - DAMA’s former VP of Professional Development.
CDMP Specialist Exam Preparation Information:
- Understand the in-depth information required for the CDMP Master and Reference Data Specialist exam
- Throughout the course, practice by taking sample questions in each section
- There is a comprehensive practice test at the end of Course 4, each of the other courses have shorter content-based review tests
Learning Plan Outcomes:
- Understand the differences between master and reference data
- Learn about the need for and the application of master data management (MDM) approaches for different categories of challenges
- Understand the different business drivers for master and reference data management
- Understand the linkage between master data management with data modeling, data quality, and data governance
- Learn how to identify what data should be mastered in across the enterprise
- Discover four generic MDM architectures and their suitability in different cases
- Understand how to undertake a master data management maturity assessment to consider business procedures for master data management and the provision and appropriateness of MDM solutions per major data subject area.
Who Should Take This Learning Plan?
This learning plan is intended for business and IT professionals at all levels who have been charged with investigating or implementing master and reference data management in their organizations and who seek to gain an overview of the different disciplines of data and information management. It is also a preparation course for people wishing to take the CDMP Master and Reference Data Management Specialist exam, and much of the material focuses on the necessary skills to pass that exam.
It does assume general business knowledge, but not specific technical knowledge or experience. It is appropriate for executives, departmental and/or project managers, data and enterprise architects, consultants, data modelers, BI and data warehouse developers, data and business analysts, DBAs, technical staff, and anyone else interested and involved in data. The course is not designed for any specific business domain, and as such is applicable to any business function in need of more reliable information, such as finance, manufacturing, human resources, analytics, operations, and more.
Learning Plan Price: $599
Individual Course Price: $199
Learning Plan CEUs: 9.0 hours
Each Course Includes:
- A 82- to 116-minute educational training video
- A 21- to 25-question content-based practice exam
- After Course 4 (the final course in the Learning Plan), there is a 24-question CDMP-style practice exam
- “Check for Understanding” quizzes after each course section
- Presentation slides to assist in studying for the CDMP
- Self-paced and on-demand e-learning
- Unlimited course access
Courses within the DMBOK and CDMP Preparation: Master and Reference Data Specialist Learning Plan:
- CDMP Overview, Master Data Drivers, and Definitions
- What Data to Master, MDM Terms, Data Categories, and Architecture Components
- Architecture Types, Data Matching, Taxonomies and Ontologies, and Implementation
- Keys and MDM, Quality in M/RDM, Metrics, Maturity, Standards, and Best Practices
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Course 1: CDMP Overview, Master Data Drivers, and Definitions
- Master and Reference Data Management - DMBOK and CDMP Specialist Learning Plan - Course Overview
- Course Goals
- Course Outline
- Overview, Definitions, and Exam Coverage
- CDMP - Career Path
- Value of the CDMP
- CDMP Associate
- CDMP Practitioner
- CDMP Master
- CDMP Levels
- CDMP Exam Prices
- Question Bank
- CDMP - Career Path
- Module Breakdown: Master and Reference Data Management
- Data, the DMBOK, and Data Management Disciplines
- Why is Data Management Critical?
- The Problem
- Data is Precious
- Data Management Disciplines (DMBoK 2)
- Environmental Elements
- Data, Information, and Knowledge (Information Value Chain)
- Reference and Master Data Management
- DMBOK 2 Context Diagram for Reference and Master Data Management
- MDM Business Drivers and Exercises
- MDM Business Drivers
- What is Event/Transaction Data?
- About Event Data
- What is Master and Reference Data? What is Master Data Management (MDM)?
- Master Vs. Reference Data Focus
- Reference Vs. Master Data Chart
- Exercise #1
- Exercise #2
- Other MDM/RDM Terms
- Course 1 - Quiz #1
- Quiz #1 Answers
- DMBOK and CDMP Preparation: Master and Reference Data Specialist Learning Plan – Progress Review
Course 2: What Data to Master, MDM Terms, Data Categories, and Architecture Components
- DMBOK and CDMP Preparation: Master and Reference Data Specialist Learning Plan -Course Overview
- Course Goals
- Court Outline
- Module Breakdown: Master and Reference Data Management
- What Data Should be Mastered?
- Where is the Data Used Most?
- Reinventing the Wheel
- MDM/RDM and Enterprise Information Architecture
- Enterprise Information Architecture
- Layers of Data
- Other Views of Reference Data
- Distinction in Financial Services
- What’s the Point?
- Specific Data Governance Tasks Exist for Each Category
- Importance of Reference Data
- More on Attitudes to Reference Data
- What Data Should be Mastered? (Continued)
- Value Chain - What “Things” Are Used?
- Utility Example
- What are the Common/Shared Data “Things?”
- Why Produce a Model?
- Data Governance in the MDM Context Determines
- MDM Readiness (Based on CMMI)
- Assessing MDM Requirements
- MDM Architecture, Terms, and Components
- MDM Architecture
- Example: Customer
- MDM Terms
- Typical MDM Components
- Master Data Environment
- Methods of Moving Data
- Typical MDM Capabilities
- Master Data “Hub”
- Data Integration and Acquisition
- Master Data Services
- Data Delivery
- Access Control
- Synchronization
- Data Quality, Governance, and Operations
- MDM Selection Criteria
- Typical MDM Tools Evaluation Criteria
- Single Domain MD Support
- Multi Domain MD Support
- Flexible Platform Approach to MDM
- Support of Complex Relationships and Hierarchies
- Automatic Generation of Services
- Integrate Data Quality Services
- Support Multiple MDM Architecture Styles
- Track History and Lineage
- Support Analytical and Operational MDM Operation
- Multiple Technology Deployment Modes
- Provide MDM Data Governance
- Metadata Management Capabilities
- MDM Framework
- Typical MDM Tools Evaluation Criteria
- Course 2 - Quiz #1
- Quiz #1 Answers
- DMBOK and CDMP Preparation: Master and Reference Data Specialist Learning Plan - Progress Review
Course 3: Architecture Types, Data Matching, Taxonomies and Ontologies, and Implementation
- DMBOK and CDMP Preparation: Master and Reference Data Specialist Learning Plan -Course Overview
- Course Goals
- Module Breakdown: Master and Reference Data Management
- Course Outline
- Master Data Management (MDM) Architecture Types
- MDM Architecture Types:
- Registry
- Consolidation
- Co-Existence
- Centralized
- Complete DV Master Data View
- Master Data Sharing Architecture (Example)
- Considerations for the Best Approach
- Architecture Style Choices
- MDM Architecture Types:
- MDM Matching
- Master Data Match Rules
- Matching (Example)
- Master Data Matching
- Exact String-Matching Algorithms
- Approximate String-Matching Algorithms
- Uses of String-Matching Algorithms
- Master Data Match Rules
- Taxonomies and Ontologies
- Example Ontologies
- Five Types of Ontologies
- Taxonomies and MDM/RDM
- Single Domain and Multi-Domain MDM
- MDM Implementation
- Implementation: Operational Vs. Analytic MDM
- MDM Implementation
- Key Processing Steps for MDM
- Exercise #1
- Course 3 – Quiz #1
- Quiz #1 Answers
- DMBOK and CDMP Preparation: Master and Reference Data Specialist Learning Plan - Progress Review
Course 4: Keys & MDM, Quality in M/RDM, Metrics, Maturity, Standards, and Best Practices
- DMBOK and CDMP Preparation: Master and Reference Data Specialist Learning Plan – Course Overview
- Course Goals
- Course Outline
- Module Breakdown - Master and Reference Data Management
- Aligning MDM with the Business Program
- Portfolio Vs. Per Project
- Keys and Master Data Management (MDM)
- Identifiers Vs. Primary Keys
- Keys: Differences
- Identifiers and Primary Keys: Examples
- Issues with Surrogate Keys
- Example: South Sudan
- What Surrogate Keys do for the Reference Data
- Store Them All
- Composite Vs. Compound
- Quality in M/RDM
- Quality in Reference Data
- Origins of Issues in Reference Data
- Definition of ALL Required Reference Data Tables
- Correct Level of Abstraction of Reference Data
- Consequences of Problems with Levels of Abstraction of Reference Data
- Resolution of Overlapping Reference Data Values
- Elimination of Gaps in Reference Data Tables
- Elimination of Different Levels of Reference Data
- Concepts Matter - Country May Not be a Country
- Importance of Reference Data
- Quality in Reference Data
- Standards
- Data Values Standards (Some Examples)
- Summary of Reference Data Normalization
- Gresham’s Law
- Quality in MDM/RDM Key Points
- Now: Set Up Governance Processes
- Process and Data Model: Relationship
- Linkages
- Process and Data’s Relation
- Master Data Management (MDM) Maturity
- Master Data Management Maturity
- Exercise #1
- Master Data Lifecycle
- A Case Study
- Statoil MDM Challenges
- Master Data Management Maturity
- Statoil Enterprise Models
- Statoil Enterprise Master Data Model
- Why Produce a Model?
- Understand Corporate Plan
- Catalog Current Initiatives
- Harmonize and Cross Reference with Data Model
- Prioritize by Multiple Criteria
- Prioritize by Interest
- Plan Big - Implement Small
- Metrics, Challenges, Considerations, and Best Practices
- MDM Dashboards
- MDM Challenges and Considerations
- MDM Dashboards
- Conclusions
- Key Points (DMBOK 2)
- Links to Additional Content
- Course 4 – Quiz #1
- Quiz #1 Answers
- After Completing Learning Plan’s Four Quizzes
- DMBOK and CDMP Preparation: Master and Reference Data Specialist Learning Plan – Progress Review
Complete All Four Master and Reference Data Management Specialist Courses
1. MDMS1: CDMP Overview, Master Data Drivers, and Definitions
required
In this course, instructor Christopher Bradley (a CDMP Fellow) lays the groundwork for the entire DMBOK and CDMP Preparation: Master and Reference Data Specialist Learning Plan with a comprehensive overview of the CDMP exam and its levels and exploration of the data management environment, the information value chain, and MDM business drivers. The course further delves into master and reference data concepts, defining MDM/RDM initiatives, their motivations, key terms, focus areas, and illustrative examples. Additionally, the course will prepare participants to take the Certified Data Management Professional (CDMP) Master and Reference Data Specialist exam, which is a prerequisite for attainment of the Practitioner and Master levels.
View Details2. MDMS2: What Data to Master, MDM Terms, Data Categories, and Architecture Components
required
In this course, instructor Christopher Bradley (a CDMP Fellow), offers an in-depth examination of master data management (MDM), encompassing foundational concepts, enterprise information architecture and data layers, and the pivotal role of reference data. With insights into essential topics including data mastering, MDM readiness requirements, and architectural considerations, the course establishes a strong foundation in MDM principles, capabilities, and selection criteria.
View Details3. MDMS3: Architecture Types, Data Matching, Taxonomies and Ontologies, and Implementation
required
In this course, instructor Christopher Bradley (a CDMP Fellow) delves into the diverse architectures of master data management (MDM), exploring beyond the traditional hub model to convey the nuances of master data matching, including rules and algorithms. The course clarifies how to navigate the complexities of taxonomies and ontologies, with practical examples to illustrate their application in MDM and reference data management (RDM), and to differentiate between operational and analytical MDM implementation, culminating in an exercise to solidify the concepts learned.
View Details4. MDMS4: Keys and MDM, Quality in M/RDM, Metrics, Maturity, Standards, and Best Practices
required
Aligning MDM with business objectives, differentiating between portfolio and project approaches and keys and identifiers, addressing data quality issues, and understanding standards and normalization are all fundamental to a successful MDM initiative. In this course, instructor Christopher Bradley (a CDMP Fellow) addresses each of these topics, employing hands-on exercises, a case study, and covering MDM maturity, metrics, and best practices to improve MDM deployment and governance.
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