Module 1 – Data Management Foundations

01 – Business Drivers for Data Management
02 – Core Concepts: Data, Information, Principles & Challenges
03 – Data as a Strategic Enterprise Asset
04 – Data Management Strategy & Operating Vision
05 – Frameworks Overview & the DMBOK Pyramid

Module 2 – Data Ethics & Responsible Data Use

06 – Business Drivers for Ethical Data Management
07 – Ethical Principles in Data Usage
08 – Foundations of Data Privacy & Protection Laws
09 – Risks & Impacts of Unethical Data Practices
10 – Building an Ethical, Data-Driven Culture
11 – Integrating Data Ethics with Governance

Module 3 – Data Governance

12 – Data Governance Overview: Drivers, Objectives & Value
13 – Core Principles of Effective Data Governance
14 – Governance Readiness & Maturity Assessment
15 – Policies, Standards, Stewardship & Accountability
16 – Embedding Governance into Business Operations
17 – Issue, Exception & Change Management
18 – Governance Tools, Techniques & KPIs
19 – Governing the Data Governance Function

Module 4 – Data Architecture

20 – Business & Technology Drivers
21 – Architecture Goals, Outcomes & Best Practices
22 – Architecture Activities & Key Deliverables
23 – Alignment with Enterprise Architecture (EA)
24 – Architecture Tools & Techniques
25 – Implementation & Transition Guidelines
26 – Architecture Governance & Metrics

Module 5 – Data Modeling & Design

27 – Objectives of Data Modeling
28 – Conceptual, Logical & Physical Modeling Concepts
29 – Modeling Lifecycle: Plan, Build, Review & Maintain
30 – Modeling, Metadata & Lineage Tools
31 – Design Standards & Best Practices
32 – Version Control & Model Governance
33 – Metrics & Alignment with Data Governance

Module 6 – Data Storage & Operations

34 – Overview: Drivers, Scope & Objectives
35 – Data Storage Concepts & Structures
36 – Database Technologies & Administration
37 – Operational Management & Monitoring
38 – Tools & Operational Techniques
39 – Implementation & Optimization Guidelines
40 – Storage Governance & Performance Metrics

Module 7 – Data Security

41 – Security Drivers & Threat Landscape
42 – Security Goals, Concepts & Controls
43 – Security Policies & Regulatory Requirements
44 – Access Control, Encryption & Data Protection
45 – Auditing, Logging & Continuous Monitoring
46 – Secure Implementation Practices
47 – Security Governance & Risk Metrics

Module 8 – Data Integration & Interoperability

48 – Integration Drivers & Business Needs
49 – Integration Concepts & Target Outcomes
50 – Integration Planning & Analysis
51 – Design & Development of Integration Pipelines
52 – Implementation, Testing & Monitoring
53 – Tools & Techniques: ETL, ELT, ESB & Virtualization
54 – Integration Governance & Metrics

Module 9 – Document & Content Management

55 – Content Management Drivers
56 – ECM Concepts & Information Lifecycle
57 – Content Lifecycle Planning
58 – Content Lifecycle Execution & Control
59 – Publishing, Access & Delivery
60 – Tools & Techniques: ECM, Collaboration, e-Discovery
61 – Content Governance & Compliance Metrics

Module 10 – Reference & Master Data Management

62 – MDM & Reference Data Drivers
63 – Core Concepts & Business Value
64 – Master Data Management Architectures
65 – Golden Records, Hierarchies & Survivorship
66 – MDM Tools & Technologies
67 – Implementation & Rollout Guidelines
68 – MDM Governance & Quality Metrics

Module 11 – Data Warehousing & Business Intelligence

69 – BI & Analytics Drivers
70 – DW & BI Concepts
71 – Business Intelligence Needs Assessment
72 – Data Warehouse Architecture Design
73 – Data Development, Loading & Population
74 – Operations, Maintenance & Optimization
75 – BI & DW Tools & Platforms
76 – Analytics Governance & Metrics

Module 12 – Metadata Management

77 – Metadata Drivers & Use Cases
78 – Metadata Concepts & Types
79 – Metadata Strategy & Requirements Definition
80 – Metadata Architecture & Integration
81 – Metadata Creation & Maintenance
82 – Metadata Delivery, Discovery & Consumption
83 – Metadata Tools & Repositories
84 – Metadata Governance & Metrics

Module 13 – Data Quality Management

85 – Data Quality Drivers & Business Impact
86 – Data Quality Dimensions & Concepts
87 – Defining & Measuring High-Quality Data
88 – Data Quality Assessment Techniques
89 – Data Cleansing & Improvement Processes
90 – Operationalizing Data Quality
91 – Data Quality Tools & Automation
92 – Quality Governance & Performance Metrics

Module 14 – Big Data & Data Science

93 – Big Data & Advanced Analytics Drivers
94 – Big Data Principles & Architectures
95 – Big Data Strategy & Use-Case Prioritization
96 – Data Ingestion, Processing & Pipelines
97 – Analytics, Modeling & Hypothesis Testing
98 – Deployment, Monitoring & Scaling
99 – Tools & Platforms: MPP, Distributed DBs & Visualization
100 – Big Data Governance & Metrics

Module 15 – Data Management Maturity Assessment

101 – Maturity Assessment Drivers
102 – Maturity Models & Concepts
103 – Assessment Planning & Scope Definition
104 – Execution of the Maturity Assessment
105 – Results Interpretation & Gap Analysis
106 – Improvement Roadmap & Action Planning
107 – Reassessment, Benchmarking & Continuous Improvement
108 – Assessment Governance & Metrics

Module 16 – Data Management Organization & Roles

109 – Data Management Organizational Overview
110 – Culture, Behavior & Operating Norms
111 – Operating Models: Centralized, Federated & Hybrid
112 – Critical Success Factors
113 – Building & Scaling the DM Organization
114 – Roles, Responsibilities & Skills
115 – Interaction with CDO, DG & EA Functions
116 – Organizational Governance & Metrics

Module 17 – Data Management & Change Management

117 – Change Management Overview for Data Programs
118 – Laws & Dynamics of Change
119 – Managing Transition vs. Organizational Change
120 – Kotter’s 8 Common Change Failures
121 – Kotter’s 8-Step Change Framework
122 – Sustaining Adoption & Behavioral Change
123 – Communicating Data Management Value
124 – Change Governance & Success Metrics

Module 18 – CDMP Exam Guide & Capstone Review

125 – Consolidated Review, Key Concepts, Practice Guidance & Exam Strategy

Appendix 1A – Strategic Alignment Model (SAM)

Appendix 1B – Amsterdam Information Model (AIM)

Appendix 1C – DAMA-DMBOK Framework Overview

Appendix 1D – The DMBOK Pyramid (Aiken)

Appendix 1E – DAMA Data Management Framework (Evolved – Sue Geuens)

Appendix 1F – DAMA and the DMBOK Relationship

Appendix 1G – DAMA Wheel (Evolved)