Data Governance & Management with DAMA-DMBOK: From Frameworks to Practical Implementation

Course Category : Data Management

A comprehensive, practice-oriented program that transforms data governance and management principles into actionable organizational practices—from roles, policies, data quality, and metadata to maturity assessment and the development of a practical governance roadmap.
10 Days – Foundational to Intermediate

Introduction

Data has become one of the most valuable organizational assets, and governing it is no longer solely a technical responsibility. Effective data governance requires clear ownership and accountability, robust policies and standards, systematic quality management, effective metadata practices, and measurable governance maturity.

This program provides a practical and integrated introduction to data governance and data management, drawing on professional principles and practices associated with the DAMA-DMBOK framework while emphasizing the translation of concepts into operating models and actionable organizational practices.

The program progresses from data management fundamentals and governance frameworks to operating model design, data ownership and stewardship, data quality, metadata and data catalogues, policies and standards, governance implementation, maturity assessment, and roadmap development.

Learning is highly interactive and application-focused through case studies, workshops, group exercises, and realistic organizational scenarios, with limited emphasis on coding or highly technical topics..

Targeted Audience

Data Governance Specialists and Officers
Data Management Specialists
Data Stewards and Data Owners
Data Quality Professionals
Data Management and Governance Office Professionals
Metadata and Data Catalogue Specialists
Data Policy and Standards Professionals
Business and Data Analysts involved in governance initiatives
Digital Transformation and Organizational Excellence Professionals involved in data management
Professionals seeking foundational-to-intermediate knowledge of data governance and management

Targeted Skills

Apply DAMA-DMBOK principles within practical organizational contexts
Analyze and design data governance frameworks and operating models
Define data ownership, stewardship, and accountability
Develop data policies, standards, and procedures
Apply data quality measurement and improvement methodologies
Organize and manage metadata and business glossaries
Utilize data catalogues to support discovery, understanding, and governance
Assess data governance and management maturity
Design governance KPIs and monitoring mechanisms
Develop practical data governance implementation roadmaps

Expected Outcomes

By the end of this program, participants will be able to

Explain the core components of data management and governance and their relationship to DAMA-DMBOK.
Select and design governance and operating models appropriate to organizational needs.
Define data roles, responsibilities, accountability, and decision rights.
Develop practical data policies, standards, and procedures.
Apply a structured approach to identifying, measuring, and resolving data quality issues.
Establish effective metadata, business glossary, and data catalogue practices.
Assess data governance maturity and identify gaps and priorities.
Develop an integrated roadmap for implementing, monitoring, and continuously improving data governance.

Training Topics Index

Data as an organizational asset and its value to business and decision-making
Fundamental concepts of data management and governance
Integrated overview of DAMA-DMBOK knowledge areas
Data lifecycle and its relationship to management and governance practices
Relationship between data management, governance, and organizational strategy

• Practical exercise

Mapping the data lifecycle within a sample organization

Definition, objectives, and core principles of data governance
Distinguishing Data Governance from Data Management
Overview of common governance models and frameworks
Components of an enterprise data governance framework
Accountability, transparency, and decision-making principles

• Case study

Analyzing a governance model and identifying strengths and gaps

Understanding the Data Governance Operating Model
Centralized, decentralized, and federated models
Data governance councils, committees, and offices
Decision rights and escalation mechanisms
Designing governance workflows and stakeholder interactions

• Workshop

Designing a data governance operating model

Understanding Data Ownership and its importance
Data Owner roles and responsibilities
Data Steward responsibilities and stewardship models
Data Custodian and supporting roles
Designing a data RACI matrix

• Group exercise

Resolving overlapping ownership and accountability scenarios

Hierarchy of policies, standards, procedures, and guidelines
Core principles for developing Data Policies
Translating governance requirements into actionable standards
Policy lifecycle, review, and approval
Compliance monitoring and exception management

• Workshop

Developing a policy, standard, and procedure for a practical scenario

Core data quality concepts and dimensions
Identifying Critical Data Elements
Developing Data Quality Rules
Measuring quality through metrics and thresholds
Root cause analysis of data quality issues
Issue management and remediation planning

• Workshop

Building a data quality scorecard for a realistic scenario

Metadata concepts and categories
Business, Technical, and Operational Metadata
Developing and maintaining a Business Glossary
Standardizing organizational terminology and definitions
Relationship between metadata, governance, and quality
Introduction to Data Lineage and its governance value

• Workshop

Building a simplified business glossary and metadata model

Understanding Data Catalogues and their role in governance
Core components and capabilities of a data catalogue
Organizing and classifying data assets
Data search, discovery, and contextual understanding
Connecting catalogues with ownership, quality, and metadata
Business and governance criteria for evaluating Data Catalogue solutions

• Practical exercise

Designing an initial enterprise data catalogue structure

Moving from governance design to implementation
Defining governance scope and implementation priorities
Stakeholder mapping and engagement
Developing the business case for data governance
Change management, communication, and data culture
Critical success factors and common implementation challenges

• Case study

Addressing governance implementation challenges in a large organization

Understanding Data Governance Maturity
Maturity assessment dimensions and levels
Conducting gap assessments and prioritization
Developing governance KPIs and compliance indicators
Identifying Quick Wins and strategic initiatives
Developing a phased data governance roadmap

• Final workshop

Assessing organizational maturity and developing a Data Governance Roadmap

Course Features

Updated and Interactive Content
Hypothetical Examples and Case Studies
Pre- and Post-assessments to Measure Impact
Verified Certificate with a QR Verification Code

Data Governance & Management with DAMA-DMBOK: From Frameworks to Practical Implementation