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

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

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.

Starts On

19 - October - 2026

Ends On

30 - October - 2026

Location

Spain - Barcelona

Language

English

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View Course Introductory PDF

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