Course Code: dmbk2
Duration: 21 hours
Prerequisites:
  • CDMP Fundamentals
Overview:

The course covers Data Governance within the DAMA Body of Knowledge (DMBoK®) in depth. It looks at why Data Governance is central to successful Data Management, roles and responsibilities, drivers and issues, reference models, organizational structures, and principles. It also discusses the role of the Data Governance Office and how to get started with Data Governance. Lastly, it covers the topic of Data Ethics, the information lifecycle, the importance of data for organizations, how Data Governance and Data Quality are linked, benefits and implications, and so much more.

Purpose

To understand the importance, position, and role of Data Governance for organizations and data professionals.

Outcome

  • Understand the many facets of Data Governance
  • Explore various Data Governance roles in organizations
  • Discuss drivers, benefits, and issues around effective governance
  • Understand how Data Governance is linked to other data disciplines
Course Outline:
  • Data Governance (Including Data Ethics)
    • Data Governance within the DAMA DMBoK Wheel
    • Business Drivers of Data Governance and Stewardship
  • What is Data Governance?
    • Defining Data Governance as a Quality Control Discipline
    • The Management of Data Assets
    • Core Data Management Functions
  • Drivers and Issues
    • Why is Data Governance Critical?
    • Understanding Information Management Disciplines
    • Motivations and Behaviors for Data Governance
    • The Impact of Poor Data Governance
  • Information Lifecycle and Data Governance
    • Information Lifecycle and Systems Development Lifecycle (SDLC)
    • What is the Information Lifecycle?
    • Information Lifecycle Activities
    • What Can and Can’t Data Governance or CDO Address?
    • Driving Key Business Decisions with Data
    • The Interdependencies of Data Quality and Data Governance
  • Data Governance Components
    • The Data Governance Framework (Simplified)
    • Data Governance Readiness
    • Considerations for Setting Data Governance Scope
    • Implementation Approaches for Data Governance
  • Data Governance Benefits and Implications
    • Taxonomy of Principles
    • Data Management Principles
    • Data is an Enterprise Asset
    • Benefits of Data Governance
    • Why Do Data Governance Initiatives Fail?
    • Typical Roles and Responsibilities of Data Governance
    • Understanding an Organization Structure of Data Governance
    • Data Management Organizations (DMBoK)
    • Typical Organization Structures
      • Data Governance Council
      • Data Governance Groups
      • Data Quality Organization
      • Data Working Groups
      • Data Governance Office
    • Data Governance Activities (DMBoK)
    • Data Governance as a Program
    • Communication is Critical
    • Guiding Principles of Data Management
    • Defining a Roadmap
    • Components of the Data Governance Framework
    • Essential Early Step: Maturity Assessment
    • Environmental Factors: People Capabilities
    • Architecture and Design Roles within the Data Management Family
    • Skills and Competencies of Enterprise Architecture
    • What is a Skills Framework Used For?
    • Shared Responsibilities of Data Governance
    • Organizational Models for Data Governance
    • Operating Models
      • Centralized
      • Decentralized
      • Hybrid
      • Federated
      • Self-Organizing Teams
    • Organization and People
    • Data Governance Metrics
    • Reporting and Assurance
  • Summary
    • Key Messages
    • Who Should Have Access to Data?
    • Ethical Risks in a Sampling Project
  • Wrap Up
    • Key Takeaways