TDWI Data Governance Fundamentals: Managing Data as an Asset Training in Hong Kong

There are no prerequisites for this course.

Data quality and data governance professionals; BI/DW managers, architects, designers, and developers; data stewards, data architects, and data administrators; anyone with a role in data governance or data quality management

• Definitions and dimensions of data governance
• Key considerations and challenges in building a data governance program
• The practices, roles, skills, and disciplines essential to data governance
• The qualities that make good data stewards and stewardship organizations
• The processes of developing, executing, and sustaining data governance
• Activities, issues, and options when building a data governance program
• How maturity models are applied for data governance
• The importance of adapting data governance for trends such as big data, cloud services, and agile development methods

• Module One: Data Governance Concepts 
• Defining Data Governance
  • Governance defined
  • Applying governance to data
  • The data-to-value chain
  • Governance through the information lifecycle
  • Why govern data?
• Dimensions of Data Governance
  • People – organizations and individuals
  • Processes – defining, creating, and using data
  • Goals – quality, standardization, consolidation, compliance, usefulness
  • Constraints – standards, policies, procedures, rules, regulations, controls
• Data Governance Challenges
  • What data to govern?
  • Who governs data?
  • Where, when, and how to get started?
  • How to fund data governance? How to staff data governance?
• Fostering Participation
  • Participation and resistance
  • Awareness
  • Perception of value
  • Providing services
• Module Two: Data Governance Organizations
• Positioning Data Governance in the Enterprise
  • Connecting business strategy, information management programs, and data governance
• Governance and Management Practices
  • Responsibility, accountability, & authority
  • Decision rights
  • Horizontal management in vertical organizations
• Data Governance Roles
  • Data Ownership
  • Data Stewardship
  • Data Custodianship
  • Stakeholders
• Data Governance Skills and Disciplines
  • Data architecture
  • Data definition
  • Metadata management
  • Issue resolution
• Module Three: Data Stewardship
• Stewardship Concepts
  • Responsibilities and accountabilities
  • Goals, purpose, and results
• Stewardship Organizations
  • Kinds of data stewards
  • Stewardship and data domains
  • Councils, committees, and other organizational structures
• Stewardship Skills and Knowledge
  • People skills – communication, facilitation, consensus building, etc.
  • Data skills – definition, naming, modeling, etc.
  • Business knowledge – business domain, data domain, rules, regulations, etc.
  • Governance knowledge – goals, standards, processes, procedures, etc.
• Module Four: Data Governance Processes
• Governance and Management
  • The processes of governing data
• Data Management Processes
  • Stewardship of data
• Program Development Processes
  • Policy alignment
  • Establishing decision rights
  • Designating accountabilities and responsibilities
  • Defining goals and measures
• Program Operation Processes
  • Stakeholder support
  • Communication and training
  • Measurement and monitoring
  • Technology alignment
• Program Sustaining Processes
  • Scope and priorities management
  • Issues management
• Program Growth Processes
  • Change management
  • Capabilities development
• Module Five: Building a Data Governance Program
• Getting Started
  • Where to begin?
  • How much data?
  • How much governance?
  • What do you already have?
  • Top-down or bottom-up?
• Planning & Preparation
  • The business case
  • Program charter
• Building the Team
  • Organizational structure
  • Participants & roles
  • Responsibilities & accountabilities
  • Communication & coordination
• Building the Infrastructure
  • Technology – metadata, wikis, portals, etc.
  • Standards – for processes, documents, deliverables, etc.
  • Services – for data providers, for data consumers, for system developers, etc.
• Executing Governance
  • Program execution
  • Planning and executing projects
  • Supporting projects
  • Day-to-day governance
• Module Six: Evolving Data Governance
• Modernizing and Maturing Data Governance
  • Responding to change
  • Maturity models
• Cloud Data Governance
  • Changing the data governance landscape
  • Data security and privacy in the cloud
  • Governance considerations
• Big Data Governance
  • Big data sources
  • Governance considerations
• Agile Data Governance
  • Agile teams
  • Agile considerations
  • Governing with agility
• Module Seven: Summary and Conclusion
  • Summary of Key Points
  • References & Resources
  • Appendix A: Bibliography and References
  • Appendix B: Tools and Templates
    • Data Governance Motivations (Assessment)
    • Decision Rights (Template)
    • Data Stewardship Needs (Assessment)
    • Data Stewardship Skills (Assessment)
    • Stakeholder Census (Assessment)
    • Data Governance Program Charter (Template)