TDWI Data Governance Innovations: Adapting for Agile, Big Data, and Cloud Training

  • Learn via: Classroom / Virtual Classroom / Online
  • Duration: 1 Day
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  • We can host this training at your preferred location. Contact us!

Rapid increases in data variety and data management practices challenge the old model of policy- and enforcement-based data governance. Cloud services bring new issues that go well beyond the obvious concerns of security and privacy. Big data implementation brings substantial changes to the scope and complexity of governance. Many ask if governance and agile can coexist. The answer must be "yes," but making them work together is especially challenging.

Cloud services, big data, and agile BI are here to stay. Data governance programs must modernize and adapt to these realities. A fundamental culture change from control-oriented governance to collaboration is at the core of modern data governance—shifting from enforcement to prevention and intervention as the means to assure data security, privacy, compliance, quality, and value. Beyond cultural change, every data governance participant needs to understand the new issues and the new opportunities that arise from current trends in data management.

There are no prerequisites for this course.

Data quality and data governance professionals; CIOs, business leaders, and IT executives facing the realities of agile, big data, or cloud services; mangers, architects, designers, and developers of BI, MDM, and data warehousing systems; data stewards, data architects, and data administrators; anyone with a role in data governance or data quality management; anyone needing to modernize a data governance program for agile BI, big data, or cloud services

  • The data governance challenges and opportunities that arise from cloud services
  • Risks, challenges, and opportunities of big data governance
  • How to overcome apparent conflicts between data governance and agile
  • Roles, relationships, and complexities of metadata management for data governance
  • Data governance challenges that arise from mobile devices and from social media
  • The importance of ethics as a data governance imperative
  • New models, practices, and processes for modern data governance

Module 1: The Current State of Data Governance

  • Current Definitions: Assets, Management, and Policies
  • Current Focus
    • Decision Rights
    • Policy and Enforcement
  • Current Organizations
    • Organization Structure
    • Roles
  • Current Processes
    • Policy Making
    • Issue Resolution and Change Control
  • Why Data Governance Innovations
    • Driving Forces
    • Evolving Definition and Purpose
    • From Decision Rights to Decision Models
    • From Enforcement to Prevention
    • From Bureaucracy to Flexibility
    • From Rigor to Agility
  • Areas of Innovation: From Current State to Future State

Module 2: Agile Data Governance

  • Agile Development
    • Agile Process and Values
    • Test-Driven Development
  • Agile Teams: Two Levels
  • Agile Projects
    • Agile Projects and Governance Goals
    • Agile Projects and Data Stewardship
    • Agile Projects and Data Governance Services
  • Agile Culture
    • Agile Culture and Governance Roles
    • Agile Culture and Decision Processes
  • Agile Governance: Governing with Agility

Module 3: Big Data Governance

  • Big Data Basics
    • Big Data Defined
    • Big Data Sources
    • Big Data Characteristics
    • Data Governance Needs
  • Big Data and Governance Goals
    • Security and Privacy
    • Quality
    • Compliance
    • Integration
    • Metadata
    • Retention and Disposal
    • Value and Risk

Module 4: Cloud Data Governance

  • Cloud Data Basics
    • Data Options in the Cloud
    • Changing the Data Governance Landscape
  • Cloud Data and Data Governance Goals
    • Security and Privacy
    • Quality
    • Compliance
    • Integration
    • Disaster Recovery
    • Data Asset Value
  • Migrating to the Cloud: Data Governance Roles

Module 5: Metadata and Governance

  • Metadata Basics
    • Metadata Defined
    • Purposes of Metadata
    • Metadata Benefits
    • Metadata and Data Lifecycles
  • Metadata Types
    • The Scope of Metadata
    • Business Metadata
    • Design Metadata
    • Implementation Metadata
    • Operations Metadata
  • Metadata Processes: Metadata Management Activities
  • Metadata Challenges
    • Metadata Management Issues
    • Metadata Disparity and Disintegration
    • Big Data and Metadata
    • Cloud Data and Metadata
  • Metadata Governance: Governance for Metadata

Module 6: Ethics, Social, Mobile and Governance

  • Ethics and Data Governance
    • Why Ethics Matters
    • Data and Ethics
    • BI and Ethics
    • Managing Ethics in Business
  • Mobile Technology and Data Governance
    • Governance Risks
    • Governance Opportunities
  • Social Media and Data Governance
    • Governance Risks
    • Governance Opportunities

Module 7: Contemporary Governance Techniques

  • Data Governance Zones: Data Variety and Pragmatic Governance
  • Flat Governance Organizations
    • Simplify for Agility
    • Embedded Governance
  • BI for Governance
    • Applying BI Concepts for Data Governance
    • Measuring and Monitoring Governance
  • Technology for Governance: Opportunities and Applications

Module 8: Summary and Conclusion

  • Summary of Key Points: A Quick Review
  • References and Resources: To Learn More


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