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IoT and Data Governance
Ray Henry
Department of Information Systems
Cleveland State University
Governance
• Ensures that stakeholder needs, conditions and options
are evaluated to determine balanced, agreed-on
enterprise objectives to be achieved
– setting direction
– prioritization
– decision making
– monitoring performance and compliance
Data Governance
Decision rights and accountability for
information/data assets
Corporate Governance
IT Governance
Data Governance
Governance Enablers
• Processes
• Organizational Structure
• Culture, Ethics, and Behavior
• Resources
Domains of Data
Governance
Data Principles
Role of data as an asset
Data Quality
Requirements for data
quality
Data Lifecycle
Retention and
retirement
Meta Data
Semantics and data definition
Data Access
Requirements for data access and
security
Asking the Right
Questions
• Who owns the data?
• How do we ensure data quality, discovery, usability and security for the
many different teams and business units that create, use and manage the
data?
• What are the key business questions and goals that are driving what data
we collect and use?
• How do we manage ad hoc data analytics? Do we restrict it or encourage
it?
IoT Data Governance
Pitfalls
• Not considering all stakeholders needs
• Underestimating security and privacy implications
• Too much or too little control
Questions?
Thank you!

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IoT and Data Governance

  • 1. IoT and Data Governance Ray Henry Department of Information Systems Cleveland State University
  • 2.
  • 3.
  • 4. Governance • Ensures that stakeholder needs, conditions and options are evaluated to determine balanced, agreed-on enterprise objectives to be achieved – setting direction – prioritization – decision making – monitoring performance and compliance
  • 5. Data Governance Decision rights and accountability for information/data assets
  • 7. Governance Enablers • Processes • Organizational Structure • Culture, Ethics, and Behavior • Resources
  • 8. Domains of Data Governance Data Principles Role of data as an asset Data Quality Requirements for data quality Data Lifecycle Retention and retirement Meta Data Semantics and data definition Data Access Requirements for data access and security
  • 9. Asking the Right Questions • Who owns the data? • How do we ensure data quality, discovery, usability and security for the many different teams and business units that create, use and manage the data? • What are the key business questions and goals that are driving what data we collect and use? • How do we manage ad hoc data analytics? Do we restrict it or encourage it?
  • 10. IoT Data Governance Pitfalls • Not considering all stakeholders needs • Underestimating security and privacy implications • Too much or too little control