IBM-CMMI Data Governance Maturity Model Sub Domains

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  • Data Risk Management & Compliance: The methodology by which risks are identified, qualified, and quantified, avoided, accepted, mitigated or transferred out.
  • Value Creation: The process by which data assets are qualified and quantified to enable the business to maximize the value created by data assets.
  • Organizational Structures & Awareness: Description of the level of mutual responsibility between the business and IT, and the recognition of the fiduciary responsibility to govern data at different levels of management.
  • Policy: A description of the desired organizational behavior(s).
  • Stewardship: A quality control discipline designed to ensure custodial care of data for asset enhancement, risk management, and organizational control.
  • Data Quality Management: Methods to measure, improve and certify the quality and integrity of production, test and archival data.
  • Information Lifecycle Management: A systematic policy-based approach to information collection, use, retention, and deletion.
  • Information Security & Privacy: The policies, practices and controls used by the organization to mitigate risk and protect data assets.
  • Data Architecture: The architectural design of structured and unstructured data systems and applications that enable data availability and distribution to appropriate users.
  • Classification & Metadata: The methods and tools used to create common semantic definitions for business and IT terms, data models, data types, and repositories. Metadata that bridge human and computer understanding.
  • Audit Information, Logging & Reporting: The organizational processes for monitoring and measuring the data value, risks, and efficacy of governance.

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