Agentic AI Data Governance

An Agentic AI Data Governance is a data governance framework that manages data lifecycle, privacy controls, and compliance requirements specifically for agentic ai system training, operation, and storage.

• AKA: AI Agent Data Management Framework, Agentic System Data Governance, AI Agent Information Governance.
• Context:
  • It can typically implement Agentic AI Data Governance Private Data Protection ensuring agentic ai data governance sensitive information never enters agentic ai data governance git history, agentic ai data governance issue trackers, or agentic ai data governance workflow logs.
  • It can typically establish Agentic AI Data Governance Dataset Versioning using agentic ai data governance dvc or agentic ai data governance git lfs to track agentic ai data governance large artifacts while maintaining agentic ai data governance pointer references in agentic ai data governance repositorys.
  • It can typically provide Agentic AI Data Governance Retention Policy enforcing agentic ai data governance data lifecycle rules, agentic ai data governance automatic deletion, and agentic ai data governance compliance timelines.
  • It can typically enforce Agentic AI Data Governance Access Classification categorizing agentic ai data governance data sensitivity, agentic ai data governance usage restrictions, and agentic ai data governance handling requirements.
  • It can often enable Agentic AI Data Governance Lineage Tracking monitoring agentic ai data governance data flow, agentic ai data governance transformation pipelines, and agentic ai data governance usage patterns across agentic ai data governance agent systems.
  • It can often integrate Agentic AI Data Governance Privacy Controls for agentic ai data governance pii protection, agentic ai data governance anonymization, and agentic ai data governance consent management.
  • It can range from being a Simple Agentic AI Data Governance to being a Complex Agentic AI Data Governance, depending on its agentic ai data governance data complexity.
  • It can range from being a Development Agentic AI Data Governance to being a Production Agentic AI Data Governance, depending on its agentic ai data governance operational requirement.
  • ...
• Examples:
  • Agentic AI Data Governance Storage Patterns, such as:
    • Agentic AI Data Governance External Storage keeping agentic ai data governance raw data in agentic ai data governance secure object stores with agentic ai data governance pointer references in agentic ai data governance version control.
    • Agentic AI Data Governance Encrypted Storage protecting agentic ai data governance sensitive datasets with agentic ai data governance encryption at rest and agentic ai data governance access control.
    • Agentic AI Data Governance Federated Storage distributing agentic ai data governance datasets across agentic ai data governance multiple locations for agentic ai data governance compliance and agentic ai data governance performance.
  • Agentic AI Data Governance Classification Systems, such as:
    • Agentic AI Data Governance Public Data allowing agentic ai data governance open access and agentic ai data governance unrestricted usage.
    • Agentic AI Data Governance Internal Data restricting agentic ai data governance organization access with agentic ai data governance usage monitoring.
    • Agentic AI Data Governance Confidential Data requiring agentic ai data governance strict access control and agentic ai data governance audit trails.
  • Agentic AI Data Governance Compliance Frameworks, such as:
    • Agentic AI Data Governance GDPR Compliance implementing agentic ai data governance right to erasure and agentic ai data governance data portability.
    • Agentic AI Data Governance HIPAA Compliance ensuring agentic ai data governance healthcare data protection and agentic ai data governance audit requirements.
  • ...
• Counter-Examples:
  • Traditional Data Governance, which lacks AI-specific considerations and agentic system requirements.
  • Database Management System, which provides data storage rather than comprehensive governance frameworks.
  • Data Warehouse Governance, which focuses on analytical data rather than AI training and operational data.
• See: Data Governance, AI Data Management, Agentic AI Security Framework, AI System Privacy Framework.

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