Data governance
What does data governance cover in AI governance?
4 competencies are filed under it: Data governance operating model and stewardship, Data lineage and provenance, Data quality rules and monitoring, Data classification, access and retention. Each has its own page saying what it means in practice.
The competencies filed under it
- Data governance operating model and stewardship
Establishes ownership, stewardship, councils, decision rights and issue workflows so data has a named owner and a defined meaning.
Data and Privacy
- Data lineage and provenance
Traces where data came from, what transformed it, who owns each hop and where it flows downstream, so a number can be defended.
Data and Privacy
- Data quality rules and monitoring
Profiles data, sets rules and thresholds, monitors, assigns issues to owners, and knows when data is not fit to train or run a model.
Data and Privacy
- Data classification, access and retention
Classifies information, applies least privilege, sets retention and acceptable-use rules, and controls what may enter a prompt, a log or an embedding.
Data and Privacy
Roles that ask for it
- Data Governance Lead4 of 4 competencies
- Chief Data Officer, data leadership edition4 of 4 competencies
- Privacy Analyst2 of 4 competencies
- AI Privacy Engineer2 of 4 competencies
- Third-Party AI Risk Analyst1 of 4 competency
- AI Auditor1 of 4 competency
- AI Governance Engineer1 of 4 competency
- AI Model Validator1 of 4 competency
- Security Compliance Manager1 of 4 competency
- Third-Party Cyber Risk Manager1 of 4 competency
- AI Security Architect1 of 4 competency
- Chief Information Officer, technology leadership edition1 of 4 competency
- Chief Privacy Officer, AI privacy edition1 of 4 competency
Where it is taught and graded
62 graded topics, each passed by explaining it back. The first module of every program is free with a free account.
- Module 0: Taking the Data Chair (1)
- Module 1: The Estate Survey (3)
- Module 2: Quality as Physics (3)
- Module 3: Consent, Purpose, and the Law of Data (2)
- Module 4: Feeding the Machines (4)
- Module 6: Access and the Keys (3)
- Module 7: The Catalog That Lives (3)
- Module 8: Lineage Under Audit (2)
- Module 9: The Money of Data (2)
- Module 11: Data Incidents (2)
- Module 12: Adversarial Data Governance (1)
- Module 0: Your First Week in Governance, Risk and Compliance (1)
- Module 9: Policy, Standards, Procedures, and Exceptions (1)
- Module 10: Privacy and Data Governance (7)
- Module 11: Cybersecurity Governance and Operational Resilience (2)
- Module 18: Governance, Risk and Compliance Technology, Automation, and Evidence Engineering (2)
- Module 2: Data Reality (5)
- Module 5: The EU AI Act: The Executive Map (1)
- Module 7: Agents Under Command (1)
- Module 10: Evidence Engineering (2)
- Module 3: Generative AI Compliance (2)
- Module 5: Data Security for AI (3)
- Module 0: Taking the Controls (1)
- Module 4: Meaningful Human Accountability (1)
- Module 7: Advanced AI Literacy (1)
- Module 10: AI Security Fundamentals (1)
- Module 3: Diagnose the Organization (1)
- Module 16: Lab: Regional and Geopolitical AI (1)
- EU AI Act Implementation Expert2 topics
- Module 3: High-Risk AI Requirements: The Technical File (2)
- Module 2: AI for Lobbying Productivity (1)
Questions
- What does data governance cover in AI governance?
- 4 competencies are filed under it: Data governance operating model and stewardship, Data lineage and provenance, Data quality rules and monitoring, Data classification, access and retention. Each has its own page saying what it means in practice.
- Which roles ask for data governance?
- 13 roles on the map name at least one of its competencies, from analyst seats to executive ones. Each role page lists the depth expected.
- Where is data governance taught and graded?
- 62 graded topics teach it across 9 programs. Each topic is graded by explaining it back against its own transcript, so a pass is evidence, not attendance. The first module of every program is free with a free account.