Data quality
What does data quality cover in AI governance?
1 competency is filed under it: Data quality rules and monitoring. Each has its own page saying what it means in practice.
The competencies filed under it
- 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
Roles that ask for it
- AI Model Validator1 of 1 competency
- Data Governance Lead1 of 1 competency
- Chief Data Officer, data leadership edition1 of 1 competency
Where it is taught and graded
18 graded topics, each passed by explaining it back. The first module of every program is free with a free account.
- Module 2: Quality as Physics (3)
- Module 4: Feeding the Machines (1)
- Module 8: Lineage Under Audit (1)
- Module 11: Data Incidents (1)
- Module 3: Generative AI Compliance (2)
- Module 5: Data Security for AI (2)
- Module 3: Diagnose the Organization (1)
- Module 16: Lab: Regional and Geopolitical AI (1)
- Module 10: Privacy and Data Governance (1)
- Module 18: Governance, Risk and Compliance Technology, Automation, and Evidence Engineering (1)
- Module 2: Data Reality (1)
- Module 7: Advanced AI Literacy (1)
- Module 3: High-Risk AI Requirements: The Technical File (1)
- Module 2: AI for Lobbying Productivity (1)
Questions
- What does data quality cover in AI governance?
- 1 competency is filed under it: Data quality rules and monitoring. Each has its own page saying what it means in practice.
- Which roles ask for data quality?
- 3 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 quality taught and graded?
- 18 graded topics teach it across 8 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.