Data domain
A distinct category of information an agent can potentially reach, defined at whatever granularity actually matters for access control in a given deployment (for example, financial records, personnel records, or legal documents), forming one axis of the probing matrix.
Defined in 3 GAGE programs, which carry 3 distinct definitions of it. The wording above is taught in Certified Agentic AI Governance Professional (CAAGP).
How each discipline defines it
The same term does different work depending on who is using it. These are the definitions as each program teaches them, unedited.
A distinct category of information an agent can potentially reach, defined at whatever granularity actually matters for access control in a given deployment (for example, financial records, personnel records, or legal documents), forming one axis of the probing matrix.
A bounded, business-meaningful grouping of data (for example, "customer billing data"), defined by what it covers and does not cover, used as the unit ownership attaches to instead of individual systems, tables, or people.
A coherent set of data about one kind of thing, named in business language, spanning systems, and capable of being owned by one executive. The unit of ownership in this module.
Where it is taught
The exact lessons this term appears in. The first module of every program is free with a free account.
- Probing Data Boundaries · Testing and Red-Teaming, Certified Agentic AI Governance Professional (CAAGP)
- Why every catalog dies, and the ownership model that keeps one alive · The Catalog That Lives, Certified AI Data Governance Professional (CADGP)
- Data governance foundations · Privacy and Data Governance, Certified Enterprise Governance, Risk and Compliance Professional (CEGP)
Where it shows up at work
A definition is where Data domain starts. The lessons above teach it inside the competencies below, which are what job descriptions ask for and what the GAGE credential records. Every link here is drawn from the same careers map that builds a role's readiness check.
Establishes ownership, stewardship, councils, decision rights and issue workflows so data has a named owner and a defined meaning.
2 lessons on this page teach it as a primary outcome.
Designs tests for factuality, robustness, fairness, safety and abuse resistance with rubrics, baselines and thresholds, and says what a score misses.
One lesson on this page teach it as a primary outcome.
Profiles data, sets rules and thresholds, monitors, assigns issues to owners, and knows when data is not fit to train or run a model.
One lesson on this page teach it as a primary outcome.
Roles that hire for it
Each role page shows the full competency set, what the seat decides, and a readiness check against your own evidence.
- Chief Data Officer, data leadership editionneeds it at depth
- Data Governance Leadneeds it at depth · 2 open postings this week
- AI Model Validatorneeds it at depth
- Chief Technology Officer, AI engineering editionneeds it at depth
- Model Risk Managerneeds it at depth
- AI Evaluation Specialistneeds it at depth · 6 open postings this week
How job descriptions say it
Postings rarely use the textbook word. These are the phrases the careers map reads as asking for the competencies above.
Where the frameworks place it: DAMA-DMBOK; ISO/IEC 42001 data controls; NIST AI RMF MEASURE 1 and 2; NIST AI 600-1.
One interview question about it
Set up data stewardship for an organization whose models train on its own data. Who owns what, and how do decisions get made?
Asked of candidates for data governance operating model and stewardship. Answering it in your own words is exactly how a GAGE topic is passed, and the credential records the pass where an employer can check it.
If you come from another field
Some backgrounds already carry this competency, and the readiness check gives credit for it.
- Data analysis, stewardship and business intelligence carries it as a claim to back up: Stewardship and glossary ownership are usually in the role.
- Model risk, credit risk and quantitative analysis carries it as work you can show: Test design and benchmark selection are the craft.
- A computer science or software engineering degree carries it as a claim to back up: Testing is second nature; AI evaluation design is a new shape of it.
Terms it appears with
Not an alphabetical neighbourhood: these are the terms taught in the same lessons, ranked by how often they appear together.