Aggregation
The process by which many individual reports are collected into a shared database and analyzed together for patterns, repeated phone numbers, repeated company names, repeated wallet addresses, rather than each being reviewed and acted on individually. The primary mechanism by which both IC3.gov and ReportFraud.ftc.gov produce value, described honestly in Section 3D.
Defined in 3 GAGE programs, which carry 5 distinct definitions of it. The wording above is taught in Senior AI Scam Defense.
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.
The process by which many individual reports are collected into a shared database and analyzed together for patterns, repeated phone numbers, repeated company names, repeated wallet addresses, rather than each being reviewed and acted on individually. The primary mechanism by which both IC3.gov and ReportFraud.ftc.gov produce value, described honestly in Section 3D.
The evaluation of several deficiencies together where they affect the same account, disclosure, assertion or exposure, or share a common cause. Performed before individual classification, because the bias runs toward the lower rung.
a calculation that summarizes many rows of data into a single value, such as a sum, average, count, or percentage; the hop type most likely to fail silently on an incomplete input range.
Combining exposures to see their joint effect. Valid only over quantities and only with an explicit assumption about dependence between the events. Never valid over ordinal ratings.
The question of what happens when several exposures, each individually within appetite, combine to exceed it. The fifth measurement question and the one least often asked.
Where it is taught
The exact lessons this term appears in. The first module of every program is free with a free account.
- Lineage archaeology: tracing one dashboard number all the way back to its birth · The Estate Survey, Certified AI Data Governance Professional (CADGP)
- Aggregation, concentration, and interconnected risk · Enterprise Risk Architecture and Risk Appetite, Certified Enterprise Governance, Risk and Compliance Professional (CEGP)
- Continuous monitoring, automation, and deficiency evaluation · Internal Control Architecture and Control Engineering, Certified Enterprise Governance, Risk and Compliance Professional (CEGP)
- Measurement architecture · Governance, Risk and Compliance Metrics, Analytics, and Board Communication, Certified Enterprise Governance, Risk and Compliance Professional (CEGP)
- Filing at IC3.gov and ReportFraud.ftc.gov, and What Happens Next · The First 24 Hours, Senior AI Scam Defense
Where it shows up at work
A definition is where Aggregation 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.
Traces where data came from, what transformed it, who owns each hop and where it flows downstream, so a number can be defended.
One lesson on this page teach it as a primary outcome.
Measures whether governance works: inventory coverage, owners named, overdue reviews, incidents, approval times, not how busy the committee is.
One lesson on this page teach it as a primary outcome.
Maps risks to preventive, detective and corrective controls, then tests design and operation with samples, evidence and defensible findings.
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.
- Data Governance Leadneeds it at depth · 2 open postings this week
- Chief Data Officer, data leadership editionneeds it at depth
- AI Auditorneeds it at depth · 9 open postings this week
- AI Privacy Engineerneeds it at depth · 6 open postings this week
- Privacy Analystneeds working knowledge
- VP of AI Governance and Ethicsneeds working knowledge
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: EU AI Act Article 10; NIST AI RMF MAP 4; ISO/IEC 42001 Clause 9; COSO.
One interview question about it
Trace the lineage of a training dataset back to its source. What do you record, and what breaks when you cannot?
Asked of candidates for data lineage and provenance. 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.
- Privacy and data protection carries it as work you can show: Data maps and records of processing are lineage by another name.
- Data analysis, stewardship and business intelligence carries it as work you can show: Source-to-report lineage is what you trace.
- A data science, statistics or analytics degree carries it as a claim to back up: Lineage and provenance are known ideas, rarely yet documented for an auditor.
Terms it appears with
Not an alphabetical neighbourhood: these are the terms taught in the same lessons, ranked by how often they appear together.