WHO DECIDES?
Roles, policies, accountability, approvals and control.
+Concept / Comparison
DATA AUTHORITY VS DATA GOVERNANCE
Data governance organizes decision rights, responsibilities, policies and controls. In the DataAuthority framework, Data Authority is a narrower evidential question: can this particular data support this particular claim, and why?
01 / The difference
GOVERNANCE CAN ASSIGN AUTHORITY. EVIDENCE MUST STILL SUPPORT THE FACT.
A governance program may designate an owner, steward or system of record. That is essential organizational context. But designation alone does not prove that a value is current, complete, correctly transformed or suitable for every downstream use.
Our use of Data Authority therefore complements governance. It asks for the evidence attached to the fact: source, date, coverage, transformations, contradictions and explicit limits.
WHY BELIEVE THIS FACT?
Evidence, provenance, transformation history, coverage and limits.
WHO + WHY
Organizational accountability plus a defensible data trail.
02 / Example
A SYSTEM OF RECORD CAN STILL CONTAIN A VALUE THAT IS WRONG FOR THE QUESTION.
Imagine an official table that reports a count of zero. Governance may correctly identify that table as the official source. Data Authority asks the next questions: did the source cover the relevant territory and period? Was the category available? Did a transformation convert missing into zero? Was the value refreshed after the event being studied?
The purpose is not to weaken governance. It is to make the conditions behind a governed fact explicit enough for analytics and AI to use it responsibly.