Trust Signals
Visible cues that tell users whether a report or metric is defined, current, owned, explainable, and safe for a decision.
Reporting Trust
The framework for making business numbers easier to trust
Reporting Trust is confidence that a business number is defined, sourced, owned, explained, and safe to use. This hub explains the language behind that work: why numbers drift, how confidence decays, and what teams can inspect before adding more dashboards, automation, or AI.
The broader philosophy is a trusted information ecosystem: raw data, semantic meaning, business interpretation, action, and realised value staying connected. The practical method is Data Value Chain Architecture, with the Semantic Layer Gate as the control point where transformed data becomes trusted business meaning.
How to use this glossary
Start with the terms your meetings already reveal
If dashboards, spreadsheets, finance packs, and source systems disagree, the disagreement usually points to one or more of these concepts. Use the terms as a way to name the problem before deciding whether the fix is definitional, technical, operational, or governance-related.
Technical implementation
Connect the language to the implementation layer
If your team needs to turn these terms into source-to-report maps, semantic-layer checks, dbt tests, or controlled reporting artefacts, the implementation notes explain how the technical layer supports the Reporting Trust framework.
Open Implementation NotesStart here
Core pages for diagnosing reporting trust gaps
These pages connect the framework vocabulary to the practical symptoms people search for: disputed revenue, hidden spreadsheet logic, stale dashboards, missing caveats, and unclear source paths.
Data Value Chain
The path from captured reality through trusted transformation, interpretation, action, and realised business value.
Shadow Reporting
Unofficial spreadsheets and reports that appear when people need a number they can trust more than the official version.
Data Modelling for Reporting Trust
How model grain, source logic, caveats, and ownership turn source events into trusted reporting structures.
Free chapter
Want the broader Reporting Trust framework?
The opening chapter explains why trusted reporting has to come before more dashboards, automation, or AI.