Definition · BI
Headless BI
Headless BI is an architecture that separates metric and semantic logic from the visualization layer, serving governed metrics via API to BI tools, notebooks, apps, and AI agents. For headless BI, a useful definition states an architecture that separates metric and semantic logic from the visualization layer, serving governed metrics via API to, who owns it, and which decision it.
Also known as headless business intelligence
Why it matters
Understanding headless BI matters because leaders need a shared, source-backed meaning before they can compare results, explain performance, or decide what to do next. Like headless BI, Pluvo defines metrics once in a central model and serves them anywhere, but it returns conclusions and root-cause analysis, not just numbers piped into a chart.
In practice
Operating example
Headless BI is useful when teams need a shared interpretation of an architecture that separates metric and semantic logic from the visualization layer, serving governed metrics via API to BI tools, notebooks, apps, and AI agents. The definition should make source data, timing, ownership, and the decision it supports explicit.
Pluvo example
Like headless BI, Pluvo defines metrics once in a central model and serves them anywhere, but it returns conclusions and root-cause analysis, not just numbers piped into a chart.
In practice, teams should define headless BI with a clear source, owner, time period, and decision before they use it in reporting, planning, or operating reviews.
Understanding headless BI matters because leaders need a shared, source-backed meaning before they can compare results, explain performance, or decide what to do next. Like headless BI, Pluvo defines metrics once in a central model and serves them anywhere, but it returns conclusions and root-cause analysis, not just numbers piped into a chart.
A strong workflow for headless BI separates the definition from the action: first agree what the term means, then decide how it is measured, when it changes, and who is accountable for the next step.
Like headless BI, Pluvo defines metrics once in a central model and serves them anywhere, but it returns conclusions and root-cause analysis, not just numbers piped into a chart.
FAQ
What is headless BI?
Headless BI is an architecture that separates metric and semantic logic from the visualization layer, serving governed metrics via API to BI tools, notebooks, apps, and AI agents. For headless BI, a useful definition states an architecture that separates metric and semantic logic from the visualization layer, serving governed metrics via API to, who owns it, and which decision it.
How does headless BI relate to a semantic layer?
To use headless BI, start with the decision, then confirm the source data, timing, calculation logic, and owner. The analysis is strongest when a reviewer can trace the answer back to the records that produced it.