shine-dashboard-spec

To write a BI dashboard specification, translate a business prompt into a complete blueprint covering audience, decisions, KPIs, dimensions, filters, refresh cadence, data sources, and metric definitions. This ensures design and data modeling align with the intended objective.

A dashboard specification for Tableau, Looker, or Metabase should include audience framing, leading and lagging KPIs, precise metric definitions, data sources, filtering options, refresh cadence, and known caveats. The output remains tool-agnostic to guide platform-specific implementation.

Define KPIs and metric definitions by identifying leading and lagging indicators relevant to the use case, specifying exact calculation logic, and documenting known caveats. This ensures the dashboard specification provides consistent and accurate data modeling.

A dashboard specification should be tool-agnostic to maintain consistency with the defined objective. While it applies to platforms like Looker, Metabase, or Tableau, the blueprint defines dimensions, filters, and data sources independently of specific BI tooling constraints.

Dashboard designs lack clear dimensions and data sources when the initial specification omits data modeling and filtering options. Defining these elements alongside metric definitions and refresh cadence translates vague prompts into a structured dashboard blueprint.

Document refresh cadence and known caveats in a dashboard blueprint during the initial specification phase. Specifying data update frequencies and limitations alongside data sources ensures the final dashboard meets audience expectations and use-case requirements.