Define a small curated dataset before building a dashboard. Check aggregations, time zones, and row-level access with representative users, then publish charts with clear metric definitions. Plan for application updates and query load separately, because a lightweight dashboard can still trigger expensive work in the underlying database.
This is best suited to technical teams operating SQL-based analytics. Before committing a larger project, account for these trade-offs: deployment has several dependencies; database modeling remains external.
