Study Databricks DA-ASSOC Dashboard Parameters: key concepts, common traps, and exam decision cues.
Dashboards are not just charts on top of queries. Databricks expects you to understand dataset structure, parameter behavior, widget use, and which visualization communicates the insight clearly once the SQL result is already correct.
| Need | Best first answer |
|---|---|
| reusable governed source for one or more charts | dashboard dataset |
| user input that changes query behavior | parameter or widget parameter |
| simple trend over time | line chart |
| comparing category sizes | bar chart |
| explanatory notes or layout support | text or image widget |
| If the stem says… | Strong reading |
|---|---|
| “same filter used across analysis views” | parameters and dataset-aware dashboard design |
| “best chart to communicate insight” | choose the clearest visualization for the metric and comparison |
| “dashboard value is wrong” | validate the source query and grain before touching chart settings |
| Trap | Better rule |
|---|---|
| changing the chart when the SQL result is wrong | fix the query first |
| assuming parameters are only cosmetic | parameter values can drive the underlying query logic |
| picking the most decorative chart | exam stems reward clarity, not novelty |
Dashboard questions usually separate visual behavior from data correctness. If a metric is wrong, inspect the source query and row grain first. If the dashboard needs a user-driven input, think parameters. The weak answer usually treats charts or layout as the fix for what is actually a query or semantic problem.