Databricks-DA-Assoc Creating Dashboards and Visualizations Practice Question
You are configuring a Databricks SQL dashboard that includes a filter widget based on a query parameter. Which TWO statements correctly describe how parameters and filter widgets behave in this dashboard? (Choose two.)
⚠ Common exam trap
The trap here is assuming a filter widget is tied to one chart or only handles numbers, when parameters are shared by name and support text and date types.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
A dashboard filter widget can be applied to multiple visualizations at once, so changing its value updates all connected queries that reference the same parameter.
Parameters written with the double-curly-brace syntax become dashboard filter widgets, and a parameter shared by name across queries lets one widget control multiple visualizations. The remaining statements are wrong because parameters are resolved at run time, filter widgets can drive many charts, and parameters support text and date types as well as numbers.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Parameter values are permanently baked into the saved query definition, so changing a filter widget does not alter the SQL that is sent to the warehouse.
Why it's wrong here
Parameters are resolved at execution time, not baked into the saved query. When a viewer changes a filter widget, the parameter value is substituted into the query before it runs, so the SQL sent to the warehouse does change. This statement contradicts how parameterized queries operate in Databricks SQL.
- ✗
A filter widget can only be bound to a single visualization, and adding the same parameter to a second chart creates an independent, unlinked control.
Why it's wrong here
Filter widgets are not limited to one visualization. A parameter with the same name used across multiple queries produces a shared control that affects all of them, not separate unlinked controls. This statement misrepresents the sharing behavior that makes dashboard filters useful for coordinated analysis.
- ✓
A dashboard filter widget can be applied to multiple visualizations at once, so changing its value updates all connected queries that reference the same parameter.
Why this is correct
Filter widgets are designed to be shared across visualizations. When several visualizations are based on queries that reference the same parameter name, a single filter widget controls them all, so one selection refreshes every connected chart. This gives consistent, coordinated filtering across the dashboard rather than per-chart controls.
- ✓
A parameter referenced in a query with the {{ parameter_name }} syntax creates a filter widget on the dashboard that viewers can use to change the value.
Why this is correct
When a query includes a parameter using the double-curly-brace syntax, Databricks SQL automatically exposes it as a filter widget on the dashboard. Viewers can then select or enter a value, and the visualization refreshes with the new parameter value applied. This is the standard mechanism for building interactive dashboard filters.
- ✗
Parameters can only accept numeric values, so a filter widget cannot be used to filter a dashboard by a text field such as region or product category.
Why it's wrong here
Parameters support multiple data types including text, number, date, and date range. A filter widget can absolutely be used to filter by text fields such as region or category, often rendering a dropdown of distinct values. Restricting parameters to numeric values would severely limit dashboard interactivity and is incorrect.
Visual reference
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Last reviewed September 2026 · checked against the official Databricks exam blueprint
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