Databricks-DA-Assoc Creating Dashboards and Visualizations Practice Question
An analyst needs to display a comparison between actual and target sales figures in a dashboard. The data exists in two separate tables. Which approach is best to display this comparison in a single visualization?
⚠ Common exam trap
Candidates frequently attempt to merge disparate tables directly within the dashboard visualization settings instead of handling the logic in SQL.
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
✓
Use a JOIN operation in the SQL query to combine the tables before visualization.
Combining data from disparate tables within the SQL layer is the recommended best practice for dashboarding in Databricks. By performing a JOIN within the SQL query, the analyst delivers a pre-aggregated, clean dataset to the visualization engine. This approach simplifies the visualization setup, minimizes the processing load on the visualizer, and ensures high performance, which is critical for complex comparative analyses in business intelligence.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Create two separate visualizations and place them side-by-side on the dashboard.
Why it's wrong here
Creating two separate visualizations makes direct comparison difficult for the end-user. It forces the human eye to reconcile the data, which defeats the purpose of an analytical dashboard. A single, integrated visualization is always preferred for direct KPI comparisons as it provides immediate, actionable insights to the business stakeholders.
- ✓
Use a JOIN operation in the SQL query to combine the tables before visualization.
Why this is correct
Joining tables via SQL is the standard way to prepare data for reporting. It allows the analyst to create a consolidated view of actual versus target data. This efficient approach keeps the dashboard lightweight and allows the visualization tool to render the comparison easily without unnecessary complexity or redundant processing.
- ✗
Use the visualization's 'secondary data source' feature to link the tables.
Why it's wrong here
Databricks SQL dashboards primarily operate on single SQL result sets per widget. They do not natively support complex 'secondary data source' linking within a single visual widget. Trying to achieve this via visual settings is not supported and would likely fail, forcing the analyst back to the SQL join approach.
- ✗
Import both tables into the dashboard's local memory and filter them.
Why it's wrong here
Databricks does not support importing data into a 'dashboard memory' for local manipulation. All dashboard queries are executed against the SQL warehouse. Trying to manipulate data locally is not a capability of the platform, and the user must perform all necessary data modeling within the SQL query definition itself.
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Databricks exam blueprint
This Databricks-DA-Assoc practice question is part of Courseiva's free Databricks certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the Databricks-DA-Assoc exam.