Databricks-DA-Assoc Creating Dashboards and Visualizations Practice Question
An analyst is preparing a report and needs to ensure that the dashboard data is always current. What is the most efficient way to achieve this?
⚠ Common exam trap
Many candidates mistakenly think they must manually execute queries every day or configure complex orchestration jobs just to keep a dashboard updated.
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
✓
Set a refresh schedule on the dashboard.
Setting a regular refresh schedule is the correct way to ensure data remains fresh. This automation removes the manual effort of refreshing queries, ensuring that the dashboard always represents the latest state of the business. It is a fundamental operational task that guarantees the dashboard's reliability and relevance, preventing stakeholders from making decisions based on stale or outdated information, which is a major risk in any data-driven environment.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Manually refresh the dashboard every morning.
Why it's wrong here
Manual processes are prone to human error and inconsistency. If the analyst forgets, the data remains stale. Automation is the standard for professional reporting environments in Databricks, as it ensures consistent updates without requiring human intervention, leading to higher reliability and trust in the dashboard's data.
- ✓
Set a refresh schedule on the dashboard.
Why this is correct
Setting a refresh schedule is the native, efficient way to automate data updates in Databricks SQL dashboards. It ensures that the SQL queries are executed at pre-defined intervals, providing up-to-date visualizations for end-users without any manual effort from the analyst, meeting the requirement for efficiency and consistency.
- ✗
Re-run the SQL queries in a notebook and export the results.
Why it's wrong here
This approach is inefficient and creates a disconnect between the data processing and the visualization layer. It requires manual steps that can be automated within the dashboard itself. Using the built-in dashboard scheduler is significantly more scalable and maintainable than running notebook-based exports for reporting purposes.
- ✗
Ask the SQL warehouse to stay running indefinitely.
Why it's wrong here
Keeping a SQL warehouse running indefinitely is a waste of compute resources and money. It does not actually trigger the refresh of the dashboard itself. Scheduling is about the timing of the query execution, not the state of the warehouse, which should be managed by auto-stop settings.
About these practice questions
This Databricks-DA-Assoc question is part of Courseiva's 291-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
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.