Databricks-DA-Assoc Understanding the Databricks Platform Practice Question
A data analyst is building a dashboard in Databricks SQL and needs to give viewers the ability to change the date range and a region filter without editing the underlying query. The dashboard should refresh results based on the viewer's selections. Which feature should the analyst use?
⚠ Common exam trap
Watch out — candidates often confuse a performance feature like a materialized view with an interactive filtering feature like dashboard parameters.
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
✓
Dashboard parameters that are referenced in the dataset queries
Dashboard parameters are the built-in way to let viewers supply values such as a date range or region that are injected into dataset queries. They provide interactive controls without editing SQL and refresh results on selection. Materialized views, Delta Live Tables, and notebook widgets address performance, pipeline refresh, or notebook interactivity, not dashboard viewer filtering.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
A materialized view that pre-aggregates the data by date and region
Why it's wrong here
A materialized view improves performance by storing precomputed results, but it does not give dashboard viewers interactive controls. Changing the date range or region would still require a query change or a separate view. Materialized views are a performance optimization, not an interactive filtering mechanism, so they do not satisfy the requirement for viewer-driven selections.
- ✓
Dashboard parameters that are referenced in the dataset queries
Why this is correct
Dashboard parameters let viewers supply values, such as a date range or region, that are substituted into the dataset queries at run time. This is exactly the interactive filtering behavior required, and it does not require viewers to edit SQL. Parameters can be exposed as widgets on the dashboard, so stakeholders can change the date range and region and see updated results.
- ✗
A Delta Live Tables pipeline that refreshes the dashboard dataset hourly
Why it's wrong here
Delta Live Tables pipelines are for declarative data engineering transformations and scheduled refreshes, not for exposing interactive filters to dashboard viewers. An hourly refresh would update data on a schedule, but viewers still could not change the date range or region themselves. This approach addresses data freshness, not interactive dashboard parameters.
- ✗
A notebook widget embedded in the dashboard as a separate visualization
Why it's wrong here
Notebook widgets are used inside notebooks for interactive input during development. They are not the supported mechanism for passing viewer selections into dashboard dataset queries. Embedding a notebook does not provide the same parameter substitution and dashboard-level filtering that dashboard parameters offer, and it complicates the dashboard rather than solving the requirement.
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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.