Databricks-DA-Assoc Understanding the Databricks Platform Practice Question
A data analyst needs to run a scheduled SQL query every morning and deliver the result to a finance team as a CSV file in cloud storage. The query logic is already tested in a Databricks SQL query. Which Databricks capability should the analyst use to automate this delivery?
⚠ Common exam trap
Many exam-takers confuse monitoring features such as alerts with delivery features, when only a scheduled query with a destination both runs on a cadence and sends the file.
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 Databricks SQL query schedule with a destination
Databricks SQL supports scheduling saved queries so they execute on a recurring cadence, and a schedule can include a destination such as cloud storage or email. That combination automates both execution and delivery of CSV results, exactly matching the finance team's requirement. Alerts, widgets, and Delta Live Tables address monitoring, interactivity, and pipeline ETL rather than scheduled result delivery.
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 Databricks SQL query schedule with a destination
Why this is correct
Scheduling a saved SQL query lets it run at defined times, and configuring a destination delivers results to cloud storage, email, or a dashboard. This directly matches the need to run daily and deliver CSV output to finance. It is the native Databricks SQL automation mechanism for recurring query results.
- ✗
A Databricks SQL alert
Why it's wrong here
Alerts evaluate a condition on a query result and notify users when the condition is met. They do not export result sets to cloud storage or deliver CSV files on a schedule. While useful for monitoring thresholds, an alert cannot fulfill the requirement to produce and deliver a CSV file every morning.
- ✗
A Delta Live Tables pipeline
Why it's wrong here
Delta Live Tables pipelines are designed for declarative, streaming or batch ETL with data quality expectations. They create and maintain tables but are not the tool for scheduling a saved SQL query and emailing or exporting a CSV to finance. Using a pipeline here adds unnecessary complexity and does not provide the required delivery format.
- ✗
A notebook-scoped widget parameter
Why it's wrong here
Widgets provide interactive parameters inside a notebook for ad hoc input, such as date ranges or filter values. They do not schedule execution or deliver files to external recipients. Using a widget would still require a human to run the notebook, so it cannot satisfy the automated daily CSV delivery the scenario demands.
About these practice questions
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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.