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Databricks Databricks-Certified-Data-Engineer-Associate Exam With Confidence Using Practice Dumps

Exam Code:
Databricks-Certified-Data-Engineer-Associate
Exam Name:
Databricks Certified Data Engineer Associate Exam
Certification:
Databricks Certification
Vendor:
Databricks
Questions:
159
Last Updated:
Feb 13, 2026
Exam Status:
Stable
Databricks Databricks-Certified-Data-Engineer-Associate

Databricks-Certified-Data-Engineer-Associate: Databricks Certification Exam 2025 Study Guide Pdf and Test Engine

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Databricks Certified Data Engineer Associate Exam Questions and Answers

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Question 1

A data engineer wants to schedule their Databricks SQL dashboard to refresh every hour, but they only want the associated SQL endpoint to be running when It is necessary. The dashboard has multiple queries on multiple datasets associated with it. The data that feeds the dashboard is automatically processed using a Databricks Job.

Which approach can the data engineer use to minimize the total running time of the SQL endpoint used in the refresh schedule of their dashboard?

Options:

A.

O They can reduce the cluster size of the SQL endpoint.

B.

Q They can turn on the Auto Stop feature for the SQL endpoint.

C.

O They can set up the dashboard's SQL endpoint to be serverless.

D.

0 They can ensure the dashboard's SQL endpoint matches each of the queries' SQL endpoints.

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Question 2

A data engineer is reviewing the documentation on audit logs in Databricks for compliance purposes and needs to understand the format in which audit logs output events.

How are events formatted in Databricks audit logs?

Options:

A.

In Databricks, audit logs output events in a plain text format. In Databricks, audit logs output events in a JSON format.

B.

In Databricks, audit logs output events in an XML format.

C.

In Databricks, audit logs output events in a CSV format.

Question 3

A data engineer is maintaining an ETL pipeline code with a GitHub repository linked to their Databricks account. The data engineer wants to deploy the ETL pipeline to production as a databricks workflow.

Which approach should the data engineer use?

Options:

A.

Databricks Asset Bundles (DAB) + GitHub Integration

B.

Maintain workflow_config.j son and deploy it using Databricks CLI

C.

Manually create and manage the workflow in Ul

D.

Maintain workflow_conf ig. json and deploy it using Terraform

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