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 Databricks-Certified-Data-Engineer-Associate Dumps with Practice Exam Questions Answers

Questions: 230 Questions and Answers With Step-by-Step Explanation

Last Update: Aug 12, 2026

Databricks-Certified-Data-Engineer-Associate Question Includes: Single Choice Questions: 226, Multiple Choice Questions: 4,

Databricks-Certified-Data-Engineer-Associate Questions and Answers

Question # 1

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?

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 # 2

Which type of workloads are compatible with Auto Loader?

A.

Streaming workloads

B.

Machine learning workloads

C.

Serverless workloads

D.

Batch workloads

Question # 3

A data engineering team uses Declarative Automation Bundles, formerly known as Databricks Asset Bundles, to deploy the same codebase across development, test, and production environments. The team wants environment-specific behavior to be applied only through bundle configuration, without modifying notebooks, job definitions, or deployment logic during promotion.

Which approach applies environment-specific configuration while meeting this requirement?

A.

Deploy the same bundle once and edit job settings in the workspace UI for each environment after deployment.

B.

Define bundle variables and reference them from bundle resources, and then override the variable values for each environment using bundle targets.

C.

Use separate Git branches for each environment so each branch can contain environment-specific configuration values.

D.

Parameterize environment-specific values inside notebooks and set those parameters whenever each job run is triggered.

Question # 4

A data engineer uploads a CSV file using the Create or modify a table using file upload option in Databricks. To avoid incorrect schema inference, the engineer disables Automatically detect column types before creating a Unity Catalog-managed table.

What is the outcome?

A.

All columns are created with the STRING data type.

B.

Numeric columns are inferred as numeric types, while all other columns use STRING.

C.

Table creation fails because column types are not specified.

D.

Previously inferred column types are preserved.

Question # 5

A data engineer has manually created several Databricks jobs and dashboards using the workspace UI. The team now wants to manage these resources as code using Declarative Automation Bundles, formerly known as Databricks Asset Bundles, store the configuration in a Git repository, and deploy changes through CI/CD.

Which approach converts the existing resources into a bundle project?

A.

Run databricks bundle generate for each existing resource, then use databricks bundle deployment bind to link the generated configuration to the corresponding existing workspace resource, and commit the bundle project to Git for CI/CD deployment.

B.

Use the Databricks REST API to export each job’s JSON definition, save the JSON files into a Git repository, and configure CI/CD to import them using the REST API during each deployment.

C.

Clone an empty Git repository into a Git folder, manually recreate each job and dashboard configuration in YAML by referencing the workspace UI, and then deploy with databricks bundle deploy.

D.

Run databricks bundle init to create a new bundle project, and then use databricks bundle deploy to automatically detect and import all existing workspace resources.

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1. What is the Databricks Databricks-Certified-Data-Engineer-Associate Exam?


The Databricks Databricks-Certified-Data-Engineer-Associateatform exam assesses your ability to use the Databricks Lakehouse Platform to perform introductory data engineering tasks.

2. What topics are covered in the Databricks-Certified-Data-Engineer-Associate Exam?


The Databricks-Certified-Data-Engineer-Associateat exam covers five main areas: Databricks Lakehouse Platform (24%), ELT with Spark SQL and Python (29%), Incremental Data Processing (22%), Production Pipelines (16%), and Data Governance (9%).

3. Are there any prerequisites for taking the Databricks-Certified-Data-Engineer-Associate Exam?


There are no formal prerequisites, but it is recommended to have at least six months of hands-on experience with Databricks and related data engineering tasks.

4. How many questions are on the Databricks-Certified-Data-Engineer-Associate Exam?


The Databricks-Certified-Data-Engineer-Associateat exam consists of 45 multiple-choice questions.

5. What is the duration of the Databricks-Certified-Data-Engineer-Associate Exam?


The duration of the Databricks-Certified-Data-Engineer-Associateat exam is 90 minutes.

6. What is the difference between Databricks-Certified-Data-Engineer-Associate and Databricks-Certified-Professional-Data-Engineer Exams?


The Databricks Certified Data Engineer Associate and Databricks Certified Professional Data Engineer exams are designed to validate different levels of expertise in data engineering using the Databricks platform. Here are the key differences:

  • Databricks-Certified-Data-Engineer-Associate: The Databricks-Certified-Data-Engineer-Associate Exam assesses your ability to perform introductory data engineering tasks using the Databricks Lakehouse Platform.

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