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Amazon Web Services Data-Engineer-Associate Exam With Confidence Using Practice Dumps

Exam Code:
Data-Engineer-Associate
Exam Name:
AWS Certified Data Engineer - Associate (DEA-C01)
Certification:
AWS Certified Data Engineer
Vendor:
Amazon Web Services
Questions:
302
Last Updated:
Sep 17, 2026
Exam Status:
Stable
Amazon Web Services Data-Engineer-Associate

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

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AWS Certified Data Engineer - Associate (DEA-C01) Questions and Answers

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Question 1

A company is developing machine learning (ML) models. A data engineer needs to apply data quality rules to training data. The company stores the training data in an Amazon S3 bucket.

Options:

A.

Create an AWS Lambda function to check data quality and to raise exceptions in the code.

B.

Create an AWS Glue DataBrew project for the data in the S3 bucket. Create a ruleset for the data quality rules. Create a profile job to run the data quality rules. Use Amazon EventBridge to run the profile job when data is added to the S3 bucket.

C.

Create an Amazon EMR provisioned cluster. Add a Python data quality package.

D.

Create AWS Lambda functions to evaluate data quality rules and orchestrate with AWS Step Functions.

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Question 2

A company uses an Amazon Redshift cluster that runs on RA3 nodes. The company wants to scale read and write capacity to meet demand. A data engineer needs to identify a solution that will turn on concurrency scaling.

Which solution will meet this requirement?

Options:

A.

Turn on concurrency scaling in workload management (WLM) for Redshift Serverless workgroups.

B.

Turn on concurrency scaling at the workload management (WLM) queue level in the Redshift cluster.

C.

Turn on concurrency scaling in the settings during the creation of and new Redshift cluster.

D.

Turn on concurrency scaling for the daily usage quota for the Redshift cluster.

Question 3

A data engineer has two datasets that contain sales information for multiple cities and states. One dataset is named reference, and the other dataset is named primary.

The data engineer needs a solution to determine whether a specific set of values in the city and state columns of the primary dataset exactly match the same specific values in the reference dataset. The data engineer wants to use Data Quality Definition Language (DQDL) rules in an AWS Glue Data Quality job.

Which rule will meet these requirements?

Options:

A.

DatasetMatch " reference " " city- > ref_city, state- > ref_state " = 1.0

B.

ReferentialIntegrity " city,state " " reference.{ref_city,ref_state} " = 1.0

C.

DatasetMatch " reference " " city- > ref_city, state- > ref_state " = 100

D.

ReferentialIntegrity " city,state " " reference.{ref_city,ref_state} " = 100

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