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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)
Questions:
289
Last Updated:
Apr 11, 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

Question 1

A company has a frontend ReactJS website that uses Amazon API Gateway to invoke REST APIs. The APIs perform the functionality of the website. A data engineer needs to write a Python script that can be occasionally invoked through API Gateway. The code must return results to API Gateway.

Which solution will meet these requirements with the LEAST operational overhead?

Options:

A.

Deploy a custom Python script on an Amazon Elastic Container Service (Amazon ECS) cluster.

B.

Create an AWS Lambda Python function with provisioned concurrency.

C.

Deploy a custom Python script that can integrate with API Gateway on Amazon Elastic Kubernetes Service (Amazon EKS).

D.

Create an AWS Lambda function. Ensure that the function is warm by scheduling an Amazon EventBridge rule to invoke the Lambda function every 5 minutes by using mock events.

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Question 2

A data engineer must implement a data cataloging solution to track schema changes in an Amazon Redshift table.

Which solution will meet these requirements?

Options:

A.

Schedule an AWS Glue crawler to run every day on the table by using the Java Database Connectivity (JDBC) driver. Configure the crawler to update an AWS Glue Data Catalog.

B.

Use AWS DataSync to log the table metadata to an AWS Glue Data Catalog. Use an AWS Glue crawler to update the Data Catalog every day.

C.

Use the AWS Schema Conversion Tool (AWS SCT) to log the table metadata to an Apache Hive metastore. Use Amazon EventBridge Scheduler to update the metastore every day.

D.

Schedule an AWS Glue crawler to run every day on the table. Configure the crawler to update an Apache Hive metastore.

Question 3

A company needs to build a data lake in AWS. The company must provide row-level data access and column-level data access to specific teams. The teams will access the data by using Amazon Athena, Amazon Redshift Spectrum, and Apache Hive from Amazon EMR.

Which solution will meet these requirements with the LEAST operational overhead?

Options:

A.

Use Amazon S3 for data lake storage. Use S3 access policies to restrict data access by rows and columns. Provide data access through Amazon S3.

B.

Use Amazon S3 for data lake storage. Use Apache Ranger through Amazon EMR to restrict data access by rows and columns. Provide data access by using Apache Pig.

C.

Use Amazon Redshift for data lake storage. Use Redshift security policies to restrict data access by rows and columns. Provide data access by using Apache Spark and Amazon Athena federated queries.

D.

Use Amazon S3 for data lake storage. Use AWS Lake Formation to restrict data access by rows and columns. Provide data access through AWS Lake Formation.