Pre-Winter Sale 70% Discount Offer - Ends in 0d 00h 00m 00s - Coupon code: save70

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:
302
Last Updated:
Oct 8, 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

Are you worried about passing the Amazon Web Services Data-Engineer-Associate (AWS Certified Data Engineer - Associate (DEA-C01)) exam? Download the most recent Amazon Web Services Data-Engineer-Associate braindumps with answers that are 100% real. After downloading the Amazon Web Services Data-Engineer-Associate exam dumps training , you can receive 99 days of free updates, making this website one of the best options to save additional money. In order to help you prepare for the Amazon Web Services Data-Engineer-Associate exam questions and verified answers by IT certified experts, CertsTopics has put together a complete collection of dumps questions and answers. To help you prepare and pass the Amazon Web Services Data-Engineer-Associate exam on your first attempt, we have compiled actual exam questions and their answers. 

Our (AWS Certified Data Engineer - Associate (DEA-C01)) Study Materials are designed to meet the needs of thousands of candidates globally. A free sample of the CompTIA Data-Engineer-Associate test is available at CertsTopics. Before purchasing it, you can also see the Amazon Web Services Data-Engineer-Associate practice exam demo.

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

Question 1

A company stores CSV files in an Amazon S3 bucket. A data engineer needs to process the data in the CSV files and store the processed data in a new S3 bucket.

The process needs to rename a column, remove specific columns, ignore the second row of each file, create a new column based on the values of the first row of the data, and filter the results by a numeric value of a column.

Which solution will meet these requirements with the LEAST development effort?

Options:

A.

Use AWS Glue Python jobs to read and transform the CSV files.

B.

Use an AWS Glue custom crawler to read and transform the CSV files.

C.

Use an AWS Glue workflow to build a set of jobs to crawl and transform the CSV files.

D.

Use AWS Glue DataBrew recipes to read and transform the CSV files.

Buy Now
Question 2

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.

Question 3

A company wants to ingest streaming data into an Amazon Redshift data warehouse from an Amazon Managed Streaming for Apache Kafka (Amazon MSK) cluster. A data engineer needs to develop a solution that provides low data access time and that optimizes storage costs.

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

Options:

A.

Create an external schema that maps to the MSK cluster. Create a materialized view that references the external schema to consume the streaming data from the MSK topic.

B.

Develop an AWS Glue streaming extract, transform, and load (ETL) job to process the incoming data from Amazon MSK. Load the data into Amazon S3. Use Amazon Redshift Spectrum to read the data from Amazon S3.

C.

Create an external schema that maps to the streaming data source. Create a new Amazon Redshift table that references the external schema.

D.

Create an Amazon S3 bucket. Ingest the data from Amazon MSK. Create an event-driven AWS Lambda function to load the data from the S3 bucket to a new Amazon Redshift table.