Pre-Summer 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:
289
Last Updated:
Apr 22, 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 ingests data from multiple data sources and stores the data in an Amazon S3 bucket. An AWS Glue extract, transform, and load (ETL) job transforms the data and writes the transformed data to an Amazon S3 based data lake. The company uses Amazon Athena to query the data that is in the data lake.

The company needs to identify matching records even when the records do not have a common unique identifier.

Which solution will meet this requirement?

Options:

A.

Use Amazon Made pattern matching as part of the ETL job.

B.

Train and use the AWS Glue PySpark Filter class in the ETL job.

C.

Partition tables and use the ETL job to partition the data on a unique identifier.

D.

Train and use the AWS Lake Formation FindMatches transform in the ETL job.

Buy Now
Question 2

A company’s data processing pipeline uses AWS Glue jobs and AWS Glue Data Catalog. All AWS Glue jobs must run in a custom VPC inside a private subnet. The company uses a NAT gateway to support outbound connections.

A data engineer needs to use AWS Glue to migrate data from an on-premises PostgreSQL database to Amazon S3. There is no current network connection between AWS and the on-premises environment. However, the data engineer has updated the on-premises database to allow traffic from the custom VPC.

Which solution will meet these requirements?

Options:

A.

Create a JDBC connection in AWS Glue with the database JDBC URL, username, and password.

B.

Create a Simple Authentication and Security Layer (SASL) connection in AWS Glue to the on-premises database.

C.

Create a JDBC connection in AWS Glue with a security group that allows TCP traffic to and from itself.

D.

Create a JDBC connection in AWS Glue that uses a JDBC driver stored in Amazon S3. Retrieve the database URL, username, and password from AWS Secrets Manager.

Question 3

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.