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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:
Oct 26, 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 uses an Amazon Redshift Single-AZ cluster for enterprise analytics. The company wants to set up a highly resilient disaster recovery (DR) solution for the cluster. The solution must meet a recovery time objective (RTO) of less than 1 hour.

Which solution will meet this requirement MOST cost-effectively?

Options:

A.

Use a Redshift dense storage (DS2) node. Enable Multi-AZ deployment.

B.

Use a Redshift RA3 node. Enable Multi-AZ deployment.

C.

Configure a Redshift cluster from a cross-Region snapshot copy in a second AWS Region when necessary.

D.

Use a Redshift RA3 node. Enable cluster relocation.

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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 company wants to implement real-time analytics capabilities. The company wants to use Amazon Kinesis Data Streams and Amazon Redshift to ingest and process streaming data at the rate of several gigabytes per second. The company wants to derive near real-time insights by using existing business intelligence (BI) and analytics tools.

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

Options:

A.

Use Kinesis Data Streams to stage data in Amazon S3. Use the COPY command to load data from Amazon S3 directly into Amazon Redshift to make the data immediately available for real-time analysis.

B.

Access the data from Kinesis Data Streams by using SQL queries. Create materialized views directly on top of the stream. Refresh the materialized views regularly to query the most recent stream data.

C.

Create an external schema in Amazon Redshift to map the data from Kinesis Data Streams to an Amazon Redshift object. Create a materialized view to read data from the stream. Set the materialized view to auto refresh.

D.

Connect Kinesis Data Streams to Amazon Kinesis Data Firehose. Use Kinesis Data Firehose to stage the data in Amazon S3. Use the COPY command to load the data from Amazon S3 to a table in Amazon Redshift.

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