A data engineering team is designing a system to process streaming data from IoT devices. The data volume is unpredictable and can spike during certain events. The team wants to use a distributed processing framework that can scale automatically. Which approach should the team use?

Use an Amazon RDS database to store the streaming data and run SQL queries.

Use Amazon Kinesis Data Analytics with a Lambda function as a consumer.

Use AWS Glue to run a batch job every hour.

Use a single EC2 instance running a Python script to poll the data.

A data engineering team maintains a pipeline that transforms data daily. Recently, a change to the transformation logic caused incorrect output, but the issue was not detected until after the data was loaded. The team wants to prevent this in the future. Which practice should the team adopt?

Increase the logging level of the pipeline to DEBUG in production.

Add unit tests for the transformation logic and run them in a CI pipeline before deployment.

Schedule the pipeline to run twice a day instead of once.

Use a larger compute instance for the transformation job.

AWSCertified Data Engineer - Associate

Domain 1Objective 4

Task 1.4: Apply Programming Concepts DEA-C01 Practice Questions (Page 2)

Part of the Content Domain 1: Data Ingestion and Transformation domain, which accounts for 34% of the DEA-C01 exam. AWS does not publish an official question count, but from its 130-minute exam (~50–85 total, ~17–29 in this domain), expect 4–7 from this objective — we provide 33 practice questions to prepare you well beyond it. (estimate)

33questions here

7free pages

10concepts

34%of the exam

Questions 6–10

6application · medium
A data engineer needs to validate that a binary search tree (BST) contains only unique values. The engineer writes a Python function to traverse the tree. Which traversal method should the engineer use to check for duplicates efficiently?
Select an answer first
7application · medium
A data engineering team is designing a system to process streaming data from IoT devices. The data volume is unpredictable and can spike during certain events. The team wants to use a distributed processing framework that can scale automatically. Which approach should the team use?
Select an answer first
8foundation · easy
A data engineer needs to query and aggregate data stored in Amazon Redshift. Which language is most appropriate for this task?
Select an answer first
9application · medium
A data engineering team maintains a pipeline that transforms data daily. Recently, a change to the transformation logic caused incorrect output, but the issue was not detected until after the data was loaded. The team wants to prevent this in the future. Which practice should the team adopt?
Select an answer first
10foundation · easy
In an AWS SAM template, which section is used to define the serverless resources, such as Lambda functions and DynamoDB tables, that make up the application?
Select an answer first

Finished these 5 questions?

Review the revealed explanations, or continue through the curriculum.

Next 5 questions →Back to DEA-C01

Free Basic Practice is a study aid with revealable answers — not a scored exam. Examers.io is independent and not affiliated with or endorsed by AWS. “DEA-C01” is a trademark of its owner, used for identification only.

Task 1.4: Apply Programming Concepts DEA-C01 Practice Questions (Page 2)

Questions 6–10

A data engineer needs to validate that a binary search tree (BST) contains only unique values. The engineer writes a Python function to traverse the tree. Which traversal method should the engineer use to check for duplicates efficiently?

A data engineering team is designing a system to process streaming data from IoT devices. The data volume is unpredictable and can spike during certain events. The team wants to use a distributed processing framework that can scale automatically. Which approach should the team use?

A data engineer needs to query and aggregate data stored in Amazon Redshift. Which language is most appropriate for this task?

A data engineering team maintains a pipeline that transforms data daily. Recently, a change to the transformation logic caused incorrect output, but the issue was not detected until after the data was loaded. The team wants to prevent this in the future. Which practice should the team adopt?

In an AWS SAM template, which section is used to define the serverless resources, such as Lambda functions and DynamoDB tables, that make up the application?

Keep studying — Content Domain 1: Data Ingestion and Transformation