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Data Ingestion and Transformation →hardMultiple ChoiceObjective-mapped

DEA-C01 Data Ingestion and Transformation Practice Question

This DEA-C01 practice question tests your understanding of data ingestion and transformation. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.

A company runs an e-commerce platform that generates clickstream data from user interactions on their website. The data is sent as JSON objects via HTTP POST to an API Gateway endpoint, which triggers a Lambda function that writes each record to a Kinesis Data Stream (100 shards). A second Lambda function consumes the stream, transforms the data (enriches with geolocation from a DynamoDB table), and writes to a Kinesis Data Firehose delivery stream that delivers Parquet files to an S3 data lake every 5 minutes. The system has been working for months, but recently the Firehose delivery stream started showing 'DeliveryFailed' errors for a subset of records. The errors point to 'InvalidData' from the Lambda transformation. The engineer reviews the Lambda transformation code and notices that the geolocation lookup occasionally fails because the DynamoDB table has a throttling issue. The engineer needs to handle these failures gracefully so that records that fail enrichment are still delivered to S3 with a null geolocation field, without blocking other records. Which course of action should the engineer take?

A
Configure the Kinesis Data Firehose delivery stream to send failed records to a dead-letter queue (DLQ) for later reprocessing.
Why wrong: Firehose does not support DLQ natively; it can send failed records to an S3 bucket for failed data, but the records would not be enriched.
B
Modify the Lambda function to send failed records to a separate Kinesis Data Stream for manual processing.
Why wrong: This adds complexity and does not solve the immediate need to deliver records with null geolocation.
C
Modify the Lambda function to catch exceptions during the geolocation lookup, set the geolocation field to null, and continue processing the record.
This ensures all records are delivered with a default value, maintaining pipeline throughput.
D
Increase the read capacity units (RCUs) on the DynamoDB table to eliminate throttling.
Why wrong: Eliminating throttling may not be possible and increases cost; failures can still occur due to other reasons.

Full breakdown with real-world context →

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

✓

Modify the Lambda function to catch exceptions during the geolocation lookup, set the geolocation field to null, and continue processing the record.

Option C is correct because it modifies the Lambda function to catch exceptions during the geolocation lookup, set the geolocation field to null, and continue processing. This ensures that records that fail enrichment are still delivered to S3 with a null geolocation field, without blocking other records, and without requiring additional infrastructure. Option A is incorrect because Kinesis Data Firehose does not natively support a dead-letter queue (DLQ); failed records can be sent to an S3 bucket for failed data, but that would not include the transformed data with null geolocation. Option B is incorrect because sending failed records to a separate Kinesis Data Stream adds complexity and does not ensure they are delivered to S3 with the desired null geolocation field. Option D is incorrect because increasing RCUs may reduce throttling but does not eliminate the possibility of failures, and it increases cost; the requirement is to handle failures gracefully, not prevent them entirely.

Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

✗
Configure the Kinesis Data Firehose delivery stream to send failed records to a dead-letter queue (DLQ) for later reprocessing.
Why it's wrong here
Firehose does not support DLQ natively; it can send failed records to an S3 bucket for failed data, but the records would not be enriched.
✗
Modify the Lambda function to send failed records to a separate Kinesis Data Stream for manual processing.
Why it's wrong here
This adds complexity and does not solve the immediate need to deliver records with null geolocation.
✓
Modify the Lambda function to catch exceptions during the geolocation lookup, set the geolocation field to null, and continue processing the record.
Why this is correct
This ensures all records are delivered with a default value, maintaining pipeline throughput.
Related concept
Read the scenario before looking for a memorised answer.
✗
Increase the read capacity units (RCUs) on the DynamoDB table to eliminate throttling.
Why it's wrong here
Eliminating throttling may not be possible and increases cost; failures can still occur due to other reasons.

Common exam traps

Common exam trap: answer the scenario, not the keyword

Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.

Detailed technical explanation

How to think about this question

This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.

KKey Concepts to Remember

Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
Use explanations to understand the rule behind the answer.

TExam Day Tips

Underline the problem statement mentally.
Watch for words such as best, first, most likely and least administrative effort.
Review why wrong options are wrong, not only why the correct option is correct.

Key takeaway

Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.

Real-world example

How this comes up in practice

A startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.

Quick reference

AWS S3 Storage Class Comparison

Storage Class	Min Duration	Retrieval	Use Case
S3 Standard	None	Immediate	Frequently accessed data
S3 Standard-IA	30 days	Immediate	Infrequent access, rapid retrieval
S3 One Zone-IA	30 days	Immediate	Non-critical infrequent data
S3 Intelligent-Tiering	None	Immediate–hours	Unknown or changing access patterns
S3 Glacier Instant	90 days	Milliseconds	Archive with instant retrieval
S3 Glacier Flexible	90 days	Minutes–hours	Archive, flexible retrieval
S3 Glacier Deep Archive	180 days	Hours	Long-term compliance archive

What to study next

Got this wrong? Here's your next step.

Identify which DEA-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.

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FAQ

Questions learners often ask

What does this DEA-C01 question test?

Data Ingestion and Transformation — This question tests Data Ingestion and Transformation — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: Modify the Lambda function to catch exceptions during the geolocation lookup, set the geolocation field to null, and continue processing the record. — Option C is correct because it modifies the Lambda function to catch exceptions during the geolocation lookup, set the geolocation field to null, and continue processing. This ensures that records that fail enrichment are still delivered to S3 with a null geolocation field, without blocking other records, and without requiring additional infrastructure. Option A is incorrect because Kinesis Data Firehose does not natively support a dead-letter queue (DLQ); failed records can be sent to an S3 bucket for failed data, but that would not include the transformed data with null geolocation. Option B is incorrect because sending failed records to a separate Kinesis Data Stream adds complexity and does not ensure they are delivered to S3 with the desired null geolocation field. Option D is incorrect because increasing RCUs may reduce throttling but does not eliminate the possibility of failures, and it increases cost; the requirement is to handle failures gracefully, not prevent them entirely.

What should I do if I get this DEA-C01 question wrong?

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

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This DEA-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DEA-C01 exam.