The correct strategies are to increase the number of shards in the Kinesis data stream and to configure the Lambda event source mapping with a batch window and concurrent batches. Increasing shards directly raises the stream’s throughput capacity, which in turn allows Lambda to scale its concurrency proportionally, preventing data from backing up and being throttled. Pairing this with a batch window and concurrent batches lets Lambda accumulate records before writing to DynamoDB, smoothing out spikes and reducing the risk of write throttling. On the AWS Certified Data Engineer Associate DEA-C01 exam, this question tests your understanding of how Kinesis shard count drives Lambda concurrency, a common trap is confusing Lambda timeout increases with throughput gains—timeout only extends processing duration, not capacity. Remember the memory tip: “Shards for speed, batches for balance” to recall that scaling shards boosts throughput while batching manages load and prevents data loss.
DEA-C01 Data Ingestion and Transformation Practice Question
This DEA-C01 practice question tests your understanding of data ingestion and transformation. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. 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 data engineer is designing a data ingestion pipeline that uses AWS Lambda to process records from a Kinesis Data Stream and write to DynamoDB. Which TWO strategies can help handle increased throughput and prevent data loss? (Choose TWO.)
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Configure the Lambda event source mapping with a batch window and set the number of concurrent batches per shard
Options B and D are correct. B: Increasing the number of shards allows higher throughput and Lambda concurrency. D: Configuring the Lambda event source mapping with a batch window and concurrent batches helps manage load. A: Increasing Lambda timeout does not increase throughput. C: Using a DLQ captures failures but does not prevent loss; retries should be configured. E: Using synchronous invocation would block and cause throttling.
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 Lambda event source mapping with a batch window and set the number of concurrent batches per shard
Why this is correct
This improves throughput and handles spikes.
Related concept
Read the scenario before looking for a memorised answer.
✗
Use synchronous invocation of Lambda from the producer
Why it's wrong here
Synchronous invocation can cause throttling and is not recommended for streaming.
✓
Increase the number of shards in the Kinesis data stream
Why this is correct
More shards increase parallelism and throughput.
Related concept
Read the scenario before looking for a memorised answer.
✗
Configure a dead-letter queue (DLQ) for the Lambda function
Why it's wrong here
DLQ captures failures but does not prevent loss; retries are needed.
✗
Increase the Lambda function timeout
Why it's wrong here
Timeout does not increase throughput.
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 cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
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.
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: Configure the Lambda event source mapping with a batch window and set the number of concurrent batches per shard — Options B and D are correct. B: Increasing the number of shards allows higher throughput and Lambda concurrency. D: Configuring the Lambda event source mapping with a batch window and concurrent batches helps manage load. A: Increasing Lambda timeout does not increase throughput. C: Using a DLQ captures failures but does not prevent loss; retries should be configured. E: Using synchronous invocation would block and cause throttling.
What should I do if I get this DEA-C01 question wrong?
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.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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