DEA-C01 Data Ingestion and Transformation Practice Question
This DEA-C01 practice question tests your understanding of data ingestion and transformation. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. 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 real-time analytics application uses Amazon Kinesis Data Streams. The consumer application falls behind, causing increased latency. Which action would MOST effectively improve throughput?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Increase the number of shards in the data stream.
Increasing the number of shards in the Kinesis Data Stream directly increases the stream's read capacity (each shard supports up to 2 MB/s read and 5 transactions per second for shared throughput). This allows the consumer application to process more data in parallel, reducing the backlog and latency. The question specifies a consumer application falling behind, which is a read-throughput bottleneck, and scaling shards is the most effective way to address it.
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.
✗
Reduce the RecordMaxBufferedTime parameter in the Firehose delivery stream.
Why it's wrong here
This parameter is for Firehose, not Kinesis Data Streams.
✓
Increase the number of shards in the data stream.
Why this is correct
More shards increase parallelism and throughput capacity.
Related concept
Read the scenario before looking for a memorised answer.
✗
Increase the batch size in the Kinesis Producer Library.
Why it's wrong here
Larger batches increase throughput but consumer may still be slow due to shard limits.
✗
Use enhanced fan-out to dedicate a shard per consumer.
Why it's wrong here
Enhanced fan-out reduces latency but does not increase total throughput.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse producer-side optimizations (like KPL batch size or Firehose buffering) with consumer-side throughput issues, or they assume enhanced fan-out alone solves a shard-scaling problem without recognizing that the root cause is insufficient shard count for the consumer's processing rate.
Detailed technical explanation
How to think about this question
Kinesis Data Streams shards are the base throughput unit: each shard provides 1 MB/s write and 2 MB/s read (shared across all consumers) or 2 MB/s per consumer with enhanced fan-out. When a consumer falls behind, the typical bottleneck is the shared read throughput limit across shards; adding shards increases both the total read capacity and the number of parallel processing tasks. In real-world scenarios, a single consumer using shared throughput on a stream with 5 shards can only read up to 10 MB/s total; doubling shards to 10 doubles that capacity, directly reducing latency.
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.
TExam Day Tips
→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 exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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: Increase the number of shards in the data stream. — Increasing the number of shards in the Kinesis Data Stream directly increases the stream's read capacity (each shard supports up to 2 MB/s read and 5 transactions per second for shared throughput). This allows the consumer application to process more data in parallel, reducing the backlog and latency. The question specifies a consumer application falling behind, which is a read-throughput bottleneck, and scaling shards is the most effective way to address it.
What should I do if I get this DEA-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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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