- A
Amazon Kinesis Data Analytics for Apache Flink
Flink can perform low-latency stream processing and join with DynamoDB.
- B
Amazon Kinesis Data Firehose with Lambda transformation
Why wrong: Firehose is for delivery, not real-time enrichment with DynamoDB.
- C
AWS Lambda function triggered by Kinesis Data Streams
Why wrong: Lambda can enrich but may have cold start latency and throughput limits.
- D
AWS Glue streaming ETL
Why wrong: Glue streaming ETL has higher latency compared to Flink.
Question 345 of 1,786
DEA-C01 Data Ingestion and Transformation Practice Question
This DEA-C01 practice question tests your understanding of data ingestion and transformation. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. 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 streaming application sends data to Amazon Kinesis Data Streams. The data must be enriched with reference data from an Amazon DynamoDB table in real-time. Which AWS service can be used to perform this enrichment with minimal latency?
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
✓
Amazon Kinesis Data Analytics for Apache Flink
Amazon Kinesis Data Analytics for Apache Flink is correct because it allows you to run Apache Flink applications that can read from a Kinesis data stream, perform stateful stream processing, and enrich records in real-time by joining with reference data stored in DynamoDB. Flink's asynchronous I/O and managed state enable sub-second enrichment latency without the cold-start delays or concurrency limits of Lambda-based approaches.
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.
- ✓
Amazon Kinesis Data Analytics for Apache Flink
Why this is correct
Flink can perform low-latency stream processing and join with DynamoDB.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Amazon Kinesis Data Firehose with Lambda transformation
Why it's wrong here
Firehose is for delivery, not real-time enrichment with DynamoDB.
- ✗
AWS Lambda function triggered by Kinesis Data Streams
Why it's wrong here
Lambda can enrich but may have cold start latency and throughput limits.
- ✗
AWS Glue streaming ETL
Why it's wrong here
Glue streaming ETL has higher latency compared to Flink.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The DEA-C01 exam often tests the distinction between real-time stream processing (Kinesis Data Analytics for Flink) and near-real-time or batch-oriented services (Firehose, Glue ETL), leading candidates to choose Lambda because they assume serverless functions are always the lowest-latency option, ignoring concurrency and cold-start limitations in streaming contexts.
Detailed technical explanation
How to think about this question
Under the hood, Apache Flink uses an asynchronous I/O operator to query DynamoDB without blocking the main processing pipeline, and it can maintain a local cache of reference data via a RichAsyncFunction to reduce repeated lookups. In a real-world scenario, a Flink application can achieve end-to-end enrichment latencies under 100 milliseconds by tuning checkpoint intervals and using DynamoDB Accelerator (DAX) for cached reads, whereas Lambda-based solutions often struggle with shard iterator age growth under sustained high throughput.
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.
Quick reference
Cloud Service Model Comparison
| Model | You Manage | Provider Manages | Examples |
|---|---|---|---|
| IaaS | OS, runtime, apps, data | Hardware, hypervisor, networking | EC2, Azure VMs, GCP Compute Engine |
| PaaS | Apps and data | OS, runtime, middleware, hardware | Elastic Beanstalk, Azure App Service |
| SaaS | Data and settings only | Everything else | Microsoft 365, Salesforce, Workday |
| FaaS / Serverless | Function code only | Infra, scaling, runtime | Lambda, Azure Functions, Cloud Run |
| CaaS | Containers and apps | Kubernetes, OS, hardware | EKS, AKS, GKE |
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.
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Data Ingestion and Transformation — study guide chapter
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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: Amazon Kinesis Data Analytics for Apache Flink — Amazon Kinesis Data Analytics for Apache Flink is correct because it allows you to run Apache Flink applications that can read from a Kinesis data stream, perform stateful stream processing, and enrich records in real-time by joining with reference data stored in DynamoDB. Flink's asynchronous I/O and managed state enable sub-second enrichment latency without the cold-start delays or concurrency limits of Lambda-based approaches.
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.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
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Last reviewed: Jul 4, 2026
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.
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