DEA-C01 Data Ingestion and Transformation Practice Question
A company wants to ingest streaming data from thousands of IoT devices into AWS for real-time analytics. The data volume is variable and can spike unpredictably. The solution must be serverless and minimize operational overhead. Which AWS service should be used for ingestion?
⚠ Common exam trap
Watch out — candidates often confuse Kinesis Data Firehose (near-real-time, batch delivery) with Kinesis Data Streams (real-time, sub-second processing), assuming Firehose is sufficient for real-time analytics when it actually introduces latency due to its buffering and batching behavior.
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
✓
Use Amazon Kinesis Data Streams to ingest and process data in real time.
Amazon Kinesis Data Streams is the correct choice because it is a serverless, real-time data ingestion service designed to handle variable and unpredictable data volumes from thousands of sources. It provides durable, low-latency streaming with the ability to process data in real time using consumers like Lambda or Kinesis Data Analytics, meeting the requirements for real-time analytics and minimal operational overhead.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use Amazon Kinesis Data Firehose to load streaming data directly into Amazon S3.
Why it's wrong here
Amazon Kinesis Data Firehose is a service for loading streaming data into data stores, but it does not provide the same real-time processing capabilities as Kinesis Data Streams.
- ✗
Use Amazon SQS to queue messages and process them in batches.
Why it's wrong here
Amazon SQS is a message queuing service, not designed for real-time streaming analytics. It would add latency and not support the required real-time processing.
- ✓
Use Amazon Kinesis Data Streams to ingest and process data in real time.
Why this is correct
Amazon Kinesis Data Streams is a serverless streaming data service that can handle variable and high-throughput data from many sources, making it ideal for IoT data ingestion.
- ✗
Use AWS IoT Core to ingest data and route it to Amazon DynamoDB.
Why it's wrong here
AWS IoT Core is a managed cloud service that lets connected devices interact with cloud applications, but it is not primarily a streaming ingestion service for analytics.
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 |
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.