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Data Ingestion and TransformationhardMultiple SelectObjective-mapped

DEA-C01 Amazon Kinesis Data Streams Practice Question

A company is ingesting IoT sensor data into Amazon Kinesis Data Streams. Each sensor sends a JSON payload every second. The data must be transformed and aggregated in real-time before being stored in Amazon DynamoDB. Which THREE services should be used together in the pipeline? (Choose THREE.)

⚠ Common exam trap

The trap is that candidates often confuse Amazon Kinesis Data Firehose with a real-time processing service, but Firehose is a delivery service with near-real-time latency (minimum 60 seconds) and cannot perform per-second aggregations. Additionally, some might think only Lambda is needed for transformation, but Kinesis Data Analytics is better suited for real-time aggregations like sliding windows.

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

AWS Lambda

Amazon Kinesis Data Streams (D) is the ingestion layer that captures the JSON payloads from IoT sensors in real-time, ensuring data is available for processing. AWS Lambda (A) can be used as a consumer of the stream to perform lightweight, per-record transformations, such as filtering or enriching the JSON payloads. Amazon Kinesis Data Analytics (B) is required for real-time aggregation and complex transformations using SQL or Apache Flink, enabling calculations like averages or counts per second before storing in DynamoDB. Together, these three services form a complete real-time pipeline: ingest with Kinesis Data Streams, transform/aggregate with Kinesis Data Analytics, and optionally further transform with Lambda before writing to DynamoDB.

Answer analysis

Option-by-option breakdown

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

  • AWS Lambda

    Why this is correct

    AWS Lambda can be used as a consumer of Kinesis Data Streams to perform lightweight, per-record transformations on the JSON payloads in real-time, but it is not sufficient alone for aggregation.

  • Amazon Kinesis Data Analytics

    Why this is correct

    Amazon Kinesis Data Analytics is necessary for real-time aggregation (e.g., per-second averages) and complex transformations using SQL or Flink.

  • Amazon S3

    Why it's wrong here

    Amazon S3 is a storage service and does not provide real-time transformation or aggregation; it is not suitable for this pipeline.

  • Amazon Kinesis Data Streams

    Why this is correct

    Amazon Kinesis Data Streams is the ingestion service that receives sensor data every second and makes it available for real-time processing.

  • Amazon Kinesis Data Firehose

    Why it's wrong here

    Amazon Kinesis Data Firehose is a delivery service with near-real-time latency (minimum 60 seconds) and cannot perform per-second aggregations; it is not appropriate here.

Quick reference

Cloud Service Model Comparison

ModelYou ManageProvider ManagesExamples
IaaSOS, runtime, apps, dataHardware, hypervisor, networkingEC2, Azure VMs, GCP Compute Engine
PaaSApps and dataOS, runtime, middleware, hardwareElastic Beanstalk, Azure App Service
SaaSData and settings onlyEverything elseMicrosoft 365, Salesforce, Workday
FaaS / ServerlessFunction code onlyInfra, scaling, runtimeLambda, Azure Functions, Cloud Run
CaaSContainers and appsKubernetes, OS, hardwareEKS, 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.