MLS-C01 Data Engineering Practice Question
A company is designing a data pipeline that ingests streaming data from social media feeds. The data must be processed in real-time to detect trending topics, and results must be stored in Amazon DynamoDB for low-latency access. Which services should the company use? (Choose TWO.)
⚠ Common exam trap
It's easy for candidates to confuse Kinesis Data Firehose (a delivery service) with Kinesis Data Analytics (a real-time processing service), or assume Lambda alone can handle streaming analytics, when in fact Kinesis Data Analytics is the only option that provides built-in SQL-based stream processing for real-time trend detection.
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
Amazon Kinesis Data Analytics (D) is correct because it provides real-time SQL-based processing of streaming data, enabling the detection of trending topics from social media feeds without requiring custom code. It directly analyzes data from Kinesis Data Streams and can output results to DynamoDB via a Lambda function or Firehose, meeting the low-latency storage requirement.
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 Firehose
Why it's wrong here
Firehose delivers data to destinations, not real-time analytics.
- ✗
AWS Lambda
Why it's wrong here
Lambda can process but not ideal for continuous real-time analytics.
- ✗
Amazon Simple Queue Service (SQS)
Why it's wrong here
SQS is for decoupling, not real-time streaming.
- ✓
Amazon Kinesis Data Analytics
Why this is correct
Provides real-time analytics to detect trending topics.
- ✓
Amazon Kinesis Data Streams
Why this is correct
Ingests high-throughput streaming data.
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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