AI0-001 AI Models and Data Engineering Practice Question
A data engineer needs to design a data pipeline for a real-time fraud detection system. The system requires low-latency processing of streaming transactions. Which architecture is most appropriate?
⚠ Common exam trap
CompTIA often tests the distinction between true stream processing (e.g., Flink, Kafka Streams) and micro-batch or near-real-time processing (e.g., Spark Streaming), where candidates mistakenly assume that any 'streaming' API (like Spark Streaming) is equivalent to low-latency stream processing.
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
✓
Stream processing with Apache Kafka and Flink
Apache Kafka provides a distributed, fault-tolerant event streaming platform that ingests high-throughput transaction data with low latency, while Apache Flink offers true stream processing with exactly-once semantics and sub-second event-time processing. Together, they enable real-time fraud detection by analyzing transactions as they arrive, without the delays inherent in batch or micro-batch approaches.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Stream processing with Apache Kafka and Flink
Why this is correct
Stream processing provides low-latency real-time analysis.
- ✗
Data lake with Apache Spark
Why it's wrong here
Spark can do streaming but data lake is storage.
- ✗
Batch processing with Apache Hadoop
Why it's wrong here
Batch processing is too slow for real-time.
- ✗
Microservices architecture with REST APIs
Why it's wrong here
Microservices handle application logic, not data streaming.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI0-001 practice question is part of Courseiva's free CompTIA 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 AI0-001 exam.