Match each GCP data processing service to its use case.
Drag a concept onto its matching description — or click a concept then click the description.
Stream and batch data processing (Apache Beam)
Managed Hadoop and Spark clusters
Asynchronous messaging for event ingestion
Visual data integration pipelines
Workflow orchestration (Apache Airflow)
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Dataflow: Unified stream and batch data processing using Apache Beam
Dataflow is for unified stream/batch processing, Dataproc manages Spark/Hadoop, BigQuery is a serverless data warehouse, Pub/Sub is for messaging. Common confusions include mixing Dataflow with Dataproc and BigQuery with Pub/Sub.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Dataflow: Unified stream and batch data processing using Apache Beam
Why this is correct
Dataflow is a unified stream and batch data processing service based on Apache Beam.
Dataproc: Managed Spark and Hadoop clusters
Why this is correct
Dataproc provides managed clusters for Spark and Hadoop workloads.
BigQuery: Serverless data warehouse for analytics
Why this is correct
BigQuery is a fully managed, serverless data warehouse for large-scale analytics.
Pub/Sub: Asynchronous and reliable messaging service
Why this is correct
Pub/Sub is a messaging service for event ingestion and asynchronous communication.
Dataflow: Managed Spark and Hadoop clusters
Why it's wrong here
Incorrect — this describes Dataproc, not Dataflow.
BigQuery: Asynchronous messaging service
Why it's wrong here
Incorrect — this describes Pub/Sub, not BigQuery.
Quick reference
| 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 |
Go deeper
Learn chapter
Data Migration and Transfer Services
Key term
Dataflow
Dataflow is a Google Cloud managed service that processes and transforms data in real-time or batch mode using Apache Beam pipelines.
Key term
Data
Data is raw, unprocessed information, like numbers, words, or measurements, that can be stored, processed, and analyzed by computers.
About these practice questions
One of 807 original PCA practice questions on Courseiva, each with a full explanation and wrong-answer analysis — not exam dumps or protected exam content. Learn why practice questions differ from exam dumps →
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This PCA practice question is part of Courseiva's free Google Cloud 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 PCA exam.