PDE Maintaining and Automating Data Workloads Practice Question
You are building a data pipeline that runs daily batch jobs on Dataproc, then loads results into BigQuery. You want to orchestrate the entire workflow, including dependencies between steps, retries, and monitoring. Which Google Cloud service is most appropriate?
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
✓
Cloud Composer
Cloud Composer is a managed Apache Airflow service that provides DAG-based orchestration with rich operators for Dataproc, BigQuery, and other GCP services. It handles dependencies, retries, and monitoring out of the box. Workflows is simpler and serverless but lacks the extensive operator library and scheduling flexibility of Airflow.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Cloud Scheduler
Why it's wrong here
Cloud Scheduler only triggers jobs at scheduled times; it does not handle dependencies between tasks.
- ✓
Cloud Composer
Why this is correct
Cloud Composer (Airflow) is the right choice for complex workflows with dependencies, retries, and scheduling across Dataproc and BigQuery.
- ✗
Cloud Workflows
Why it's wrong here
Workflows is serverless but does not have built-in scheduling or the rich set of operators needed for complex Dataproc orchestration.
- ✗
Dataflow
Why it's wrong here
Dataflow is a data processing service, not an orchestrator. It can run pipelines but does not orchestrate multi-service workflows.
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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This PDE 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 PDE exam.