PDE Maintaining and Automating Data Workloads Practice Question
You need to schedule a recurring BigQuery query that aggregates data from a partitioned table and writes the results to a new table every day at 03:00 UTC. You want a fully managed solution with minimal operational overhead. What should you use?
⚠ Common exam trap
The trap here is overcomplicating the solution by using orchestration tools like Cloud Composer or Cloud Functions when a native BigQuery feature already provides the required scheduling with zero infrastructure management.
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
✓
BigQuery scheduled queries.
BigQuery scheduled queries are a fully managed feature that lets you schedule SQL queries to run at specified intervals. They require no additional infrastructure, support cron scheduling, and can write results to destination tables. This makes them the ideal choice for a recurring aggregation query with minimal operational overhead, unlike Cloud Functions, Composer, or VM-based cron jobs.
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 with a cron job that invokes a Cloud Function to run the query.
Why it's wrong here
This approach requires writing and maintaining a Cloud Function, managing authentication, and handling errors. It adds operational overhead compared to a native BigQuery scheduling feature. While it works, it is not the most managed or minimal-overhead solution for scheduling a BigQuery query.
- ✓
BigQuery scheduled queries.
Why this is correct
BigQuery scheduled queries allow you to schedule SQL queries directly in the BigQuery UI or via API. They are fully managed, require no additional infrastructure, and support cron-like schedules. This is the simplest and most operationally efficient way to run a recurring query and write results to a table.
- ✗
Cloud Composer with a DAG that runs a BigQueryOperator.
Why it's wrong here
Cloud Composer provides powerful orchestration but introduces significant operational overhead, including managing the Composer environment, dependencies, and costs. For a single recurring query, it is overkill and not the minimal-overhead solution. BigQuery scheduled queries are more appropriate for this simple use case.
- ✗
A cron job on a Compute Engine instance that runs the bq query command.
Why it's wrong here
Running a cron job on a VM requires managing the instance, ensuring it is always available, handling authentication, and monitoring failures. This is not a fully managed solution and adds unnecessary operational burden. BigQuery scheduled queries eliminate the need for infrastructure management.
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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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Google Cloud exam blueprint
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.