Design innovative, scalable, and highly available cloud database solutions →mediumMultiple ChoiceObjective-mapped
PCDE Practice Question: Design innovative, scalable, and highly available cloud database solutions
A company wants to run complex analytical queries on terabytes of data with sub-second response times. The data is structured and stored in Cloud Storage as Parquet files. They need a serverless solution that can query the data directly without loading it into a database. Which service should they use?
⚠ Common exam trap
Many exam-takers confuse BigQuery with Cloud Dataproc, thinking that Hadoop/Spark is required for large-scale analytics, but BigQuery's serverless architecture and direct Cloud Storage querying eliminate the need for cluster management and provide faster interactive response times.
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
BigQuery is the correct choice because it is a serverless, fully managed data warehouse that supports querying structured data directly from Cloud Storage using external tables, without requiring data loading. It can handle terabytes of data with sub-second response times via its columnar storage, automatic scaling, and BI Engine for acceleration.
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 Dataproc
Why it's wrong here
Dataproc is a managed Spark/Hadoop service; it is not serverless and requires provisioning clusters.
- ✓
BigQuery
Why this is correct
BigQuery can query external data sources like Cloud Storage Parquet files using external tables, with sub-second performance.
- ✗
Cloud Bigtable
Why it's wrong here
Bigtable is a NoSQL database; it requires data to be imported, not queried from files.
- ✗
Cloud SQL
Why it's wrong here
Cloud SQL is a managed relational database; it cannot query external files directly.
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 |
Go deeper
Related to this question
About these practice questions
One of 1,446 original PCDE 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 →
Same concept, more angles
4 more ways this is tested on PCDE
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A data engineering team needs to run complex analytical queries on terabytes of data stored in Cloud Storage. The queries are ad-hoc and require scanning large portions of the dataset. The team needs a serverless solution that optimizes for cost by charging only for the data processed. Which Google Cloud service should they use?
medium- ✓ A.BigQuery
- B.Dataproc
- C.Cloud SQL
- D.Cloud Spanner
Why A: BigQuery is a serverless data warehouse that uses columnar storage and charges for the data scanned by queries. It is ideal for ad-hoc analytical queries on large datasets.
Variation 2. A company is running analytical queries on large datasets (terabytes) that involve aggregations, joins, and window functions. The data is updated daily via batch loads. The queries must complete in seconds to minutes. Which Google Cloud database service is BEST suited for this workload?
easy- A.Cloud SQL for MySQL
- B.Cloud Spanner
- C.Bigtable
- ✓ D.BigQuery
Why D: BigQuery is a serverless data warehouse designed for large-scale analytics with fast SQL queries. It handles terabytes to petabytes, charges by query usage, and is ideal for OLAP workloads.
Variation 3. A data engineer needs to run complex analytical queries on terabytes of data with sub-second query latency. The data is stored in Google Cloud Storage and updated daily. Which database service should they use?
easy- A.Cloud Bigtable
- ✓ B.BigQuery
- C.Cloud SQL
- D.Cloud Spanner
Why B: BigQuery is a serverless data warehouse designed for complex SQL queries on large datasets with fast query execution. It can query data directly from Cloud Storage using external tables. Cloud SQL and Spanner are for OLTP, Bigtable for real-time low-latency lookups.
Variation 4. A company needs to run complex analytical queries on large datasets (petabytes) with SQL support and high scalability. The data is stored in CSV files in Cloud Storage. Which Google Cloud service is MOST suitable?
easy- ✓ A.BigQuery
- B.Cloud Bigtable
- C.Cloud SQL
- D.Cloud Spanner
Why A: BigQuery is a serverless, highly scalable, and cost-effective data warehouse designed for running analytical queries on large datasets. It can query data directly in Cloud Storage using external tables.
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This PCDE 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 PCDE exam.