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PDE Designing a data lake on Google Cloud Practice Question
A company is designing a data lake on Google Cloud. They need to store raw data in multiple formats (CSV, Parquet, Avro) and allow various downstream processing frameworks. Which two storage solutions provide flexibility and scalability? (Choose two.)
⚠ Common exam trap
Google Cloud often tests the misconception that any database or storage service can serve as a data lake, but the trap here is that only object storage (Cloud Storage) and a serverless query engine (BigQuery) provide the schema-on-read flexibility and scalability required for raw multi-format data, while transactional or operational databases (Spanner, Bigtable) impose schema-on-write constraints and are not designed for bulk analytical storage.
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 correct because it can directly query raw data stored in Cloud Storage in formats like CSV, Parquet, and Avro using external tables or federated queries, without requiring data loading. This provides a flexible, serverless analytics layer that scales automatically and integrates with downstream processing frameworks like Apache Spark, Dataflow, and Dataproc.
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 Filestore
Why it's wrong here
Filestore provides shared filesystems for VMs, not scalable object storage.
- ✓
BigQuery
Why this is correct
BigQuery can store and query structured data, and with federated queries it can access external files.
- ✓
Cloud Storage
Why this is correct
Cloud Storage is object storage that can hold any file format and is highly scalable.
- ✗
Cloud Spanner
Why it's wrong here
Spanner is a relational database with strong consistency, not for data lake storage.
- ✗
Cloud Bigtable
Why it's wrong here
Bigtable is a NoSQL wide-column database, not suitable for raw file storage.
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.