hardMultiple ChoiceObjective-mapped
PDE Practice Question: Building a data lake on Cloud Storage with data…
A company is building a data lake on Cloud Storage with data from multiple sources. They need to apply schema-on-read and support ad-hoc SQL queries. Which architecture is most suitable?
⚠ Common exam trap
Google Cloud often tests the distinction between schema-on-read (BigQuery external tables) and schema-on-write (traditional databases like Cloud Spanner or Cloud SQL), where candidates mistakenly choose a transactional database for analytical workloads.
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
✓
Ingest to Cloud Storage, create BigQuery external tables.
BigQuery external tables allow schema-on-read by defining the schema at query time over data stored in Cloud Storage, enabling ad-hoc SQL queries without loading data into a separate system. This architecture directly supports the requirement for schema-on-read and SQL-based analysis, as BigQuery provides a serverless, scalable SQL engine.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Ingest to Cloud Spanner, query directly.
Why it's wrong here
Spanner is transactional.
- ✗
Ingest to Cloud SQL, then export to Cloud Storage for queries.
Why it's wrong here
Cloud SQL not for data lakes.
- ✓
Ingest to Cloud Storage, create BigQuery external tables.
Why this is correct
Schema-on-read and SQL.
- ✗
Ingest to Cloud Storage, load into Dataproc for queries.
Why it's wrong here
Requires cluster startup.
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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