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Google Cloud Products and ServiceseasyMultiple ChoiceObjective-mapped

Cloud Digital Leader Google Cloud Products and Services Practice Question

Which Google Cloud service provides a fully managed, scalable data warehouse for running SQL queries on petabyte-scale data and supports BI tools like Looker?

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 a serverless data warehouse that scales to petabytes and uses SQL for analytics. Cloud SQL is for OLTP, Cloud Storage is object storage, and Dataflow is for data processing pipelines.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • BigQuery

    Why this is correct

    BigQuery is Google Cloud's serverless, fully managed data warehouse built on a columnar storage format and the Dremel massively parallel query engine, letting you run SQL over petabytes without provisioning. Its compute and storage are decoupled, so it scales elastically and you pay only for queries and stored data; native Looker integration and BI Engine in-memory acceleration directly support analytical workloads. That combination of serverless scalability, ANSI SQL, and built-in BI connectivity is what makes it the correct answer.

  • Cloud SQL

    Why it's wrong here

    Cloud SQL is a managed relational database service for MySQL, PostgreSQL, and SQL Server, designed for transactional (OLTP) workloads, not for petabyte-scale analytical queries. The stem requires a data warehouse that supports BI tools like Looker, which demands columnar storage and massively parallel processing (MPP) — capabilities Cloud SQL lacks. It is tempting because it offers managed SQL access, making it a natural choice for standard database needs, and would be correct for a scenario requiring a fully managed OLTP database with moderate storage.

  • Cloud Storage

    Why it's wrong here

    Cloud Storage is binary object (BLOB) storage for unstructured files, not a query engine; it lacks SQL capability, columnar formats, and compute machinery for aggregation. While BigQuery can read external data from Cloud Storage, the service itself cannot serve as the warehouse backing BI tools like Looker, because every query would require separate processing infrastructure and you cannot run analytics directly on objects.

  • Dataflow

    Why it's wrong here

    Dataflow is a unified stream and batch data processing platform built on Apache Beam that executes ETL/ELT pipelines, transforms, and real-time enrichment across workflows; it is not a place to store and query data. It autoscales worker pools to process events, but those workers are ephemeral compute, not a persistent SQL engine, so it cannot power ad-hoc analytical queries or Looker dashboards over an enterprise data set. Choosing it confuses the pipeline that loads the warehouse with the warehouse itself.

Quick reference

Cloud Service Model Comparison

ModelYou ManageProvider ManagesExamples
IaaSOS, runtime, apps, dataHardware, hypervisor, networkingEC2, Azure VMs, GCP Compute Engine
PaaSApps and dataOS, runtime, middleware, hardwareElastic Beanstalk, Azure App Service
SaaSData and settings onlyEverything elseMicrosoft 365, Salesforce, Workday
FaaS / ServerlessFunction code onlyInfra, scaling, runtimeLambda, Azure Functions, Cloud Run
CaaSContainers and appsKubernetes, OS, hardwareEKS, AKS, GKE

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JA

Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

This GCDL 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 GCDL exam.