Cloud Digital Leader Google Cloud products, services, and solutions Practice Test 3 — 15 Questions

Question 1

A company wants to use Google Cloud's Generative AI capabilities to build an internal assistant that can answer questions about company policies using documents stored in Google Drive. Which Google Cloud product provides pre-built infrastructure for building this type of AI application?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Vertex AI Agent Builder with Gemini and document-grounded search (RAG).. Vertex AI Agent Builder with Gemini and document-grounded search (RAG) is correct because it provides pre-built infrastructure for building a generative AI assistant that retrieves information from enterprise documents. It combines Gemini's large language model with Retrieval-Augmented Generation (RAG) to ground answers in company policy documents stored in Google Drive, without requiring custom model training or manual infrastructure setup.

Answer

BigQuery ML — train a custom language model on company policy documents.

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Cloud Natural Language API — it reads and summarizes documents automatically.

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Cloud Translation API — it translates policy documents into the user's language.

Question 2

A company currently uses Hadoop and Spark for batch data processing on a large on-premises cluster. They want to migrate these workloads to Google Cloud with minimal rewriting of existing Spark and Hadoop jobs. Which Google Cloud service is the best fit?

Accepted Answer

Cloud Dataproc — managed Apache Spark and Hadoop with minimal code changes.. Cloud Dataproc is a managed service for running Apache Spark and Hadoop clusters on Google Cloud. It supports the same open-source versions of Spark and Hadoop that the company currently uses, allowing them to migrate their existing batch processing workloads with minimal code changes. This makes it the best fit for the stated requirement of minimal rewriting.

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Cloud Dataflow — it runs all Spark and Hadoop jobs natively.

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BigQuery — it runs Spark SQL queries via BigQuery Spark stored procedures.

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Google Kubernetes Engine — deploy Spark clusters on Kubernetes.

Question 3

A development team needs a managed relational database (MySQL or PostgreSQL) for their web application. They want automatic backups, patching, and high availability without managing a database server. Which Google Cloud service provides this?

Accepted Answer

Cloud SQL. Cloud SQL is a fully managed relational database service for MySQL, PostgreSQL, and SQL Server. It handles automated backups, patching, and high availability (via regional failover replicas) without requiring the user to manage the underlying database server, directly matching the team's requirements.

Answer

Compute Engine with a self-managed MySQL installation.

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Cloud Bigtable

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Cloud Storage

Question 4

A power utility company collects electricity meter readings from 10 million smart meters every 15 minutes — generating billions of rows of time-series data per year. They need to query this data to detect anomalies and patterns. Which Google Cloud database is optimized for this massive-scale time-series IoT data?

Accepted Answer

Cloud Bigtable. Cloud Bigtable is a fully managed, scalable NoSQL database designed for large analytical and operational workloads, making it ideal for ingesting and querying high-throughput time-series data from millions of IoT devices. It supports sub-10ms latency on queries, automatic sharding, and seamless integration with Google Cloud's data analytics ecosystem (e.g., BigQuery, Dataflow), which is critical for detecting anomalies and patterns across billions of rows of meter readings.

Answer

Cloud SQL (PostgreSQL)

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Firestore

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Cloud Storage (CSV files)

Question 5

A developer wants to run a small piece of code that resizes images whenever a new image is uploaded to Cloud Storage. The code runs for less than a second and should only be triggered by the upload event. No always-on server is needed. Which Google Cloud service is ideal?

Accepted Answer

Cloud Functions triggered by Cloud Storage object creation events.. Cloud Functions is the ideal serverless compute service for event-driven, short-lived tasks like image resizing triggered by Cloud Storage uploads. It automatically scales to zero when idle, charges only for execution time (sub-second in this case), and natively binds to Cloud Storage object creation events via the `google.storage.object.finalize` trigger, eliminating the need for any always-on infrastructure.

Answer

A Compute Engine VM that runs continuously, checking for new uploads every minute.

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Cloud Run with a permanent container that listens for uploads.

Answer

BigQuery scheduled query that processes new uploads daily.

Question 6

A development team uses Cloud Build to automatically build, test, and create container images whenever code is pushed to their repository. The resulting Docker images need to be stored securely and made available to their GKE deployment pipelines. Which Google Cloud service stores and manages these container images?

Accepted Answer

Artifact Registry. Artifact Registry is the correct service because it is a fully managed, private container registry designed to store, manage, and secure Docker images and other artifacts. It integrates natively with Cloud Build for pushing images and with GKE for pulling them, supporting vulnerability scanning and IAM-based access control.

Answer

Cloud Storage bucket with a `containers/` folder.

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Cloud SQL — storing build artifacts in a relational database.

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Cloud Source Repositories — the code repository stores both source code and container images.

Question 7

An enterprise needs advanced business intelligence capabilities: governed semantic models that business users query with natural language, embedded analytics in their customer-facing application, and centralized data access controls. Which Google Cloud analytics product is purpose-built for these enterprise BI requirements?

Accepted Answer

Looker (enterprise BI platform with LookML semantic layer). Looker is purpose-built for enterprise BI with its LookML semantic modeling layer, which governs data definitions and access controls. It supports natural language querying through Looker's 'Ask Looker' feature and enables embedded analytics via its API and SDK, directly matching the requirements for governed semantic models, natural language queries, and embedded analytics.

Answer

Looker Studio (free BI dashboards)

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BigQuery — it provides natural language querying via BQML.

Answer

Vertex AI — it builds ML models that answer business questions.

Question 8

A healthcare organization wants to build an application that ingests FHIR-formatted patient records from multiple hospital systems, normalizes them, and makes them queryable by clinical researchers. Which Google Cloud service is purpose-built for healthcare data interoperability?

Accepted Answer

Cloud Healthcare API with FHIR store support.. The Cloud Healthcare API with FHIR store support is purpose-built for healthcare data interoperability because it natively handles FHIR (Fast Healthcare Interoperability Resources) standards, including resource validation, versioning, and search. It provides a managed service that ingests, normalizes, and stores FHIR-formatted patient records from multiple hospital systems, enabling secure querying by clinical researchers without requiring custom ETL pipelines.

Answer

BigQuery — store FHIR JSON records and query them with SQL.

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Cloud SQL — store patient records in a relational schema.

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Google Forms — collect patient data directly from hospitals via web forms.

Question 9

A company wants to add location-based features to their mobile app: showing nearby stores, calculating driving routes, and embedding interactive maps. Which Google Cloud platform provides these mapping and location services?

Accepted Answer

Google Maps Platform. Google Maps Platform is the correct choice because it provides the specific APIs needed for location-based features: Places API for nearby stores, Directions API for driving routes, and Maps SDK for embedding interactive maps. Cloud Spanner, IoT Core, and BigQuery Geo Viz are not designed to deliver these front-end mapping and routing services.

Answer

Cloud Spanner — it stores geolocation data with ACID transactions.

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Cloud IoT Core — it tracks device locations in real time.

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BigQuery Geo Viz — it visualizes geographic data on a map.

Question 10

A company's PostgreSQL database has grown to 50 TB and their application requires near-zero downtime, automatic failover, and the ability to scale reads horizontally without the migration complexity of switching to Spanner. Which Google Cloud database product is specifically designed as a fully managed, highly scalable PostgreSQL-compatible database?

Accepted Answer

AlloyDB for PostgreSQL. AlloyDB for PostgreSQL is a fully managed, PostgreSQL-compatible database service designed for high scalability, near-zero downtime, and automatic failover. It separates compute and storage to enable horizontal read scaling with read pools, and it uses a columnar engine for analytical acceleration, making it ideal for large workloads like 50 TB without the migration complexity of Spanner.

Answer

Cloud SQL (PostgreSQL)

Answer

Cloud Spanner

Answer

Bare metal PostgreSQL on Compute Engine

Question 11

A global e-commerce company wants to build a product recommendation engine that suggests items to customers based on their real-time browsing behavior and purchase history. They want a pre-built solution that doesn't require building an ML recommendation model from scratch. Which Google Cloud product is purpose-built for retail recommendations?

Accepted Answer

Recommendations AI (Vertex AI Search for Retail). Recommendations AI (now part of Vertex AI Search for Retail) is Google Cloud's purpose-built, pre-built solution for retail product recommendations. It uses deep learning models trained on retail-specific data (e.g., clickstream, purchase history) to generate personalized suggestions without requiring the user to build or train an ML model from scratch.

Answer

BigQuery ML — build a collaborative filtering model using SQL.

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Cloud SQL — query purchase history to find commonly bought-together products.

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Cloud Dataflow — stream user clickstream data to build recommendations in real time.

Question 12

A team uses multiple cloud services and wants to deploy all resources — VPCs, Cloud SQL databases, GKE clusters, and IAM roles — using a declarative, open-source infrastructure-as-code tool that works across multiple cloud providers. Which tool integrates natively with Google Cloud for this purpose?

Accepted Answer

Terraform. Terraform is the correct choice because it is a declarative, open-source infrastructure-as-code tool that supports multiple cloud providers, including Google Cloud, through its provider plugin architecture. It allows you to manage VPCs, Cloud SQL databases, GKE clusters, and IAM roles using HashiCorp Configuration Language (HCL) and integrates natively with Google Cloud via the google provider.

Answer

Cloud Deployment Manager — Google's native IaC service.

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Cloud Build — it builds and deploys application code.

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Ansible — it automates server configuration management.

Question 13

A data analyst at a media company needs to run complex SQL queries on petabytes of user engagement data to produce weekly reports. The dataset is stored in Google Cloud. Which Google Cloud product is purpose-built for this type of large-scale analytical SQL workload?

Accepted Answer

BigQuery, Google Cloud's serverless data warehouse for petabyte-scale analytical SQL. BigQuery is Google Cloud's serverless, highly scalable data warehouse specifically designed for petabyte-scale analytical SQL queries. It separates compute from storage and uses a columnar storage format and a distributed query engine to execute complex SQL on massive datasets without provisioning infrastructure, making it the ideal choice for the described workload.

Answer

Cloud SQL, Google Cloud's managed relational database service

Answer

Cloud Bigtable, Google's NoSQL wide-column database

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Firestore, Google Cloud's serverless NoSQL document database

Question 14

A software team deploys microservices using containers and wants Google Cloud to automatically manage the scaling, self-healing, and rollout of their containerized applications. They don't want to provision or manage underlying virtual machines. Which Google Cloud service best meets this need?

Accepted Answer

Google Kubernetes Engine (GKE), which manages containerized applications with automatic scaling, self-healing, and rolling updates. Google Kubernetes Engine (GKE) is the correct choice because it provides a managed Kubernetes environment that automates scaling, self-healing (e.g., automatic pod restarts and node repair), and rollout management (e.g., rolling updates and rollbacks) for containerized applications. This meets the requirement of not provisioning or managing underlying virtual machines, as GKE abstracts the node infrastructure.

Answer

Compute Engine, Google Cloud's virtual machine service

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Cloud Storage, for storing container images and serving them to instances

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Cloud CDN, which distributes containerized applications globally

Question 15

A marketing team wants to create interactive dashboards and reports for business stakeholders using data stored in BigQuery, without writing code. Which Google Cloud product is most appropriate for this self-service business intelligence requirement?

Accepted Answer

Looker Studio, Google's self-service data visualization tool with native BigQuery connectivity and a no-code interface. Looker Studio (formerly Google Data Studio) is the correct choice because it is Google Cloud's self-service business intelligence tool that provides a no-code, drag-and-drop interface for creating interactive dashboards and reports. It has native, built-in connectivity to BigQuery, allowing the marketing team to visualize data without writing any code or SQL queries.

Answer

Cloud Dataflow, Google Cloud's stream and batch data processing service

Answer

BigQuery itself, where the marketing team writes SQL queries to generate reports

Answer

Vertex AI, Google Cloud's unified machine learning platform