Google Cloud Digital Leader — All Questions

An analytics team needs to run fast SQL queries across petabytes of historical sales data without managing servers or clusters. Which Google Cloud service is designed for this?

• a.Cloud SQL
• b.BigQuery✓
• c.Compute Engine
• d.Cloud Storage

BigQuery is a fully managed, serverless data warehouse built for fast SQL analytics over very large datasets, scaling to petabytes without infrastructure management. Cloud SQL is a managed relational database aimed at transactional (OLTP) workloads, not petabyte-scale analytics. Compute Engine is raw VMs, and Cloud Storage is object storage, not a query engine. BigQuery fits analytical querying at scale.

A company needs a fully managed relational database that offers strong consistency and horizontal scalability across multiple regions for a global application. Which service best fits?

• a.BigQuery
• b.Pub/Sub
• c.Cloud Storage
• d.Cloud Spanner✓

Cloud Spanner is a fully managed relational database that combines the structure of SQL with horizontal scalability and strong consistency across regions globally. BigQuery is an analytics warehouse, not an operational transactional database. Pub/Sub is a messaging service, and Cloud Storage is for objects. Spanner is the right choice for a globally scalable, consistent relational database.

Which of the following is the best example of unstructured data?

• a.Customer support call recordings and product photos✓
• b.A table of orders with columns for date, amount, and customer ID
• c.Rows of inventory counts in a relational database
• d.A spreadsheet of employee names and salaries

Unstructured data has no predefined schema or tabular organization, such as audio recordings, images, and free-form text. The other options describe structured data organized into rows and columns with defined fields. Recognizing this distinction matters because structured and unstructured data are stored and processed with different tools. Call recordings and photos are the unstructured example.

A team wants to ingest a real-time stream of events from thousands of IoT sensors and reliably deliver those messages to multiple downstream processing systems. Which Google Cloud service is designed for this messaging pattern?

• a.Cloud SQL
• b.Looker
• c.Pub/Sub✓
• d.BigQuery BI Engine

Pub/Sub is a scalable, asynchronous messaging service that decouples senders (publishers) from receivers (subscribers), making it ideal for ingesting real-time event streams and fanning them out to multiple consumers. Cloud SQL is a database, Looker is a BI platform, and BI Engine accelerates queries. Pub/Sub is the messaging backbone for streaming ingestion.

Business analysts want a governed, self-service platform to explore data, build dashboards, and define consistent business metrics on top of their data warehouse. Which Google Cloud tool is purpose-built for this?

• a.Compute Engine
• b.Looker✓
• c.Cloud Functions
• d.Cloud Spanner

Looker is Google Cloud's business intelligence and data-visualization platform, letting analysts model consistent metrics and build governed self-service dashboards on top of a warehouse like BigQuery. Compute Engine provides VMs, Cloud Functions runs event code, and Spanner is a database. Looker is the BI and semantic-modeling layer described here.

Which sequence best represents a typical data lifecycle in a cloud analytics pipeline?

• a.Analyze, then ingest, then store, then delete
• b.Store, then delete, then ingest, then process
• c.Process, then ingest, then analyze, then store
• d.Ingest, then store, then process, then analyze✓

A common data lifecycle first ingests data from sources, stores it, processes or transforms it, and then analyzes it to generate insights. The other sequences put analysis or deletion before the data has even been collected or prepared, which is not workable. Understanding this ordered flow helps you match the right Google Cloud service to each stage.

A company runs a MySQL database on-premises and wants to move to a fully managed version on Google Cloud with minimal changes to their application. Which service is the most direct fit?

• a.Cloud SQL✓
• b.BigQuery
• c.Pub/Sub
• d.Cloud Storage

Cloud SQL is a fully managed database service that supports MySQL, PostgreSQL, and SQL Server, so an existing MySQL app can migrate with minimal changes. BigQuery is for analytics, not a drop-in transactional MySQL replacement. Pub/Sub is messaging and Cloud Storage is object storage. Cloud SQL best matches a managed MySQL lift.