Google Cloud Digital Leader 2025 – 400 Free Practice Questions to Pass the Exam

BigQuery is specifically designed for analyzing large datasets using SQL, making it the correct choice. It is a fully-managed, serverless data warehouse that enables super-fast SQL queries using the processing power of Google's infrastructure. The service is optimized for querying large volumes of data and can perform analytics at scale, allowing users to run complex queries on datasets that range into terabytes and petabytes.

BigQuery supports standard SQL, which is a widely used language for querying and managing data in relational databases. This makes it accessible to many data analysts and other users who are already familiar with SQL. Additionally, BigQuery is designed to handle big data efficiently, offering features such as automatic data partitioning and clustering, which enhance performance and cost-effectiveness.

In contrast, Google Cloud Storage is primarily a storage service for unstructured data, Google Kubernetes Engine is focused on container orchestration and application deployment, and Google Cloud Functions enables event-driven serverless function execution. None of these alternatives are specifically tailored for large-scale data analysis using SQL, highlighting why BigQuery is the best option for the given question.