Correct Answer: BigQuery ML
BigQuery ML allows data scientists to build and execute machine learning models in BigQuery using standard SQL queries, eliminating the need to move data to a separate ML platform....
Correct Answer
BigQuery ML
Why This Answer Is Correct
BigQuery ML allows data scientists to build and execute machine learning models in BigQuery using standard SQL queries, eliminating the need to move data to a separate ML platform.
This question evaluates your knowledge of BigQuery — a core concept tested in Professional Cloud Architect. Understanding BigQuery is essential for designing scalable, secure, and cost-effective cloud architectures. Mastery of this topic will help you answer scenario-based questions confidently on exam day.
You are analyzing petabytes of data for business intelligence reports. You need a fully managed, serverless enterprise data warehouse that supports SQL queries. Which service is best suited for this task?
A data analytics team needs to process streaming data from millions of IoT devices. The data arrives at unpredictable intervals and must be analyzed in real-time before being stored in BigQuery. Which architecture is most scalable and cost-effective?
A data warehouse team needs to join data from BigQuery with data stored in a Cloud SQL PostgreSQL instance in real-time. Which BigQuery feature allows this federated query without moving the data?
To optimize costs for a BigQuery project, you want to identify which queries are consuming the most 'Slots' and which datasets are never accessed. Which tool should you use?
Your company is audit-driven and needs to capture and analyze every SQL query executed against BigQuery for compliance purposes. How can they achieve this?