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Google Professional-Cloud-Database-Engineer Exam Syllabus Topics:

SectionObjectives
Managing database solutions- Deploy and administer databases
  • 1. Manage maintenance and upgrades
  • 2. Configure backups and recovery
  • 3. Implement monitoring and alerting
Designing scalable and highly available cloud database solutions- Select appropriate database services
  • 1. Design globally distributed architectures
  • 2. Plan scalability and availability strategies
  • 3. Choose relational and non-relational databases
Securing and ensuring compliance of database solutions- Implement security best practices
  • 1. Configure IAM and access controls
  • 2. Ensure compliance and governance
  • 3. Enable encryption and auditing
Migrating data solutions- Plan and execute migrations
  • 1. Migrate on-premises databases to Google Cloud
  • 2. Use Database Migration Service
  • 3. Validate migrated workloads
Optimizing database performance- Improve database efficiency
  • 1. Troubleshoot performance bottlenecks
  • 2. Optimize storage and compute resources
  • 3. Tune queries and indexes

>> Latest Professional-Cloud-Database-Engineer Practice Questions <<

Professional-Cloud-Database-Engineer Practice Engine | Professional-Cloud-Database-Engineer Reliable Exam Questions

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Google Cloud Certified - Professional Cloud Database Engineer Sample Questions (Q39-Q44):

NEW QUESTION # 39
Your company is developing a new global transactional application that must be ACID-compliant and have 99.999% availability. You are responsible for selecting the appropriate Google Cloud database to serve as a datastore for this new application. What should you do?

Answer: D


NEW QUESTION # 40
You want to migrate an existing on-premises application to Google Cloud. Your application supports semi-structured data ingested from 100,000 sensors, and each sensor sends 10 readings per second from manufacturing plants. You need to make this data available for real-time monitoring and analysis. What should you do?

Answer: A

Explanation:
Bigtable is a scalable, fully managed, and high-performance NoSQL database service that can handle semi-structured data and support real-time monitoring and analysis. Cloud SQL is a relational database service that does not support semi-structured dat a. BigQuery is a data warehouse service that is optimized for batch processing and analytics, not real-time monitoring. Cloud Spanner is a relational database service that supports semi-structured data with JSON data type, but it is more expensive and complex than Bigtable for this use case.


NEW QUESTION # 41
You are configuring a brand new Cloud SQL for PostgreSQL database instance in Google Cloud. Your application team wants you to deploy one primary instance, one standby instance, and one read replica instance. You need to ensure that you are following Google-recommended practices for high availability.
What should you do?

Answer: B

Explanation:
https://cloud.google.com/sql/docs/postgres/high-availability#failover-overview


NEW QUESTION # 42
An analytics team needs to read data out of Cloud SQL for SQL Server and update a table in Cloud Spanner. You need to create a service account and grant least privilege access using predefined roles. What roles should you assign to the service account?

Answer: C


NEW QUESTION # 43
Your company is evaluating Google Cloud database options for a mission-critical global payments gateway application. The application must be available 24/7 to users worldwide, horizontally scalable, and support open source databases. You need to select an automatically shardable, fully managed database with 99.999% availability and strong transactional consistency. What should you do?

Answer: B


NEW QUESTION # 44
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