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

SectionObjectives
Manage a database solution spanning multiple systems- Operational database management
  • 1. Backup and restore strategies
    • 2. Capacity planning and scaling
      • 3. Monitoring and performance tuning
        Migrate data solutions to Google Cloud- Database migration strategies
        • 1. Lift-and-shift vs re-platforming
          • 2. Online vs offline migration tools (e.g., Database Migration Service)
            Design scalable and highly available database solutions- Design for high availability and disaster recovery
            • 1. Replication strategies and failover design
              • 2. Regional vs multi-regional architectures
                - Select appropriate database services (relational, NoSQL, analytical)
                • 1. Cloud SQL vs AlloyDB vs Spanner selection criteria
                  • 2. Bigtable use cases and schema design
                    • 3. Firestore and document database patterns
                      Ensure reliability, performance, and optimization- Performance optimization
                      • 1. Workload tuning across database services
                        • 2. Indexing, query optimization, and caching strategies
                          - Security and compliance
                          • 1. IAM roles and access control
                            • 2. Encryption at rest and in transit

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                              Google Cloud Certified - Professional Cloud Database Engineer Sample Questions (Q15-Q20):

                              NEW QUESTION # 15
                              You are running a large, highly transactional application on Oracle Real Application Cluster (RAC) that is multi-tenant and uses shared storage. You need a solution that ensures high- performance throughput and a low-latency connection between applications and databases. The solution must also support existing Oracle features and provide ease of migration to Google Cloud. What should you do?

                              Answer: C


                              NEW QUESTION # 16
                              Your customer has a global chat application that uses a multi-regional Cloud Spanner instance. The application has recently experienced degraded performance after a new version of the application was launched. Your customer asked you for assistance. During initial troubleshooting, you observed high read latency. What should you do?

                              Answer: D

                              Explanation:
                              To troubleshoot high read latency, you can use SQL statements to analyze the SPANNER_SYS.
                              READ_STATS* tables. These tables contain statistics about read operations in Cloud Spanner, including the number of reads, read latency, and the number of read errors. By analyzing these tables, you can identify the cause of the high read latency and take appropriate action to resolve the issue. Other options, such as using query parameters to speed up frequently executed queries or changing the Cloud Spanner configuration from multi-region to single region, may not be directly related to the issue of high read latency. Similarly, analyzing the SPANNER_SYS.QUERY_STATS* tables, which contain statistics about query operations, may not be relevant to the issue of high read latency.


                              NEW QUESTION # 17
                              Your organization works with sensitive data that requires you to manage your own encryption keys. You are working on a project that stores that data in a Cloud SQL database. You need to ensure that stored data is encrypted with your keys. What should you do?

                              Answer: D


                              NEW QUESTION # 18
                              Your team is building a new inventory management application that will require read and write database instances in multiple Google Cloud regions around the globe. Your database solution requires 99.99% availability and global transactional consistency. You need a fully managed backend relational database to store inventory changes. What should you do?

                              Answer: A

                              Explanation:
                              Spanner covers the SLA


                              NEW QUESTION # 19
                              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: B

                              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 data. 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 # 20
                              ......

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