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To be eligible to take the Google Professional-Cloud-Database-Engineer certification exam, you must have a minimum of three years of experience in database administration or data management, and at least one year of experience working with Google Cloud Platform. You should also have a strong understanding of SQL and database design principles. Professional-Cloud-Database-Engineer Exam consists of multiple-choice questions and performance-based scenarios, and you will have two hours to complete it.

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Earning the Google Professional-Cloud-Database-Engineer Certification demonstrates an individual's expertise and proficiency in designing and managing cloud-based database solutions using Google Cloud Platform. Google Cloud Certified - Professional Cloud Database Engineer certification can help individuals advance their careers and increase their earning potential.

Google Professional-Cloud-Database-Engineer certification is designed for database professionals who want to validate their skills in designing, building, and managing scalable and reliable database solutions on Google Cloud Platform. Google Cloud Certified - Professional Cloud Database Engineer certification is suitable for individuals who have a solid understanding of database concepts and working experience with databases, and want to demonstrate their expertise in designing and maintaining database systems on Google Cloud.

Google Cloud Certified - Professional Cloud Database Engineer Sample Questions (Q45-Q50):

NEW QUESTION # 45
Your organization needs to migrate a critical, on-premises MySQL database to Cloud SQL for MySQL. The on-premises database is on a version of MySQL that is supported by Cloud SQL and uses the InnoDB storage engine. You need to migrate the database while preserving transactions and minimizing downtime. What should you do?

A. Use Database Migration Service to connect to your on-premises database, and choose continuous replication.
After the on-premises database is migrated, promote the Cloud SQL for MySQL instance, and connect applications to your Cloud SQL instance.
B. Pause the on-premises applications.
Use the mysqldump utility to dump the database content in CSV format.
Run gsutil -m to move the dump file to Cloud Storage.
Use the Cloud SQL for MySQL import option.
After the import operation is complete, re-point the applications to the Cloud SQL for MySQL instance.
C. Build a Cloud Data Fusion pipeline for each table to migrate data from the on-premises MySQL database to Cloud SQL for MySQL.
Schedule downtime to run each Cloud Data Fusion pipeline.
Verify that the migration was successful.
Re-point the applications to the Cloud SQL for MySQL instance.
D. Pause the on-premises applications.
Use the mysqldump utility to dump the database content in compressed format.
Run gsutil -m to move the dump file to Cloud Storage.
Use the Cloud SQL for MySQL import option.
After the import operation is complete, re-point the applications to the Cloud SQL for MySQL instance.

Answer: C

NEW QUESTION # 46
Your application uses Cloud SQL for MySQL. Your users run reports on data that relies on near- real time; however, the additional analytics caused excessive load on the primary database. You created a read replica for the analytics workloads, but now your users are complaining about the lag in data changes and that their reports are still slow. You need to improve the report performance and shorten the lag in data replication without making changes to the current reports. Which two approaches should you implement? (Choose two.)

A. Disable replication on the read replica, and set the flag for parallel replication on the read replica.
Re-enable replication and optimize performance by setting flags on the primary instance.
B. Move your analytics workloads to BigQuery, and set up a streaming pipeline to move data and update BigQuery.
C. Disable replication on the primary instance, and set the flag for parallel replication on the primary instance. Re-enable replication and optimize performance by setting flags on the read replica.
D. Create secondary indexes on the replica.
E. Create additional read replicas, and partition your analytics users to use different read replicas.

Answer: A,D

Explanation:
https://cloud.google.com/sql/docs/mysql/replication/read-replica-indexes increase performance on read operation
https://cloud.google.com/sql/docs/mysql/replication/manage-replicas#basic-steps-to-change-parallel-replication-flags

NEW QUESTION # 47
Your ecommerce website captures user clickstream data to analyze customer traffic patterns in real time and support personalization features on your website. You plan to analyze this data using big data tools. You need a low-latency solution that can store 8 TB of data and can scale to millions of read and write requests per second. What should you do?

A. Write your data into Bigtable and use Dataproc and the Apache Hbase libraries for analysis.
B. Deploy a Cloud SQL environment with read replicas for improved performance. Use Datastream to export data to Cloud Storage and analyze with Dataproc and the Cloud Storage connector.
C. Use Memorystore to handle your low-latency requirements and for real-time analytics.
D. Stream your data into BigQuery and use Dataproc and the BigQuery Storage API to analyze large volumes of data.

Answer: A

NEW QUESTION # 48
Your organization needs to migrate a critical, on-premises MySQL database to Cloud SQL for MySQL. The on-premises database is on a version of MySQL that is supported by Cloud SQL and uses the InnoDB storage engine. You need to migrate the database while preserving transactions and minimizing downtime. What should you do?

A. 1. Pause the on-premises applications.
2. Use the mysqldump utility to dump the database content in compressed format.
3. Run gsutil -m to move the dump file to Cloud Storage.
4. Use the Cloud SQL for MySQL import option.
5. After the import operation is complete, re-point the applications to the Cloud SQL for MySQL instance.
B. 1. Build a Cloud Data Fusion pipeline for each table to migrate data from the on-premises MySQL database to Cloud SQL for MySQL.
2. Schedule downtime to run each Cloud Data Fusion pipeline.
3. Verify that the migration was successful.
4. Re-point the applications to the Cloud SQL for MySQL instance.
C. 1. Use Database Migration Service to connect to your on-premises database, and choose continuous replication.
2. After the on-premises database is migrated, promote the Cloud SQL for MySQL instance, and connect applications to your Cloud SQL instance.
D. 1 Pause the on-premises applications.
2. Use the mysqldump utility to dump the database content in CSV format.
3. Run gsutil -m to move the dump file to Cloud Storage.
4. Use the Cloud SQL for MySQL import option.
5. After the import operation is complete, re-point the applications to the Cloud SQL for MySQL instance.

Answer: C

Explanation:
https://cloud.google.com/database-migration/docs/mysql/configure-source-database

NEW QUESTION # 49
Your project is using Bigtable to store data that should not be accessed from the public internet under any circumstances, even if the requestor has a valid service account key. You need to secure access to this dat a. What should you do?

A. Use customer-managed encryption keys (CMEK).
B. Use Identity and Access Management (IAM) for Bigtable access control.
C. Use VPC Service Controls to create a trusted network for the Bigtable service.
D. Use Google Cloud Armor to add IP addresses to an allowlist.

Answer: C

Explanation:
"Users can define a security perimeter around Google Cloud resources such as Cloud Storage buckets, Bigtable instances, and BigQuery datasets to constrain data within a VPC and control the flow of data." https://cloud.google.com/vpc-service-controls

NEW QUESTION # 50
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P.S. Free 2026 Google Professional-Cloud-Database-Engineer dumps are available on Google Drive shared by TestKingFree: https://drive.google.com/open?id=1MWoQn21e3bncSSUmCviKhlbWI0dW3JuS