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Google Professional-Cloud-Database-Engineer Exam With Confidence Using Practice Dumps

Exam Code:
Professional-Cloud-Database-Engineer
Exam Name:
Google Cloud Certified - Professional Cloud Database Engineer
Certification:
Cloud Database Engineer
Vendor:
Google
Questions:
141
Last Updated:
Dec 25, 2025
Exam Status:
Stable
Google Professional-Cloud-Database-Engineer

Professional-Cloud-Database-Engineer: Cloud Database Engineer Exam 2025 Study Guide Pdf and Test Engine

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Google Cloud Certified - Professional Cloud Database Engineer Questions and Answers

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Question 1

You need to migrate existing databases from Microsoft SQL Server 2016 Standard Edition on a single Windows Server 2019 Datacenter Edition to a single Cloud SQL for SQL Server instance. During the discovery phase of your project, you notice that your on-premises server peaks at around 25,000 read IOPS. You need to ensure that your Cloud SQL instance is sized appropriately to maximize read performance. What should you do?

Options:

A.

Create a SQL Server 2019 Standard on Standard machine type with 4 vCPUs, 15 GB of RAM, and 800 GB of solid-state drive (SSD).

B.

Create a SQL Server 2019 Standard on High Memory machine type with at least 16 vCPUs, 104 GB of RAM, and 200 GB of SSD.

C.

Create a SQL Server 2019 Standard on High Memory machine type with 16 vCPUs, 104 GB of RAM, and 4 TB of SSD.

D.

Create a SQL Server 2019 Enterprise on High Memory machine type with 16 vCPUs, 104 GB of RAM, and 500 GB of SSD.

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Question 2

You currently have a MySQL database running on Cloud SQL with a read replica in a different zone for non-mission critical analytics workloads. You want to enable high availability (HA) for the analytic workloads while keeping costs low. What should you do?

Options:

A.

Increase the size of the read replica Instance and enable MA.

B.

Enable HA on the current read replica.

C.

Create a new HA instance in the same zone db lie primary.

D.

Create a new MA Instance in a different region than the primary.

Question 3

You are building a data warehouse on BigQuery. Sources of data include several MySQL databases located on-premises.

You need to transfer data from these databases into BigQuery for analytics. You want to use a managed solution that has low latency and is easy to set up. What should you do?

Options:

A.

Create extracts from your on-premises databases periodically, and push these extracts to Cloud Storage.

Upload the changes into BigQuery, and merge them with existing tables.

B.

Use Cloud Data Fusion and scheduled workflows to extract data from MySQL. Transform this data into the appropriate schema, and load this data into your BigQuery database.

C.

Use Datastream to connect to your on-premises database and create a stream. Have Datastream write to Cloud Storage. Then use Dataflow to process the data into BigQuery.

D.

Use Database Migration Service to replicate data to a Cloud SQL for MySQL instance. Create federated tables in BigQuery on top of the replicated instances to transform and load the data into your BigQuery database.

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