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Google Professional-Cloud-Database-Engineer Exam Overview:

Certification Vendor:Google Cloud
Exam Name:Google Cloud Certified - Professional Cloud Database Engineer
Exam Number:Professional-Cloud-Database-Engineer
Certificate Validity Period:2 years
Exam Duration:120 minutes
Exam Price:$200 USD
Exam Format:Multiple Choice, Multiple Select
Available Languages:Japanese, English
Related Certifications:Google Cloud Certified - Professional Data Engineer
Google Cloud Certified - Associate Cloud Engineer
Google Cloud Certified - Professional Cloud Architect
Real Exam Qty:50-60
Passing Score:Not officially disclosed
Sample Questions:Google Professional-Cloud-Database-Engineer Sample Questions
Exam Way:Online-proctored or onsite-proctored at a testing center
Pre Condition:No formal prerequisites. Google recommends hands-on experience with Google Cloud database services and cloud architecture.
Official Syllabus URL:https://cloud.google.com/learn/certification/cloud-database-engineer

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The Google Professional-Cloud-Database-Engineer Exam consists of multiple-choice questions and scenarios that test your ability to design, deploy, and manage databases on the Google Cloud Platform. Professional-Cloud-Database-Engineer exam covers a wide range of topics, including database design, data modeling, database deployment, data security, and database optimization. Passing Professional-Cloud-Database-Engineer exam demonstrates your expertise in managing databases on the Google Cloud Platform and can help you advance your career in this field.

Google Cloud Certified - Professional Cloud Database Engineer is an advanced level certification exam offered by Google Cloud. It is designed for IT professionals who are responsible for managing and maintaining cloud-based databases. Google Cloud Certified - Professional Cloud Database Engineer certification is a validation of an individual's expertise in designing, developing, and managing scalable and secure cloud-based databases on Google Cloud Platform.

Google Cloud Certified - Professional Cloud Database Engineer Sample Questions (Q30-Q35):

NEW QUESTION # 30
You are running an instance of Cloud Spanner as the backend of your ecommerce website. You learn that the quality assurance (QA) team has doubled the number of their test cases. You need to create a copy of your Cloud Spanner database in a new test environment to accommodate the additional test cases. You want to follow Google-recommended practices. What should you do?

Answer: D

Explanation:
https://cloud.google.com/spanner/docs/import-export-overview#file-format


NEW QUESTION # 31
You are evaluating Cloud SQL for PostgreSQL as a possible destination for your on-premises PostgreSQL instances. Geography is becoming increasingly relevant to customer privacy worldwide. Your solution must support data residency requirements and include a strategy to:
configure where data is stored
control where the encryption keys are stored
govern the access to data
What should you do?

Answer: B

Explanation:
https://cloud.google.com/blog/products/identity-security/meet-data-residency-requirements-with-google-cloud


NEW QUESTION # 32
Your organization has an existing app that just went viral. The app uses a Cloud SQL for MySQL backend database that is experiencing slow disk performance while using hard disk drives (HDDs). You need to improve performance and reduce disk I/O wait times. What should you do?

Answer: A


NEW QUESTION # 33
You want to migrate your on-premises PostgreSQL database to Compute Engine. You need to migrate this database with the minimum downtime possible. What should you do?

Answer: C


NEW QUESTION # 34
You are migrating an on-premises online transactional process (OLTP) PostgreSQL database to Google Cloud. You want to reduce the administrative overhead on database maintenance activities, such as vacuum and memory tuning. You are also planning to introduce analytic use cases in this database. You need the migration to have minimal schema and application changes.
What should you do-

Answer: A

Explanation:
AlloyDB for PostgreSQL is a fully managed, PostgreSQL-compatible service that automates chores like vacuuming and memory tuning while still supporting standard Postgres schemas and drivers. Its built-in analytics acceleration (columnar storage and vectorized execution engines) lets you run OLAP queries alongside your OLTP workload with minimal changes to your existing applications.


NEW QUESTION # 35
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