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Google Professional-Cloud-Database-Engineer Exam Overview:
| Certification Vendor: | Google Cloud |
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| Exam Name: | Google Cloud Certified - Professional Cloud Database Engineer |
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| Exam Number: | Professional-Cloud-Database-Engineer |
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| Certificate Validity Period: | 2 years |
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| Exam Duration: | 120 minutes |
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| Exam Price: | $200 USD |
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| Exam Format: | Multiple Choice, Multiple Select |
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| Available Languages: | Japanese, English |
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| Related Certifications: | Google Cloud Certified - Professional Data Engineer Google Cloud Certified - Associate Cloud Engineer Google Cloud Certified - Professional Cloud Architect |
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| Real Exam Qty: | 50-60 |
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| Passing Score: | Not officially disclosed |
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| Sample Questions: | Google Professional-Cloud-Database-Engineer Sample Questions |
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| Exam Way: | Online-proctored or onsite-proctored at a testing center |
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| Pre Condition: | No formal prerequisites. Google recommends hands-on experience with Google Cloud database services and cloud architecture. |
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| 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?
- A. Use Dataflow to run the export in text format.
- B. Use Cloud Functions to run the export in text format.
- C. Use Cloud Functions to run the export in Avro format.
- D. Use Dataflow to run the export in Avro format.
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?
- A. Create a Cloud SQL for PostgreSQL instance on Google Cloud for the data that does not need to adhere to data residency requirements. Keep the data that must adhere to data residency requirements on-premises. Make application changes to support both databases.
- B. Use features like customer-managed encryption keys (CMEK), VPC Service Controls, and Identity and Access Management (IAM) policies.
- C. Allow application access to data only if the users are in the same region as the Google Cloud region for the Cloud SQL for PostgreSQL database.
- D. Replicate Cloud SQL databases across different zones.
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?
- A. Create a high availability (HA) failover instance with SSDs, and perform a failover to the new instance.
- B. Create a read replica of the instance with SSDs, and perform a failover to the new instance
- C. Export the data from the existing instance, and import the data into a new instance with solid-state drives (SSDs).
- D. Edit the instance to change the storage type from HDD to SSD.
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?
- A. Perform a full backup of your on-premises PostgreSQL, and then, in the migration window, perform an incremental backup.
- B. Create a hot standby on Compute Engine, and use PgBouncer to switch over the connections.
- C. Create a read replica on Cloud SQL, and then promote it to a read/write standalone instance.
- D. Use Database Migration Service to migrate your database.
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-
- A. Use AlloyDB for PostgreSQL.
- B. Use Cloud SQL for PostgreSQL.
- C. Use Spanner with PGAdapter.
- D. Deploy a self-managed PostgreSQL database on Compute Engine.
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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