Google Professional Machine Learning Engineer exam dumps

Google Professional Machine Learning Engineer practice question 401 of 522

Professional Machine Learning Engineer. Professional level, Google Cloud. Free question with the correct answer and a full explanation.

Google Professional Machine Learning Engineer Question 401

Select 3Google Cloud Platform

Your company operates in a regulated industry and must keep certain sensitive data on-premises while leveraging the scalability of Google Cloud for machine learning workloads. You are tasked with designing a hybrid cloud strategy that supports secure data access and ML model training on Google Cloud while ensuring compliance. Which components or services should you consider to implement this solution?

  1. A

    Cloud VPN to establish a private connection between on-premises systems and Google Cloud.

  2. B

    BigQuery Omni to query data stored on-premises directly from Google Cloud.

  3. C

    Vertex AI Workbench to preprocess data and train ML models on Google Cloud.

  4. D

    Google Cloud Storage Transfer Service to migrate all on-premises data to Google Cloud.

  5. E

    Anthos to manage workloads across on-premises and Google Cloud environments.

Show answer and explanation

Correct answers: A, C, E

Explanation

To design a hybrid cloud strategy in a regulated industry, you need components that support secure data access, compliance, and workload management across environments. Cloud VPN ensures secure connectivity, Vertex AI Workbench handles cloud-based ML workloads, and Anthos provides a unified way to manage workloads across on-premises and Google Cloud. These components together enable an effective hybrid strategy while maintaining compliance requirements.

  • A. Correct.

    Cloud VPN allows secure communication between on-premises systems and Google Cloud, which is critical for hybrid cloud strategies where sensitive data must remain on-premises.

  • B. Incorrect.

    BigQuery Omni is designed for querying data stored in other clouds, not specifically for on-premises data. It is not relevant to this scenario.

  • C. Correct.

    Vertex AI Workbench is used to preprocess data and train ML models in the cloud, aligning with the hybrid strategy of leveraging Google Cloud for ML workloads.

  • D. Incorrect.

    Google Cloud Storage Transfer Service is used for migrating data to the cloud, which may conflict with the requirement to keep sensitive data on-premises.

  • E. Correct.

    Anthos is a hybrid and multicloud platform that enables you to manage workloads across on-premises and Google Cloud environments, making it suitable for this use case.

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