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An organization wants to adopt the advanced machine learning capabilities of the Google Cloud. However, regulations require data to be stored in an on-premises data center.
Which approach should the organization use?
The correct answer is C. A hybrid-cloud approach. Here's why:
Context of the Questio n : The organization wants to use Google Cloud's advanced machine learning capabilities while maintaining data storage on-premises due to regulatory requirements.
Google Cloud Product Relevance:
A hybrid-cloud approach combines on-premises infrastructure with cloud services. This approach allows organizations to keep sensitive data on-premises while leveraging cloud services for additional computing capabilities, such as advanced machine learning. Google Cloud offers tools like Anthos and Google Cloud's hybrid and multi-cloud solutions to facilitate this integration, enabling the organization to use cloud-based machine learning tools while keeping data in their local data center.
Why Not Other Options:
A . A private-cloud approach: This refers to a cloud environment that is entirely operated within the organization's own infrastructure, which would not provide access to Google Cloud's ML capabilities.
B . A multi-cloud approach: While multi-cloud involves using services from multiple cloud providers, it does not specifically address the requirement to keep data on-premises.
D . A public-cloud approach: This would involve moving data to the public cloud, which contradicts the requirement to keep data stored on-premises.
Google Cloud Digital Leader Reference:
Refer to Hybrid and Multi-Cloud Solutions in Google Cloud documentation to understand how Google Cloud can integrate with on-premises data centers while providing cloud services.