Which Workspace permissions are available in Oracle Machine Learning?

Which Workspace permissions are available in Oracle Machine Learning?

• A. Only Viewer and Developer
• B. Manager and Editor
• C. Developer, Manager, and Viewer
• D. Administrator and Contributor

Answer: (C)

In Oracle Machine Learning, the available Workspace permissions consist of roles that allow users to interact with the platform according to their needs and responsibilities. The Developer role is designed for users who create and run analytical models, the Manager role enables users to oversee projects and manage workspace activities, while the Viewer role provides essential access to see the projects and results without permissions to modify them. This combination of Developer, Manager, and Viewer roles ensures that there is a clear hierarchy and division of responsibilities within the workspace. Users can engage effectively according to their skill levels and project requirements, enhancing collaboration and data governance. While other options may present various combinations of roles, they do not encompass the comprehensive set that Oracle Machine Learning offers, which is specifically tailored to facilitate the diverse functions needed within a data analysis environment. The inclusion of all three key roles—Developer, Manager, and Viewer—highlights the flexible and collaborative nature of Oracle Machine Learning's access control.

In Oracle Machine Learning, the available Workspace permissions consist of roles that allow users to interact with the platform according to their needs and responsibilities. The Developer role is designed for users who create and run analytical models, the Manager role enables users to oversee projects and manage workspace activities, while the Viewer role provides essential access to see the projects and results without permissions to modify them.

This combination of Developer, Manager, and Viewer roles ensures that there is a clear hierarchy and division of responsibilities within the workspace. Users can engage effectively according to their skill levels and project requirements, enhancing collaboration and data governance.

While other options may present various combinations of roles, they do not encompass the comprehensive set that Oracle Machine Learning offers, which is specifically tailored to facilitate the diverse functions needed within a data analysis environment. The inclusion of all three key roles—Developer, Manager, and Viewer—highlights the flexible and collaborative nature of Oracle Machine Learning's access control.