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NEW QUESTION: 1
What job roles are required to access information within Functional Setup Manager?
A. Application Implementation Manager
B. Application Implementation Consultant
C. Any Functional User
D. IT Security Manager
E. Functional Setup Manager Superuser
Answer: A,B
Explanation:
Explanation/Reference:
Reference https://apps2fusion.com/oracle-fusion-online-training/fusion-applications/oracle-fusion-hcm/694- introducing-to-functional-set-up-manager-in-oracle-fusion-hcm
NEW QUESTION: 2
Your company has a hybrid deployment of Office 365. All mailboxes are hosted on Office 365. All users access their Office 365 mailbox by using a user account that is hosted on-premises. You need to delete a user account and its associated mailbox. Which tool should you use?
A. The Office 365 portal
B. The Remove-MSOLUser cmdlet
C. Active Directory Users and Computers
D. The Remove-Mailbox cmdlet
Answer: C
Explanation:
Explanation/Reference:
Explanation:
In a hybrid deployment of Office 365, the user accounts in the on-premise Active Directory are replicated to the Azure Active Directory using the Azure Active Directory Sync Tool (DirSync). This enables users to access Office 365 resources such as Exchange Online mailboxes by using the on-premise Active Directory credentials.
Any changes to a user account must be performed in the on-premise Active Directory. The changes will then be replicated to Azure Active Directory.
To delete a user account and mailbox, the user account must be deleted in the on-premise Active Directory. The user account deletion will be replicated to Azure Active Directory. The Exchange Online mailbox will then be deleted.
NEW QUESTION: 3
Why do you need to split a machine learning dataset into training data and test data?
A. So you can use one dataset for a wide model and one for a deep model
B. So you can try two different sets of features
C. To make sure your model is generalized for more than just the training data
D. To allow you to create unit tests in your code
Answer: C
Explanation:
The flaw with evaluating a predictive model on training data is that it does not inform you on how well the model has generalized to new unseen data. A model that is selected for its accuracy on the training dataset rather than its accuracy on an unseen test dataset is very likely to have lower accuracy on an unseen test dataset. The reason is that the model is not as generalized. It has specialized to the structure in the training dataset. This is called overfitting.
Reference: https://machinelearningmastery.com/a-simple-intuition-for-overfitting/
NEW QUESTION: 4
What considerations must you take into account when using an External Authentication solution with Cisco ISE?
A. Certain ports must be opened on any firewalls between the servers
B. NAT is not supported
C. It requires accurate time on the ISE and Authentication servers
D. Active Directory is the only supported external authentication source
Answer: A,B,C
