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NEW QUESTION: 1
잠재적인 고객을 위해 어떤 상황에서 BVF를 만드는 것이 이상적입니까?
A. 오랫동안 가치를 창출하고 싶다면 고객의 비즈니스 언어를 이해하고 부가가치를 입증하십시오.
B. 다른 판매 전술을 시도하고 고객이 여전히 HPE 솔루션에 주저하는 경우.
C. 계정 크기 및 향후 잠재적 수입에 관계없이 모든 고객에 대해 BVF를 작성해야 합니다.
D. BVF는 작성하는데 시간이 많이 걸리기 때문에 고객이 요청하면 BVF를 작성해야 합니다.
Answer: A

NEW QUESTION: 2
You are assisting a customer with the initial setup of Microsoft Dynamics 365 for finance and Operation.
You need to start the Fiscal Calendar setup process.
Which capability of Microsoft Dynamics 365 for Finance and Operations will meet this customer's need?
(Choose two)
A. Once a fiscal year is defined, months and quarters are auto -populated.
B. A fiscal year can be divided into dither quarters or months.
C. A fiscal year can be set to any length of time.
D. Multiple fiscal calendars can be defined for a single legal entity.
Answer: A,C

NEW QUESTION: 3
When assessing a newborn with cleft lip, the nurse would be alert which of the following will most likely be compromised:
A. GI function
B. Locomotion
C. Respiratory status
D. Sucking ability
Answer: D
Explanation:
Explanation: Because of the defect, the child will be unable to form the mouth adequately around the nipple thereby requiring special devices to allow feeding and sucking gratification. Respiratory status may be compromised when the child is fed improperly or during post op period.

NEW QUESTION: 4
You plan to provision an Azure Machine Learning Basic edition workspace for a data science project.
You need to identify the tasks you will be able to perform in the workspace.
Which three tasks will you be able to perform? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
D
A. Use the Automated Machine Learning user interface to train a model.
B. Create a tabular dataset that supports versioning.
C. Use the designer to train a model by dragging and dropping pre-defined modules.
D. Create an Azure Kubernetes Service (AKS) inference cluster.
E. Create a Compute Instance and use it to run code in Jupyter notebooks.
Answer: B,D,E
Explanation:
Reference:
https://azure.microsoft.com/en-us/pricing/details/machine-learning/