Questions and Answers: 166
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NEW QUESTION: 1
You configure the following salary rule in the compensation plan template XML.
<comp-salary-rule useFor="merit" benchmark="range-penetration" actionOnExceed="disallow"><comp- salary-rule-threshold>100.0</comp-salary-rule-threshold><message-on-exceed><![CDATA[ You have exceeded the maximum of the salary range.
]]></message-on-exceed></comp-salary-rule>
On the compensation worksheet, a planner enters a merit increase, which puts the employee's final salary over the maximum for the salary range.
How does the system behave?
Please choose the correct answer.
Response:
A. The rule alerts the planner that the range penetration threshold has been exceeded and the merit field text turns red. The planner saves the merit recommendation.
B. A popup message asks the planner if the exceeded amount should be assigned to lump sum. The planner can save the merit recommendation by selecting "Cancel" in the pop-up message.
C. The rule prevents the planner from saving the merit increase. The planner must go back and change their merit recommendation.
D. A popup message asks the planner if the exceeded amount should be assigned to lump sum. The planner cannot save the merit increase by selecting "Cancel" in the pop-up message.
Answer: C
NEW QUESTION: 2
A ProLiant Gen8 server with several controllers and SSD drives has had multiple drive failure in the past
week. You view the overall status in the SmartSSD Wear Gauge Summary to determine whether more
failures might occur.
Which filter should you apply to evaluate which drives have problems?
A. Wear
B. Hide OK
C. SmartSSD
D. Days left
Answer: B
NEW QUESTION: 3
HOTSPOT

Answer:
Explanation:
to allow local management of the cluster to be configured.
NEW QUESTION: 4
You need to schedule an Azure Data Factory pipeline to execute when a new file arrives in an Azure Data Lake Storage Gen2 container.
Which type of trigger should you use?
A. on-demand
B. event
C. schedule
D. tumbling window
Answer: B
Explanation:
Event-driven architecture (EDA) is a common data integration pattern that involves production, detection, consumption, and reaction to events. Data integration scenarios often require Data Factory customers to trigger pipelines based on events happening in storage account, such as the arrival or deletion of a file in Azure Blob Storage account.
Reference:
https://docs.microsoft.com/en-us/azure/data-factory/how-to-create-event-trigger