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NEW QUESTION: 1
The problem just described is best approached by use of which quantitative method?
A. Linear programming.
B. Queuing theory.
C. Integrated autoregressive-moving average (ARIMA) modeling.
D. Exponential smoothing, multiple parameters.
Answer: B
Explanation:
Two basic costs are involved in queuing (waiting-line) models: (1) the cost of providing service (including facility costs and operating costs), and (2) the cost of idle resources waiting in line. The latter may be a direct cost if paid employees are waiting, or an opportunity cost in the case of waiting customers. The objective of the queuing theory is to minimize the total cost of the system, including both service and waiting costs, for a given rate of arrivals. This minimization occurs at the point where the cost of waiting is balanced by the cost of providing service.

NEW QUESTION: 2



A. Option C
B. Option A
C. Option B
D. Option D
Answer: A

NEW QUESTION: 3
Your company identifies the following business continuity and disaster recovery objectives for virtual machines that host sales, finance, and reporting application in the company's on-premises data center.
*The finance application requires that data be retained for seven years. In the event ot a disaster, the application must be able to run from Azure. The recovery in objective (RTO) is 10 minutes,
* The reporting application must be able to recover point in-time data al a daily granularity. The RTO is eight hours.
*The sales application must be able to fail over to second on-premises data center.
You need to recommend which Azure services meet the business community and disaster recovery objectives.
The solution must minimize costs.
What should you recommend for each application? To answer, drag the appropriate services to the correct application. Each service may be used owe. More than once not at an You may need to drag the spin bar between panes or scroll 10 view content.

Answer:
Explanation: