Assignment # 5 ( BI)

Chapter 8: Questions for Discussion #1 through #4

How does prescriptive analytics relate to descriptive and predictive analytics?
Explain the differences between static and dynamic models. How can one evolve into the other?
What is the difference between an optimistic approach and a pessimistic approach to decision making under assumed uncertainty?
Explain why solving problems under uncertainty sometimes involves assuming that the problem is to be solved under conditions of risk.

Chapter 8: Exercise 4

Investigate via a Web search how models and their solutions are used by the U.S. Department of Homeland Security in the “war against terrorism.” Also investigate how other governments or government agencies are using models in their missions

Chapter 9: Questions for Discussion #1 through #5

What is Big Data? Why is it important? Where does Big Data come from?
What do you think the future of Big Data will be? Will it lose its popularity to something else? If so, what will it be?
What is Big Data analytics? How does it differ from regular analytics?
What are the critical success factors for Big Data analytics?
What are the big challenges that one should be mindful of when considering implementation of Big Data analytics?

Chapter 9: Exercise 3

At teradatauniversitynetwork.com, go to the Sports Analytics page. Find applications of Big Data in sports. Summarize your findings.

Important Note:  In cases if any websites or links do not work, select another respective exercise of choice to replace. ????When submitting work, be sure to include an APA cover page and include at least two APA formatted references (and APA in-text citations) to support the work this week.  Below is the general assessment rubric for this assignment and remember that late penalties are built within the overall assessment so complete this assignment by the Sunday due date of week 5.Important Note:  When I see similarity indexes over 20%, I will review the similarity report to determine if points are going to be docked for plagiarism issues and as a tip, do not include or write the actual questions or exercise directions within these papers.  In other words, all work must be original and not copied from any source and very high similarity indexes will be reported to the University.

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