Analytics, Data Science,  Artificial Intelligence Systems for Decision Support

From book:  Analytics, Data Science,  Artificial Intelligence Systems for Decision Support (11th Edition)

Chapter 8:

1. How does prescriptive analytics relate to descriptive and predictive analytics?

2. Explain the differences between static and dynamic models. How can one evolve into the other?

3. What is the difference between an optimistic approach and a pessimistic approach to decision making under assumed uncertainty?

4. Explain why solving problems under uncertainty some- times involves assuming that the problem is to be solved under conditions of risk.

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:

1. What is Big Data? Why is it important? Where does Big Data come from?

2. 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?

3. What is Big Data analytics? How does it differ from regular analytics?

4. What are the critical success factors for Big Data analytics?

5. What are the big challenges that one should be mindful of when considering implementation of Big Data analytics?

Exercise: 3

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

Need one page for  question responses and one for exercise, total 3 pages with APA format in text and separate references without plagiarism and quality work in next 48 hours.