ANSWERS TO END OF CHAPTER EXERCISES O C Teradata University Network and Other Hands-On Exercises Go to teradatauniversitynetwork. com. Using the site password your instructor provides, register for the site if you have not already previously registered. Log on and learn the content of the site. You will receive assignments related to this site Prepare a list of 20 items on the site that you think could be beneficial to you Student responses will vary 2. Go to the TUN site. Explore the Sports Analytics page, and summarize at least two applications of analytics in any sport of your choice Student responses will vary 3. Enter the TUN site, and select"Cases, Projects, and Assignments. Then select the case study Harrah's High Payoff from Customer Information. Answer the following questions about this case What information does the data mining generate? abcd How is this information helpful to management in decision making?(Be specific. List the types of data that are mined Is this a dss or BI application? Why? Student responses will and Goodhue). Read the paper, and answer the following questiong warehousing 4. Go to teradatauniversitynetwork com and find the paper titled" Data w Supports Corporate Strategy at First American Corporation"(by n wixom What were the drivers for the dW/BI project in the company? b. What strategic advantages were realized? What operational and tactical advantages were achieved? d. What were the critical success factors for the implementation? Student responses will vary 5.Gotohttp://analytics-magazine.org/issues/digitaleditionsandfindthe January/February 2012 edition titled"Special Issue: The Future of Healthcare Read the article"Predictive Analytics--Saving Lives and Lowering Medical Bills. Answer the following questions a. What problem is being addressed by applying pred ictive analytics? What is the fico medication adherence score? C. How is a prediction model trained to predict the FICO Medication Adherence Score HoH? Did the prediction model classify the fIco Medication adherence score? Copyright C2018 Pearson Education, Inc.17 Copyright © 2018Pearson Education, Inc. ANSWERS TO END OF CHAPTER EXERCISES   Teradata University Network and Other Hands-On Exercises 1. Go to teradatauniversitynetwork.com. Using the site password your instructor provides, register for the site if you have not already previously registered. Log on and learn the content of the site. You will receive assignments related to this site. Prepare a list of 20 items on the site that you think could be beneficial to you. Student responses will vary. 2. Go to the TUN site. Explore the Sports Analytics page, and summarize at least two applications of analytics in any sport of your choice. Student responses will vary. 3. Enter the TUN site, and select “Cases, Projects, and Assignments.” Then select the case study “Harrah’s High Payoff from Customer Information.” Answer the following questions about this case: a. What information does the data mining generate? b. How is this information helpful to management in decision making? (Be specific.) c. List the types of data that are mined. d. Is this a DSS or BI application? Why? Student responses will vary. 4. Go to teradatauniversitynetwork.com and find the paper titled “Data Warehousing Supports Corporate Strategy at First American Corporation” (by Watson, Wixom, and Goodhue). Read the paper, and answer the following questions: a. What were the drivers for the DW/BI project in the company? b. What strategic advantages were realized? c. What operational and tactical advantages were achieved? d. What were the critical success factors for the implementation? Student responses will vary. 5. Go to http://analytics-magazine.org/issues/digitaleditions and find the January/February 2012 edition titled “Special Issue: The Future of Healthcare.” Read the article “Predictive Analytics—Saving Lives and Lowering Medical Bills.” Answer the following questions: a. What problem is being addressed by applying predictive analytics? b. What is the FICO Medication Adherence Score? c. How is a prediction model trained to predict the FICO Medication Adherence Score HoH? Did the prediction model classify the FICO Medication Adherence Score?