Application Case 4.1: Visa Is Enhancing the Customer Experience While Reducing Fraud with Predictive Analytics and Data Mining

1. What challenges were Visa and the rest of the credit card industry facing?

2. How did Visa improve customer service while also improving retention of fraud?

3. What is in-memory analytics, and why was it necessary?

Application Case 4.2: Dell Is Staying Agile and Effective with Analytics in the 21st Century

1. What was the challenge Dell was facing that led to their analytics journey?

2. What solution did Dell develop and implement? What were the results?
3. As an analytics company itself, Dell has used its service offerings for its own business. Do you think it is easier or harder for a company to taste its own medicine? Explain.

Application Case 4.3: A Mine on Terrorist Funding

1. How can data mining be used to fight terrorism?

2. Do you think data mining, while essential for fighting terrorist cells, also jeopardizes individuals rights of privacy?

Application Case 4.4: Data Mining in Cancer Research

1. How can data mining be used for ultimately curing illnesses like cancer?

2. What do you think are the promises and major challenges for data miners in contributing to medical and biological research endeavors?

Application Case 4.5: Influence Health Uses Advanced Predictive Analytics to Focus on the Factors That Really Influence Peoples Healthcare Decisions

1. What did Influence Health do?

2. What were the challenges, the proposed solutions, and the obtained results?

3. How can data mining help companies in the healthcare industry (in ways other than the ones mentioned in this case)?

Application Case 4.6: Data Mining Goes to Hollywood: Predicting Financial Success of Movies

1. Why is it important for many Hollywood professionals to predict the financial success of movies?

2. How can data mining be used for predicting financial success of movies before the start of their production process?

3. How do you think Hollywood did, and perhaps still is performing, this task without the help of data mining tools and techniques?

Application Case 4.7: Predicting Customer Buying PatternsThe Target Story

1. What do you think about data mining and its implication for privacy? What is the threshold between discovery of knowledge and infringement of privacy?

2. Did Target go too far? Did it do anything illegal? What do you think Target should have done? What do you think Target should do next (quit these types of practices)?

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