68 )In lessons learned from the Target case, what legal warnings would you give another retailer using data mining for marketing? Answer: If you look at this practice from a legal perspective, you would conclude that Targe did not use any information that violates customer privacy; rather, they used transactional data that most every other retail chain is collecting and storing(and perhaps analyzing) about their customers. What was disturbing in this scenario was perhaps the targeted concept: pregnancy There are certain events or concepts that should be off limits or treated extremely cautiously, such as terminal disease, divorce, and bankruptcy Diff: 2 Page Ref: 238 69)List four myths associated with data mining Answer Data mining provides instant, crystal-ball-like predictions Data mining is not yet viable for business applications Data mining requires a separate, dedicated database Only those with advanced degrees can do data mining Data mining is only for large firms that have lots of customer data iff: 2 Page Ref: 239 70)List six common data mining mistakes Answer Selecting the wrong problem for data mining Ignoring what your sponsor thinks data mining is and what it really can and cannot do Leaving insufficient time for data preparation Looking only at aggregated results and not at individual records Being sloppy about keeping track of the data mining procedure and results Ignoring suspicious findings and quickly moving on Running mining algorithms repeatedly and blindly Believing everything you are told about the data Believing everything you are told about your own data mining analysi Measuring your results differently from the way your sponsor measures them Diff: 2 Page Ref: 239-240 Copyright o 2018 Pearson Education, Inc12 Copyright © 2018 Pearson Education, Inc. 68) In lessons learned from the Target case, what legal warnings would you give another retailer using data mining for marketing? Answer: If you look at this practice from a legal perspective, you would conclude that Target did not use any information that violates customer privacy; rather, they used transactional data that most every other retail chain is collecting and storing (and perhaps analyzing) about their customers. What was disturbing in this scenario was perhaps the targeted concept: pregnancy. There are certain events or concepts that should be off limits or treated extremely cautiously, such as terminal disease, divorce, and bankruptcy. Diff: 2 Page Ref: 238 69) List four myths associated with data mining. Answer: • Data mining provides instant, crystal-ball-like predictions. • Data mining is not yet viable for business applications. • Data mining requires a separate, dedicated database. • Only those with advanced degrees can do data mining. • Data mining is only for large firms that have lots of customer data. Diff: 2 Page Ref: 239 70) List six common data mining mistakes. Answer: • Selecting the wrong problem for data mining • Ignoring what your sponsor thinks data mining is and what it really can and cannot do • Leaving insufficient time for data preparation • Looking only at aggregated results and not at individual records • Being sloppy about keeping track of the data mining procedure and results • Ignoring suspicious findings and quickly moving on • Running mining algorithms repeatedly and blindly • Believing everything you are told about the data • Believing everything you are told about your own data mining analysis • Measuring your results differently from the way your sponsor measures them Diff: 2 Page Ref: 239-240