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This textbook presents a practical approach to predictive analytics for classroom learning. It focuses on using analytics to solve business problems and compares several different modeling techniques, all explained from examples using the SAS Enterprise Miner software. The authors demystify complex algorithms to show how they can be utilized and explained within the context of enhancing business opportunities. Each chapter includes an opening vignette that provides real-life example of how business analytics have been used in various aspects of organizations to solve issue or improve their results. A running case provides an example of a how to build and analyze a complex analytics model and utilize it to predict future outcomes. Focuses on how to use predictive analytic techniques to analyze historical data for the purpose of predicting future results; Takes an applied approach and focus on solving business problems using predictive analytics and features case studies and a variety of examples; Uses examples in SAS Enterprise Miner, one of world’s leading analytics software tools.

Telecommunication. --- Engineering. --- Data mining. --- Big data. --- Communications Engineering, Networks. --- Computational Intelligence. --- Data Mining and Knowledge Discovery. --- Big Data/Analytics. --- Data sets, Large --- Large data sets --- Data sets --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Construction --- Industrial arts --- Technology --- Electric communication --- Mass communication --- Telecom --- Telecommunication industry --- Telecommunications --- Communication --- Information theory --- Telecommuting --- Enterprise miner --- SAS Enterprise miner --- Electrical engineering. --- Computational intelligence. --- Intelligence, Computational --- Artificial intelligence --- Soft computing --- Electric engineering --- Engineering