Real-World Data Mining: Applied Business Analytics and Decision Making [Elektronisk resurs]Upplaga 1

Use New Data Mining Best Practices to Promote Timely, Actionable, Evidence-Based Decision Making A complete data mining framework: processes, methods, techniques, evaluation, tools, and more Up-to-date primers on text/web mining, sentiment analysis, and Big Data Demystifies complex concepts with easy tutorials and modern case studies For managers, analytics team members, certification candidates, and students To make the best possible decisions, you need insights you can only uncover through data mining and business analytics. Now, renowned expert Dr. Dursun Delen explains everything you need to capture and leverage these insights, whether youre part of an analytical team or you consume its outputs. Drawing on decades at the forefront of research and instruction in the field, Delen illuminates its core principles, best practices, and key applications in areas from marketing and finance to defense. He clarifies its dense jargon, shows how its technologies fit together, identifies obstacles to success, and helps you overcome them. His plain-English, step-by-step explanations demystify everything from workflows to algorithms. Best of all, he shares indispensable practical guidance for maximizing your effectiveness, every step of the way. As business becomes increasingly complex, decision-makers must act more rapidly and accurately based on the best available evidence. Modern data mining and analytics are indispensable for doing this. Real-World Data Mining introduces current best practices in these fields, showing how to uncover hidden patterns and correlations and systematically use your findings to improve decision making. Youll find broad and up-to-date coverage of data mining processes, methods, and techniques; effective data management techniques; tools and metrics; text and web mining; Big Data integration; and much more. Dr. Dursun Delen delivers an optimal balance of concepts, hands-on tutorials, and real-world application case studies--helping you learn from both successes and failures. Without compromising either simplicity or clarity, he provides enough technical depth to help you understand how data mining really works--and how to put it to work for you. Analytics: A practical, useful taxonomy Data mining: Converting data to information to knowledge Applications: From marketing to finance, healthcare to defense Processes and standards: KDD, CRISP-DM,SEMMA, and Six Sigma DMAIC Data and methods: Handling structured, unstructured, and semi-structured data Algorithms and statistics: Nearest neighbor, neural networks, SVMs Text analytics/mining: Sentiment analysis, natural language processing Big data: Volume, variety, velocity, veracity, variability, and value