Data Mining for Business Intelligence

Author: Galit Shmueli
Publisher: John Wiley and Sons
ISBN: 1118126041
Format: PDF, Docs
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Praise for the First Edition " full of vivid and thought-provoking anecdotes needs to be read by anyone with a serious interest in research and marketing." —Research magazine "Shmueli et al. have done a wonderful job in presenting the field of data mining a welcome addition to the literature." —computingreviews.com Incorporating a new focus on data visualization and time series forecasting, Data Mining for Business Intelligence, Second Edition continues to supply insightful, detailed guidance on fundamental data mining techniques. This new edition guides readers through the use of the Microsoft Office Excel add-in XLMiner for developing predictive models and techniques for describing and finding patterns in data. From clustering customers into market segments and finding the characteristics of frequent flyers to learning what items are purchased with other items, the authors use interesting, real-world examples to build a theoretical and practical understanding of key data mining methods, including classification, prediction, and affinity analysis as well as data reduction, exploration, and visualization. The Second Edition now features: Three new chapters on time series forecasting, introducing popular business forecasting methods including moving average, exponential smoothing methods; regression-based models; and topics such as explanatory vs. predictive modeling, two-level models, and ensembles A revised chapter on data visualization that now features interactive visualization principles and added assignments that demonstrate interactive visualization in practice Separate chapters that each treat k-nearest neighbors and Naïve Bayes methods Summaries at the start of each chapter that supply an outline of key topics The book includes access to XLMiner, allowing readers to work hands-on with the provided data. Throughout the book, applications of the discussed topics focus on the business problem as motivation and avoid unnecessary statistical theory. Each chapter concludes with exercises that allow readers to assess their comprehension of the presented material. The final chapter includes a set of cases that require use of the different data mining techniques, and a related Web site features data sets, exercise solutions, PowerPoint slides, and case solutions. Data Mining for Business Intelligence, Second Edition is an excellent book for courses on data mining, forecasting, and decision support systems at the upper-undergraduate and graduate levels. It is also a one-of-a-kind resource for analysts, researchers, and practitioners working with quantitative methods in the fields of business, finance, marketing, computer science, and information technology.

Integration of Data Mining in Business Intelligence Systems

Author: Azevedo, Ana
Publisher: IGI Global
ISBN: 1466664789
Format: PDF, Mobi
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Uncovering and analyzing data associated with the current business environment is essential in maintaining a competitive edge. As such, making informed decisions based on this data is crucial to managers across industries. Integration of Data Mining in Business Intelligence Systems investigates the incorporation of data mining into business technologies used in the decision making process. Emphasizing cutting-edge research and relevant concepts in data discovery and analysis, this book is a comprehensive reference source for policymakers, academicians, researchers, students, technology developers, and professionals interested in the application of data mining techniques and practices in business information systems.

Data Mining and Business Intelligence

Author: Stephan Kudyba
Publisher: IGI Global
ISBN: 9781930708037
Format: PDF
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Annotation Provides an overview of data mining technology and how it is applied in a business environment. Material is not written in a technical style, but rather addresses the applied methodology behind implementing data mining techniques in the corporate environment. Explains how the technology evolved, overviews the methodologies that comprise the data mining spectrum, and looks at everyday business applications for data mining, in areas such as marketing and advertising promotions and pricing policies using econometric-based modeling, and using the Internet to help improve an organization's performance. Kudyba is an economic consultant. Hoptroff is an independent consultant with experience in data mining software. Annotation c. Book News, Inc., Portland, OR (booknews.com).

Microsoft Data Mining

Author: Barry De Ville
Publisher: Digital Press
ISBN: 9781555582425
Format: PDF, ePub
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This guide teaches data mining from the perspective of IT professionals using Microsoft data management and e-commerce technologies. The book explains major new data mining capabilities in the forthcoming SQL Server 2000, Microsoft Commerce Server, and other products, and details the new Microsoft standard, "OLE DB for Data Mining".

Web Data Mining and Applications in Business Intelligence and Counter Terrorism

Author: Bhavani Thuraisingham
Publisher: CRC Press
ISBN: 9780203499511
Format: PDF, Mobi
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The explosion of Web-based data has created a demand among executives and technologists for methods to identify, gather, analyze, and utilize data that may be of value to corporations and organizations. The emergence of data mining, and the larger field of Web mining, has businesses lost within a confusing maze of mechanisms and strategies for obtaining and managing crucial intelligence. Web Data Mining and Applications in Business Intelligence and Counter-Terrorism responds by presenting a clear and comprehensive overview of Web mining, with emphasis on CRM and, for the first time, security and counter-terrorism applications. The tools and methods of Web mining are revealed in an easy-to-understand style, emphasizing the importance of practical, hands-on experience in the creation of successful e-business solutions. The author, a program director for Data and Applications Security at the National Science Foundations, details how both opportunities and dangers on the Web can be identified and managed. Armed with the knowledge contained in this book, businesses can collect and analyze Web-based data to help develop customer relationships, increase sales, and identify existing and potential threats. Organizations can apply these same Web mining techniques to battle the real and present danger of terrorism, demonstrating Web mining's critical role in the intelligence arsenal.

Business Intelligence

Author: Carlo Vercellis
Publisher: John Wiley & Sons
ISBN: 1119965470
Format: PDF
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Business intelligence is a broad category of applications and technologies for gathering, providing access to, and analyzing data for the purpose of helping enterprise users make better business decisions. The term implies having a comprehensive knowledge of all factors that affect a business, such as customers, competitors, business partners, economic environment, and internal operations, therefore enabling optimal decisions to be made. Business Intelligence provides readers with an introduction and practical guide to the mathematical models and analysis methodologies vital to business intelligence. This book: Combines detailed coverage with a practical guide to the mathematical models and analysis methodologies of business intelligence. Covers all the hot topics such as data warehousing, data mining and its applications, machine learning, classification, supply optimization models, decision support systems, and analytical methods for performance evaluation. Is made accessible to readers through the careful definition and introduction of each concept, followed by the extensive use of examples and numerous real-life case studies. Explains how to utilise mathematical models and analysis models to make effective and good quality business decisions. This book is aimed at postgraduate students following data analysis and data mining courses. Researchers looking for a systematic and broad coverage of topics in operations research and mathematical models for decision-making will find this an invaluable guide.

Business Intelligence and Data Mining

Author: Anil Maheshwari
Publisher: Business Expert Press
ISBN: 1631571214
Format: PDF, ePub, Docs
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“This book is a splendid and valuable addition to this subject. The whole book is well written and I have no hesitation to recommend that this can be adapted as a textbook for graduate courses in Business Intelligence and Data Mining.” Dr. Edi Shivaji, Des Moines, Iowa “As a complete novice to this area just starting out on a MBA course I found the book incredibly useful and very easy to follow and understand. The concepts are clearly explained and make it an easy task to gain an understanding of the subject matter.” -- Mr. Craig Domoney, South Africa. Business Intelligence and Data Mining is a conversational and informative book in the exploding area of Business Analytics. Using this book, one can easily gain the intuition about the area, along with a solid toolset of major data mining techniques and platforms. This book can thus be gainfully used as a textbook for a college course. It is also short and accessible enough for a busy executive to become a quasi-expert in this area in a couple of hours. Every chapter begins with a case-let from the real world, and ends with a case study that runs across the chapters.

Business Intelligence Data Mining and Optimization for Decision Making

Author: CTI Reviews
Publisher: Cram101 Textbook Reviews
ISBN: 1467215678
Format: PDF, ePub
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Facts101 is your complete guide to Business Intelligence, Data Mining and Optimization for Decision Making. In this book, you will learn topics such as as those in your book plus much more. With key features such as key terms, people and places, Facts101 gives you all the information you need to prepare for your next exam. Our practice tests are specific to the textbook and we have designed tools to make the most of your limited study time.

Data Mining and Market Intelligence

Author: Mustapha Akinkunmi
Publisher: Morgan & Claypool Publishers
ISBN: 1681733218
Format: PDF, Docs
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This book is written to address the issues relating to data gathering, data warehousing, and data analysis, all of which are useful when working with large amounts of data. Using practical examples of market intelligence, this book is designed to inspire and inform readers on how to conduct market intelligence by leveraging data and technology, supporting smart decision making. The book explains some suitable methodologies for data analysis that are based on robust statistical methods. For illustrative purposes, the author uses real-life data for all the examples in this book. In addition, the book discusses the concepts, techniques, and applications of digital media and mobile data mining. Hence, this book is a guide tool for policy makers, academics, and practitioners whose areas of interest are statistical inference, applied statistics, applied mathematics, business mathematics, quantitative techniques, and economic and social statistics.