Business Intelligence And Data Mining
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Data Mining For Business Intelligence
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Author : Galit Shmueli
language : en
Publisher: John Wiley & Sons
Release Date : 2011-09-28
Data Mining For Business Intelligence written by Galit Shmueli and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-09-28 with Mathematics categories.
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 Challenges For Analytics Business Intelligence And Data Mining
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Author : Azevedo, Ana
language : en
Publisher: IGI Global
Release Date : 2020-12-11
Integration Challenges For Analytics Business Intelligence And Data Mining written by Azevedo, Ana and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-11 with Computers categories.
As technology continues to advance, it is critical for businesses to implement systems that can support the transformation of data into information that is crucial for the success of the company. Without the integration of data (both structured and unstructured) mining in business intelligence systems, invaluable knowledge is lost. However, there are currently many different models and approaches that must be explored to determine the best method of integration. Integration Challenges for Analytics, Business Intelligence, and Data Mining is a relevant academic book that provides empirical research findings on increasing the understanding of using data mining in the context of business intelligence and analytics systems. Covering topics that include big data, artificial intelligence, and decision making, this book is an ideal reference source for professionals working in the areas of data mining, business intelligence, and analytics; data scientists; IT specialists; managers; researchers; academicians; practitioners; and graduate students.
Business Intelligence And Data Mining
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Author : Anil Maheshwari
language : en
Publisher: Business Expert Press
Release Date : 2014-12-31
Business Intelligence And Data Mining written by Anil Maheshwari and has been published by Business Expert Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-31 with Business & Economics categories.
“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.
Decision Trees For Business Intelligence And Data Mining
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Author : Barry De Ville
language : en
Publisher: SAS Press
Release Date : 2006
Decision Trees For Business Intelligence And Data Mining written by Barry De Ville and has been published by SAS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Business & Economics categories.
This example-driven guide illustrates the application and operation of decision trees in data mining, business intelligence, business analytics, prediction, and knowledge discovery. It explains in detail the use of decision trees as a data mining technique and how this technique complements and supplements other business intelligence applications.
Data Mining For Business Intelligence
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Author : Galit Shmueli
language : en
Publisher: John Wiley & Sons
Release Date : 2008-09
Data Mining For Business Intelligence written by Galit Shmueli and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-09 with categories.
Market_Desc: As a textbook or supplement for courses in data mining, data warehousing, business intelligence, and/or decision support systems at the upper undergraduate or beginning graduate (MS, Ph.D., or MBA) levels in departments of mathematics and statistics, computer science, information technology, engineering, or business; as a reference guide for professionals in related fields. Special Features: · The book s greatest strength lies in its presentation of hands-on, business-oriented applications, complete with real data sets and cases.· The chapters have been written with flexibility in mind so the user and/or instructor can navigate throughout the book as he or she chooses.· The excellent mix between mathematical rigor and readability make the book ideal for multiple readerships.· The software system-of-choice, XLMinerTM, is a familiar and easy-to-use tool for business analysts, consultants, and students since it is based on the popular Excel® spreadsheet concept. It provides a comprehensive set of data mining models and algorithms that includes statistical, machine learning and database methods - at no additional cost to the purchaser!· There are plentiful exercises and examples to motivate learning and understanding. About The Book: This book arose out of a data mining course at MIT s Sloan School of Management. Preparation for the course revealed that there are a number of excellent books on the business context of data mining, but their coverage of the statistical and machine learning algorithms and theoretical underpinnings is not sufficiently detailed to provide a practical guide for users who possess the raw skills and tools to analyze data. This book is intended for the business student (and practitioner) of data mining techniques, and the goal is threefold: (1) to provide both a theoretical and practical understanding of the key methods of classification, prediction, reduction and exploration that are at the heart of data mining; (2) to provide a business decision-making context for these methods; and (3) using real business cases and data, to illustrate the application and interpretation of these methods. The book employs the use of an Excel® add-in, XLMinerTM, at no cost to registered instructors, in order to illustrate and interpret the various data sets that are presented throughout. Real-life business cases are also presented so that readers can implement algorithms with a very low learning hurdle.
Data Mining For Business Analytics
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Author : Galit Shmueli
language : en
Publisher: John Wiley & Sons
Release Date : 2016-05-11
Data Mining For Business Analytics written by Galit Shmueli and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-05-11 with Mathematics categories.
Data Mining for Business Analytics: Concepts, Techniques, and Applications with JMP Pro® presents an applied and interactive approach to data mining. Featuring hands-on applications with JMP Pro®, a statistical package from the SAS Institute, the book uses engaging, real-world examples to build a theoretical and practical understanding of key data mining methods, especially predictive models for classification and prediction. Topics include data visualization, dimension reduction techniques, clustering, linear and logistic regression, classification and regression trees, discriminant analysis, naive Bayes, neural networks, uplift modeling, ensemble models, and time series forecasting. Data Mining for Business Analytics: Concepts, Techniques, and Applications with JMP Pro® also includes: Detailed summaries that supply an outline of key topics at the beginning of each chapter End-of-chapter examples and exercises that allow readers to expand their comprehension of the presented material Data-rich case studies to illustrate various applications of data mining techniques A companion website with over two dozen data sets, exercises and case study solutions, and slides for instructors www.dataminingbook.com Data Mining for Business Analytics: Concepts, Techniques, and Applications with JMP Pro® is an excellent textbook for advanced undergraduate and graduate-level courses on data mining, predictive analytics, and business analytics. The book is also a one-of-a-kind resource for data scientists, analysts, researchers, and practitioners working with analytics in the fields of management, finance, marketing, information technology, healthcare, education, and any other data-rich field.
Data Mining Business Intelligence
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Author : Mohit Thakkar
language : en
Publisher: Mohit Thakkar
Release Date : 2018-01-12
Data Mining Business Intelligence written by Mohit Thakkar and has been published by Mohit Thakkar this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-12 with Computers categories.
It often happens that when we try to study a subject for some examination or a job interview, we just don’t find the right content. The problem with the reference books is that they are too descriptive for last moment studies. Whereas the problem with local publications is that they are inaccurate as compared to the reference books. This particular book encapsulates the subject notes on Data Mining & Business Intelligence with the combined benefits of reference books & local publications. It has the accuracy of a reference book as well as the abstraction of a local publication. The author studied the subject from various sources such as web lectures, reference books, online tutorials & so on. After having a thorough understanding of the subject, the author compiled this book for an easy understanding of the subject. This book presents the content in the form of question & answers, with utmost simplicity of language, and in an abstract manner so that it can be used for last moment studies. This book can be used by: Ø Students to prepare for their examinations Ø Professionals to prepare for job interviews. Ø Individuals willing to have a basic understanding of the domain: Data Mining & Business Intelligence. Happy Reading! 😄
Integration Of Data Mining In Business Intelligence Systems
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Author : Azevedo, Ana
language : en
Publisher: IGI Global
Release Date : 2014-09-30
Integration Of Data Mining In Business Intelligence Systems written by Azevedo, Ana and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-30 with Computers categories.
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 A Guide To Productivity
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Author : Hoptroff, Richard
language : en
Publisher: IGI Global
Release Date : 2000-07-01
Data Mining And Business Intelligence A Guide To Productivity written by Hoptroff, Richard and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-07-01 with Computers categories.
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).
Utilizing Big Data Paradigms For Business Intelligence
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Author : Darmont, Jérôme
language : en
Publisher: IGI Global
Release Date : 2018-08-10
Utilizing Big Data Paradigms For Business Intelligence written by Darmont, Jérôme and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-10 with Business & Economics categories.
Because efficient compilation of information allows managers and business leaders to make the best decisions for the financial solvency of their organizations, data analysis is an important part of modern business administration. Understanding the use of analytics, reporting, and data mining in everyday business environments is imperative to the success of modern businesses. Utilizing Big Data Paradigms for Business Intelligence is a pivotal reference source that provides vital research on how to address the challenges of data extraction in business intelligence using the five “Vs” of big data: velocity, volume, value, variety, and veracity. This book is ideally designed for business analysts, investors, corporate managers, entrepreneurs, and researchers in the fields of computer science, data science, and business intelligence.