Business Intelligence And Data Mining Techniques
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Data Mining For Business Analytics
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Author : Galit Shmueli
language : en
Publisher: John Wiley & Sons
Release Date : 2019-10-14
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 2019-10-14 with Mathematics categories.
Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python presents an applied approach to data mining concepts and methods, using Python software for illustration Readers will learn how to implement a variety of popular data mining algorithms in Python (a free and open-source software) to tackle business problems and opportunities. This is the sixth version of this successful text, and the first using Python. It covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, recommender systems, clustering, text mining and network analysis. It also includes: A new co-author, Peter Gedeck, who brings both experience teaching business analytics courses using Python, and expertise in the application of machine learning methods to the drug-discovery process A new section on ethical issues in data mining Updates and new material based on feedback from instructors teaching MBA, undergraduate, diploma and executive courses, and from their students More than a dozen case studies demonstrating applications for the data mining techniques described End-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presented A companion website with more than two dozen data sets, and instructor materials including exercise solutions, PowerPoint slides, and case solutions Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python is an ideal textbook for graduate and upper-undergraduate level courses in data mining, predictive analytics, and business analytics. This new edition is also an excellent reference for analysts, researchers, and practitioners working with quantitative methods in the fields of business, finance, marketing, computer science, and information technology. “This book has by far the most comprehensive review of business analytics methods that I have ever seen, covering everything from classical approaches such as linear and logistic regression, through to modern methods like neural networks, bagging and boosting, and even much more business specific procedures such as social network analysis and text mining. If not the bible, it is at the least a definitive manual on the subject.” —Gareth M. James, University of Southern California and co-author (with Witten, Hastie and Tibshirani) of the best-selling book An Introduction to Statistical Learning, with Applications in R
Business Intelligence And Data Mining
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Author : Anil K. Maheshwari
language : en
Publisher:
Release Date : 2014-12-30
Business Intelligence And Data Mining written by Anil K. Maheshwari and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-30 with Business & Economics categories.
Data Analytics and Data-based Decision-making are hot topics now. Big Data has entered the common parlance. Many kinds of data are generated by business, social media, machines, and more. Organizations have a choice: they can be buried under the avalanche of data, or they can do something with it to increase competitive advantage. A new field of Data Science is born, and Data Scientist has been called the sexiest job of the decade. Students across a variety of academic departments, including business, computer science, statistics, and engineering are attracted to the idea of discovering new insights and ideas from data. This is a proposal for a short and lucid book on this whole area. It is designed to provide a student with the intuition behind this evolving area, along with a solid toolset of the major data mining techniques and platforms, all within a single semester- or quarter-long course.
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.
Business Intelligence And Data Mining Techniques
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Author : Dwaipayan Sethi
language : en
Publisher: Educohack Press
Release Date : 2025-02-20
Business Intelligence And Data Mining Techniques written by Dwaipayan Sethi and has been published by Educohack Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-20 with Business & Economics categories.
"Business Intelligence and Data Mining Techniques" is a comprehensive guide that explores the world of data analysis and data-driven decision-making. In an era where big data is ubiquitous, businesses, social media, machines, and more generate vast amounts of data. Organizations face a choice: be overwhelmed by data or harness it for a competitive advantage. This book aims to demystify data science, a field that has gained immense popularity and is now considered one of the most desirable careers. Designed to provide students with an understanding of data mining and business intelligence, the book covers essential techniques and platforms within a semester or quarter course. It highlights the importance of transforming raw data into meaningful, actionable insights. Data engineers use software to identify patterns, analyze consumer behavior, compare datasets, and optimize strategies, sales, and marketing campaigns. While data mining, data analysis, and business intelligence are often used interchangeably, this book clarifies their differences. Data mining involves extracting information from large datasets, while data analysis focuses on finding patterns in that information, including exploration, cleaning, transformation, and modeling. The ultimate goal of this book is to guide readers in discovering insights, drawing conclusions, and making informed decisions.
Data Mining For Business Applications
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Author : Longbing Cao
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-10-03
Data Mining For Business Applications written by Longbing Cao and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-10-03 with Computers categories.
Data Mining for Business Applications presents the state-of-the-art research and development outcomes on methodologies, techniques, approaches and successful applications in the area. The contributions mark a paradigm shift from “data-centered pattern mining” to “domain driven actionable knowledge discovery” for next-generation KDD research and applications. The contents identify how KDD techniques can better contribute to critical domain problems in theory and practice, and strengthen business intelligence in complex enterprise applications. The volume also explores challenges and directions for future research and development in the dialogue between academia and business.
Data Mining For Business Intelligence
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Author : Galit Shmueli
language : en
Publisher: Wiley-Interscience
Release Date : 2008-03-14
Data Mining For Business Intelligence written by Galit Shmueli and has been published by Wiley-Interscience this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-03-14 with Mathematics categories.
This set contains: 9780470084854 Data Mining for Business Intelligence: Concepts, Techniques, and Applications in Microsoft Office Excel(R) with XL Miner(TM) by Galit Shmueli, Nitin R. Patel, Peter C. Bruce and 9780470074718 Making Sense of Data by Glenn J. Myatt
Fundamentals Of Business Intelligence
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Author : Wilfried Grossmann
language : en
Publisher: Springer
Release Date : 2015-06-02
Fundamentals Of Business Intelligence written by Wilfried Grossmann and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-02 with Computers categories.
This book presents a comprehensive and systematic introduction to transforming process-oriented data into information about the underlying business process, which is essential for all kinds of decision-making. To that end, the authors develop step-by-step models and analytical tools for obtaining high-quality data structured in such a way that complex analytical tools can be applied. The main emphasis is on process mining and data mining techniques and the combination of these methods for process-oriented data. After a general introduction to the business intelligence (BI) process and its constituent tasks in chapter 1, chapter 2 discusses different approaches to modeling in BI applications. Chapter 3 is an overview and provides details of data provisioning, including a section on big data. Chapter 4 tackles data description, visualization, and reporting. Chapter 5 introduces data mining techniques for cross-sectional data. Different techniques for the analysis of temporal data are then detailed in Chapter 6. Subsequently, chapter 7 explains techniques for the analysis of process data, followed by the introduction of analysis techniques for multiple BI perspectives in chapter 8. The book closes with a summary and discussion in chapter 9. Throughout the book, (mostly open source) tools are recommended, described and applied; a more detailed survey on tools can be found in the appendix, and a detailed code for the solutions together with instructions on how to install the software used can be found on the accompanying website. Also, all concepts presented are illustrated and selected examples and exercises are provided. The book is suitable for graduate students in computer science, and the dedicated website with examples and solutions makes the book ideal as a textbook for a first course in business intelligence in computer science or business information systems. Additionally, practitioners and industrial developers who are interested in the concepts behind business intelligence will benefit from the clear explanations and many examples.
Business Intelligence Techniques
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Author : Murugan Anandarajan
language : en
Publisher: Springer Science & Business Media
Release Date : 2004
Business Intelligence Techniques written by Murugan Anandarajan and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Business & Economics categories.
Modern businesses generate huge volumes of accounting data on a daily basis. The recent advancements in information technology have given organizations the ability to capture and store these data in an efficient and effective manner. However, there is a widening gap between this data storage and usage of the data. Business intelligence techniques can help an organization obtain and process relevant accounting data quickly and cost efficiently. Such techniques include, query and reporting tools, online analytical processing (OLAP), statistical analysis, text mining, data mining, and visualization. Business Intelligence Techniques is a compilation of chapters written by experts in the various areas. While these chapters stand of their own, taken together they provide a comprehensive overview of how to exploit accounting data in the business environment.
Data Mining For Business Analytics
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Author : Galit Shmueli
language : en
Publisher: John Wiley & Sons
Release Date : 2016-05-09
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 2016-05-09 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.
Big Data And Business Analytics
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Author : Jay Liebowitz
language : en
Publisher: CRC Press
Release Date : 2016-04-19
Big Data And Business Analytics written by Jay Liebowitz and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-19 with Business & Economics categories.
"The chapters in this volume offer useful case studies, technical roadmaps, lessons learned, and a few prescriptions todo this, avoid that.'"-From the Foreword by Joe LaCugna, Ph.D., Enterprise Analytics and Business Intelligence, Starbucks Coffee CompanyWith the growing barrage of "big data," it becomes vitally important for organizations to mak