Data Mining for Business Analytics

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  • Author : Galit Shmueli
  • Publisher : John Wiley & Sons
  • Pages : 560 pages
  • ISBN : 1118729277
  • Rating : /5 from reviews
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Download or Read online Data Mining for Business Analytics full in PDF, ePub and kindle. this book written by Galit Shmueli and published by John Wiley & Sons which was released on 18 April 2016 with total page 560 pages. We cannot guarantee that Data Mining for Business Analytics book is available in the library, click Get Book button and read full online book in your kindle, tablet, IPAD, PC or mobile whenever and wherever You Like. Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner®, Third Edition presents an applied approach to data mining and predictive analytics with clear exposition, hands-on exercises, and real-life case studies. Readers will work with all of the standard data mining methods using the Microsoft® Office Excel® add-in XLMiner® to develop predictive models and learn how to obtain business value from Big Data. Featuring updated topical coverage on text mining, social network analysis, collaborative filtering, ensemble methods, uplift modeling and more, the Third Edition also includes: Real-world examples to build a theoretical and practical understanding of key data mining methods End-of-chapter exercises that help readers better understand the presented material Data-rich case studies to illustrate various applications of data mining techniques Completely new chapters on social network analysis and text mining A companion site with additional data sets, instructors material that include solutions to exercises and case studies, and Microsoft PowerPoint® slides https://www.dataminingbook.com Free 140-day license to use XLMiner for Education software Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner®, Third Edition is an ideal textbook for upper-undergraduate and graduate-level courses as well as professional programs on data mining, predictive modeling, and Big Data analytics. The new edition is also a unique reference for analysts, researchers, and practitioners working with predictive analytics in the fields of business, finance, marketing, computer science, and information technology. Praise for the Second 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 "Excellent choice for business analysts...The book is a perfect fit for its intended audience." – Keith McCormick, Consultant and Author of SPSS Statistics For Dummies, Third Edition and SPSS Statistics for Data Analysis and Visualization Galit Shmueli, PhD, is Distinguished Professor at National Tsing Hua University’s Institute of Service Science. She has designed and instructed data mining courses since 2004 at University of Maryland, Statistics.com, The Indian School of Business, and National Tsing Hua University, Taiwan. Professor Shmueli is known for her research and teaching in business analytics, with a focus on statistical and data mining methods in information systems and healthcare. She has authored over 70 journal articles, books, textbooks and book chapters. Peter C. Bruce is President and Founder of the Institute for Statistics Education at www.statistics.com. He has written multiple journal articles and is the developer of Resampling Stats software. He is the author of Introductory Statistics and Analytics: A Resampling Perspective, also published by Wiley. Nitin R. Patel, PhD, is Chairman and cofounder of Cytel, Inc., based in Cambridge, Massachusetts. A Fellow of the American Statistical Association, Dr. Patel has also served as a Visiting Professor at the Massachusetts Institute of Technology and at Harvard University. He is a Fellow of the Computer Society of India and was a professor at the Indian Institute of Management, Ahmedabad for 15 years.

Data Mining for Business Analytics

Data Mining for Business Analytics
  • Author : Galit Shmueli,Peter C. Bruce,Nitin R. Patel
  • Publisher : John Wiley & Sons
  • Release : 18 April 2016
GET THIS BOOK Data Mining for Business Analytics

Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner®, Third Edition presents an applied approach to data mining and predictive analytics with clear exposition, hands-on exercises, and real-life case studies. Readers will work with all of the standard data mining methods using the Microsoft® Office Excel® add-in XLMiner® to develop predictive models and learn how to obtain business value from Big Data. Featuring updated topical coverage on text mining, social network analysis, collaborative filtering, ensemble methods, uplift modeling

Data Mining for Business Analytics

Data Mining for Business Analytics
  • Author : Galit Shmueli,Peter C. Bruce,Peter Gedeck,Nitin R. Patel
  • Publisher : John Wiley & Sons
  • Release : 05 November 2019
GET THIS BOOK Data Mining for Business Analytics

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,

Data Mining and Business Analytics with R

Data Mining and Business Analytics with R
  • Author : Johannes Ledolter
  • Publisher : John Wiley & Sons
  • Release : 28 May 2013
GET THIS BOOK Data Mining and Business Analytics with R

Collecting, analyzing, and extracting valuable information froma large amount of data requires easily accessible, robust,computational and analytical tools. Data Mining and BusinessAnalytics with R utilizes the open source software R for theanalysis, exploration, and simplification of large high-dimensionaldata sets. As a result, readers are provided with the neededguidance to model and interpret complicated data and become adeptat building powerful models for prediction and classification. Highlighting both underlying concepts and practicalcomputational skills, Data Mining and Business Analytics withR begins with

Data Mining for Business Intelligence

Data Mining for Business Intelligence
  • Author : Galit Shmueli,Nitin R. Patel,Peter C. Bruce
  • Publisher : Wiley-Interscience
  • Release : 18 January 2022
GET THIS BOOK Data Mining for Business Intelligence

Learn how to develop models for classification, prediction, and customer segmentation with the help of Data Mining for Business Intelligence In today's world, businesses are becoming more capable of accessing their ideal consumers, and an understanding of data mining contributes to this success. Data Mining for Business Intelligence, which was developed from a course taught at the Massachusetts Institute of Technology's Sloan School of Management, and the University of Maryland's Smith School of Business, uses real data and actual cases

Real World Data Mining

Real World Data Mining
  • Author : Dursun Delen
  • Publisher : FT Press
  • Release : 16 December 2014
GET THIS BOOK Real World Data Mining

Use the latest data mining best practices to enable timely, actionable, evidence-based decision making throughout your organization! Real-World Data Mining demystifies current best practices, showing how to use data mining to uncover hidden patterns and correlations, and leverage these to improve all aspects of business performance. Drawing on extensive experience as a researcher, practitioner, and instructor, Dr. Dursun Delen delivers an optimal balance of concepts, techniques and applications. Without compromising either simplicity or clarity, he provides enough technical depth to

Customer and Business Analytics

Customer and Business Analytics
  • Author : Daniel S. Putler,Robert E. Krider
  • Publisher : CRC Press
  • Release : 15 September 2015
GET THIS BOOK Customer and Business Analytics

Customer and Business Analytics: Applied Data Mining for Business Decision Making Using R explains and demonstrates, via the accompanying open-source software, how advanced analytical tools can address various business problems. It also gives insight into some of the challenges faced when deploying these tools. Extensively classroom-tested, the text is ideal for students in customer and business analytics or applied data mining as well as professionals in small- to medium-sized organizations. The book offers an intuitive understanding of how different analytics

Data Mining for Business Applications

Data Mining for Business Applications
  • Author : Longbing Cao,Philip S. Yu,Chengqi Zhang,Huaifeng Zhang
  • Publisher : Springer Science & Business Media
  • Release : 03 October 2008
GET THIS BOOK Data Mining for Business Applications

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

Getting Started with Business Analytics

Getting Started with Business Analytics
  • Author : David Roi Hardoon,Galit Shmueli
  • Publisher : CRC Press
  • Release : 26 March 2013
GET THIS BOOK Getting Started with Business Analytics

Assuming no prior knowledge or technical skills, Getting Started with Business Analytics: Insightful Decision-Making explores the contents, capabilities, and applications of business analytics. It bridges the worlds of business and statistics and describes business analytics from a non-commercial standpoint. The authors demystify the main concepts and terminologies and give many examples of real-world applications. The first part of the book introduces business data and recent technologies that have promoted fact-based decision-making. The authors look at how business intelligence differs from

Integration of Data Mining in Business Intelligence Systems

Integration of Data Mining in Business Intelligence Systems
  • Author : Azevedo, Ana
  • Publisher : IGI Global
  • Release : 30 September 2014
GET THIS BOOK Integration of Data Mining in Business Intelligence Systems

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,

Guide to Data Mining for Business Analytics

Guide to Data Mining for Business Analytics
  • Author : Vincent Bronson
  • Publisher : Unknown
  • Release : 04 December 2020
GET THIS BOOK Guide to Data Mining for Business Analytics

A business is an entity that is formed in order to carry out activities for the purpose of generating revenue. It involves managing people to organize and maintain a collective effort toward accomplishing a particular creative or productive goal. The term may refer to general commercial, professional, or industrial activity. The singular usage of the term refers to a particular company or corporation, wherein individuals organize based on expertise and skills to bring about social or technological advancement. The generalized

Integration Challenges for Analytics Business Intelligence and Data Mining

Integration Challenges for Analytics  Business Intelligence  and Data Mining
  • Author : Azevedo, Ana,Santos, Manuel Filipe
  • Publisher : IGI Global
  • Release : 11 December 2020
GET THIS BOOK Integration Challenges for Analytics Business Intelligence and Data Mining

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

Business Intelligence in Plain Language

Business Intelligence in Plain Language
  • Author : Jeremy M. Kolb
  • Publisher : CreateSpace
  • Release : 21 May 2013
GET THIS BOOK Business Intelligence in Plain Language

One day a man walked into Asgard Inc. and changed the company forever. Unlike anyone who came before, he remembered and understood data as naturally as a fish swims in water. The CEO was shocked at how well the man knew the company. He started posing questions to this man. Who are my best customers? Why is this product struggling? Where is my greatest growth happening? The man answered these and more. Using his understanding of data, he identified key

Predictive Analytics

Predictive Analytics
  • Author : Dursun Delen
  • Publisher : FT Press Analytics
  • Release : 30 October 2020
GET THIS BOOK Predictive Analytics

In Predictive Analytics: Data Mining, Machine Learning and Data Science for Practitioners, Dr. Dursun Delen illuminates state-of-the-art best practices for predictive analytics for students. Using predictive analytics techniques, students can uncover hidden patterns and correlations in their data, and leverage this insight to improve a wide range of business decisions. Delen's holistic approach covers all this, and more: Data mining processes, methods, and techniques The role and management of data Predictive analytics tools and metrics Techniques for text and web

Getting Started with Business Analytics

Getting Started with Business Analytics
  • Author : Galit Shmueli
  • Publisher : Unknown
  • Release : 18 January 2022
GET THIS BOOK Getting Started with Business Analytics

Assuming no prior knowledge or technical skills, Getting Started with Business Analytics: Insightful Decision-Making explores the contents, capabilities, and applications of business analytics. It bridges the worlds of business and statistics and describes business analytics from a non-commercial standpoint. The authors demystify the main concepts and terminologies and give many examples of real-world applications. The first part of the book introduces business data and recent technologies that have promoted fact-based decision-making. The authors look at how business intelligence differs from