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Saturday, July 25, 2020 | History

7 edition of Data Mining for Business Intelligence found in the catalog.

Data Mining for Business Intelligence

Concepts, Techniques, and Applications in Microsoft Office Excel with XLMiner

by Galit Shmueli

  • 244 Want to read
  • 8 Currently reading

Published by Wiley-Interscience .
Written in English


The Physical Object
Number of Pages279
ID Numbers
Open LibraryOL7595764M
ISBN 100470084855
ISBN 109780470084854

  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 /5(56).   As well as teaching courses in Operations Research and Business Intelligence, Professor Vercellis is director of the research group MOLD (Mathematical Modeling, Optimization, Learning from Data). He has written four book in Italian, contributed to numerous other books, and has had many papers published in a variety of international journals.

Access to the datasets is restricted to registered users only. Registered users will see the datasets attached : XLMiner's name changed to Analytic Solver Data Mining in This document describes the resulting changes to the book examples and register click here. The Role of Data Mining for Business Intelligence in Knowledge Management: /ch This chapter introduces the role of Data Mining (DM) for Business Intelligence (BI) in Knowledge Management (KM), thus explaining the concept of KM, BI, andCited by:

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. Instructor materials include Instructor SlidesSolutions for the book exercises and casesExtra Problems and SolutionsChapter Example Files (data and analyses)Access to XLMinerList of datasets and uses (contributed by Prof. Susan Palocsay)To gain access to these instructor materials:Please send us official proof that the students in your class are required to purchase the book.


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Data Mining for Business Intelligence by Galit Shmueli Download PDF EPUB FB2

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 by: 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 Cited by: : Data Mining for Business Intelligence: Concepts, Techniques, and Applications in Microsoft Office Excel with XLMiner (): Galit Shmueli, Nitin R.

Patel, Peter C. Bruce: Books/5(9). From the Back Cover. 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, Cited by: Kudyba and Hoptroff have demonstrated one of the true 'value added' benefits to this electronic world we live in: technology enhanced business intelligence.

As technology aids the processing of information, Data Mining continues to play a large role in delivering information and analysis to enhance by: 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. XLMiner, 3rd Edition () XLMiner, 2nd Edition () XLMiner, 1st Edition () We're at a University Near You. This textbook is used at over universities, colleges, and business schools around the world, including MIT Sloan, Yale School of Management, Caltech, UMD, Cornell, Duke, McGill, HKUST, ISB, KAIST and hundreds of others.

Data Mining has become an essential tool for any enterprise that collects, stores and processes data as part of its operations. This book is ideal for business users, data analysts, business analysts, business intelligence and data warehousing professionals and for anyone who wants to learn Data Mining.

You’ll be able to: 1. Forecasting Analytics. Practical Time Series Forecasting with R: A Hands-On Guide is the ideal forecasting textbook for Business Analytics, MBA, Executive MBA, and Data Analytics programs: Perfect balance of theory & practice.

Concise and accessible exposition. "Data Mining for Business Intelligence," Second Edition is an excellent book for courses on data mining, forecasting, and decision support systems at /5. Data Mining for Business Intelligence: Concepts, Techniques, and Applications in Microsoft Office Excel with XLMiner.

" full of vivid and thought-provoking anecdotes needs to be read by anyone with a serious interest in research and marketing.". Major data sets, such as the Charles Book Club Case data used in chap are described in chapter Shmueli et al.

have done a wonderful job in presenting the field of data mining, and the significant techniques used for the classification and analysis of real-world data. 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. 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/5(56).

Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner, Third Editionpresents 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.

Helpful Books Decision Trees for Business Intelligence and Data Mining: Using SAS Enterprise Miner, published by SAS Press. Using SAS Enterprise Miner, this book illustrates the application and operation of decision trees in business intelligence, data mining, business.

Facts is your complete guide to Business Intelligence. In this book, you will learn topics such as Business Analytics and Data Visualization, Data, Text, and Web Mining, Business Performance Management, and Neural Networks for Data Mining plus much more. With Author: CTI Reviews.

Book Description. Data Mining for Business Intelligence, Second Edition uses real data and actual cases to illustrate the applicability of data mining (DM) intelligence in the development of successful business models.

Featuring complimentary access to XLMiner®, the Microsoft Office Excel® add-in, this book allows readers to follow along and implement algorithms at their own speed, with a.

Galit Shmueli is Distinguished Professor at the Institute of Service Science, National Tsing Hua University, Taiwan. She is co-author of the best-selling textbook Data Mining for Business Analytics, among other books and numerous publications in top journals.

She has designed and instructed courses on forecasting, data mining, statistics and other data analytics topics at. 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. Data Mining for Business Intelligence, Second Edition uses real data and actual cases to illustrate the applicability of data mining (DM) intelligence in the development of successful business models.

Featuring complimentary access to XLMiner, the Microsoft Office Excel add-in, this book allows readers to follow along and implement algorithms.Data Mining and Business Intelligence: A Guide to Productivity provides an overview of data mining technology and how it is applied in a business environment.

It describes the corresponding data mining methodologies that are used to solve a variety of business problems which enhance firm-level efficiency in a less technical, more managerial style. 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 Price: $