PDF Ebook Data Mining for Business Intelligence: Concepts, Techniques, and Applications in Microsoft Office Excel with XLMiner
PDF Ebook Data Mining for Business Intelligence: Concepts, Techniques, and Applications in Microsoft Office Excel with XLMiner
As related to this referred publication, you may have understood why this publication is waited for. Yet, for you that are still interested of the reasons, you will certainly understand he reasons when you start to review guide. Looking at the cover of Data Mining For Business Intelligence: Concepts, Techniques, And Applications In Microsoft Office Excel With XLMiner and also check out title will lead you know why lots of people falling in love. Fond of guide that pertaining to the topic you are looking for can make you feel satisfied. This is exactly what will certainly make you load that wish.
Data Mining for Business Intelligence: Concepts, Techniques, and Applications in Microsoft Office Excel with XLMiner
PDF Ebook Data Mining for Business Intelligence: Concepts, Techniques, and Applications in Microsoft Office Excel with XLMiner
Have you found a brand-new publication to fulfil your vacations to review? Do you plan for looking it? When someone only have strategies to have holidays and also vacations to go with some people, there other who also look for the books to make use of the leisure time. It is not kind of hard ways to conquer this issue. Nowadays, the advanced modern technology is worried to assist you in doing anything.
It is also exactly what you can obtain from the internet connection. You are very easy to get everything there, specifically for looking the book. Data Mining For Business Intelligence: Concepts, Techniques, And Applications In Microsoft Office Excel With XLMiner as one of the referred book to read when vacations is additionally provided in the web site. We are the website that has many completed publication kinds and styles. Lots of books from numerous countries are offered. So, you will certainly not be hard to seek for more than a publication.
When accelerating as well as promoting this book we are also so sure that you can gain the lesson as well as understanding conveniently. Why? With your basic knowledge and also thoughts, your option to blend with the lessons supplied by this publication is extremely outstanding. You could discover the appropriate selection of exactly how today publication in this lesson is obtained. And also currently, when you are actually locate of this type of publication subject, you could get the data of guide in this rest.
If puzzled on how you can get the book, you could not should get confused anymore. This internet site is served for you to assist everything to locate guide. Due to the fact that we have finished publications from world writers from numerous nations, you necessity to get the book will certainly be so very easy here. When this Data Mining For Business Intelligence: Concepts, Techniques, And Applications In Microsoft Office Excel With XLMiner has the tendency to be guide that you need a lot, you can locate it in the link download. So, it's very easy after that exactly how you get this publication without spending lot of times to browse and find, experimentation in the book shop.
Review
"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
Read more
From the Back Cover
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 ensemblesA revised chapter on data visualization that now features interactive visualization principles and added assignments that demonstrate interactive visualization in practiceSeparate chapters that each treat k-nearest neighbors and Naïve Bayes methodsSummaries at the start of each chapter that supply an outline of key topicsThe 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.
Read more
See all Editorial Reviews
Product details
Hardcover: 428 pages
Publisher: Wiley; 2 edition (October 26, 2010)
Language: English
ISBN-10: 0470526823
ISBN-13: 978-0470526828
Product Dimensions:
7.3 x 1.1 x 10.3 inches
Shipping Weight: 2 pounds
Average Customer Review:
3.8 out of 5 stars
61 customer reviews
Amazon Best Sellers Rank:
#314,736 in Books (See Top 100 in Books)
I am a data mining trainer and consultant. This book not only has good content, but it offers a 90 day license of software with which to rehearse the case study examples. My comments on the book will be accompanied by comments on the software. The book is the perfect fit for its intended audience. With the caution that certain readers will do better elsewhere, I think it is a great book. The major topics are addressed, albeit briefly, with clarity. If you are a first timer reader of this subject, there are not many books that will do a better job explaining these technical subjects for a general audience.Like most full time data miners, I would have difficulty living within the constraints of Excel. XLMiner is a fine piece of software, but it lives inside Excel as an Excel add-on. The most famous limitation is having no more than 1,000,000 rows of data, but that nature of that limitation applied to Data Mining is frequently misunderstood. I am often on projects with "big data" clients where I only model 100,000 or fewer records. XLMiner allows you to read from a database larger than Excel can handle, and let's you write out to a database larger than Excel can handle. I was surprised and impressed by this. In the end, though, it still isn't enough. I need to be able to merge and manipulate my large data files so that I can carefully select the smaller fraction that I am going to model. In short, I can't live without my more powerful tools. There is an essay offered as a sidebar in the book on the state of the Data Mining Software Tools market by Herb Edelstein which discusses exactly this fact. XLMiner was originally developed as a piece of teaching software, and it excels at that. It doesn't intend to be a deployment tool for the whole business enterprise like some of the more powerful Data Mining suites. If you don't have access to such tools you might be pleasantly surprised what it can do since the other tools are many times more expensive.Despite this limitation, this is a strong book. It would be just perfect for MBAs that are intrigued with Data Mining. It would be great for a first course in Data Mining provided that it wasn't the first of many. If someone were about to embark on a Data Mining advanced degree, I don't think this book is the best route to go. I would suggest Handbook of Statistical Analysis and Data Mining Applications as an introduction for that audience. I also think it is an outstanding choice for a seminar leader that wants to offer demonstrations for the audience. I would suggest providing the audience with copies (or allowing them to get them). What a great way to learn the material - by doing. I debated using this book for exactly that purpose and ended up going with the Handbook of Statistical Analysis and Data Mining Applications only because I felt my audience, representing larger companies, would end up using one the Data Mining suites in the end, and I wanted them to see them.I would also suggest this book for self study. It is as easy a read as this kind of material is going to get. Technical? Yes. Light reading? Not really. However, Data Mining algorithms never make for light reading. What you hope for is clarity, and the right amount of detail. For the uninitiated, this is perfect. For Data Mining professionals, it would be just a very basic review. Some reviewers seems to have found it a tough slog. It is very much in the style of "here is the rough idea - try a case study". If you've never studied statistics, there is no careful walk through of the formulas, but that is not the point of the book. Lots of other books do that. If you want to know how Data Mining works "under the hood" you won't really find that here either. For example, Regression is covered in about 15 pages. Overall, I think it makes good choices in terms of detail.It covers all the material you need in an introduction. It offers a very brief initial chapter defining the subject. It does a decent job at data visualization. It is a basic introduction the algorithms with supporting case studies. The is almost no data preparation because XLMiner is not designed to do any heavy lifting here. It can do partitioning and explains why this is critical to data mining. For a good discussion of data preparation and Excel read Linoff's fine book Data Analysis Using SQL and Excel. A surprising number of the famous techniques are here: neural nets, k nearest neighbors, clustering, classification trees and even time series analysis. The case studies are fairly basic, but well described. They are easy to download from the website. Again, perfect for a first course in Data Mining. Everything an instructor would need for a good solid introduction - exactly the audience the book was written for.
I was made to buy this book as a part of one of my marketing classes in college. While the book explains the concepts decently well, the processes to answer the questions asked at the end of the chapters were often not explained.The book works in conjunction with a software called DataMiner XL and the questions asked in the chapters relate to this software. The problem is that the book asks you to perform complex tasks, but never goes ahead to explain how to do them using the software. It is up to you to do external research in order to find out how to complete the tasks. I believe that an instructional book such as this one should offer step by step guidance on the processes in which they expect you to perform.I would not recommend this book to anybody based on these reasons. The reason it got 2 stars is because the concepts were explained decently well.
Used this for my DSC 340 class (Data Mining class).This book does a great job with overviews. By that, I mean it explains a general topic fairly well. However, when it comes down to "how to" steps, the book is of almost no help. If there are "how-to" guides, they are very poorly written and extremely hard to follow. For most topics, it simply compares and contrasts different how to methods without actually explaining how to do them.
This book provides an excellent overview of a variety of data mining techniques related to business analysis. It does not provide much detailed statistical discussion or "how-to" steps. Instead, it provides enough detail to explain major concepts, the strengths and weaknesses of various analytic techniques, and when to use which technique. That alone is worth the price of admission.Readers without some background in math or statistics may find it necessary to do additional reading if they want to implement these techniques on their own. The book was originally intended to support college level teaching, where this kind of background is acquired in the class room and in study groups. Readers who buy this book for independent study may be disappointed that the answer key to the study problems is only available to instructors. A shame, really, since the authors clearly put a great deal of effort into finding many excellent case studies.Overall, I found this book worth the investment of my time and money. It provides an excellent outline for determining an analytics approach to most business questions.
Got me through
Purchased this book for a data mining course.As a Finance major I needed a big refresher on concepts. This book is excellent as it it tailored for MBA students. Gives practical examples that are easy and clear to understand. I first rented this from Amazon but ended up purchasing to have around
Unfortunately, the software updates have out paced the text updates and there are a lot of places where the problems either don't line up with the software and they aren't able to be completed as writen, or the problem is flawed to begin with and they can't be completed at all. We've had a number of individuals in the current class who's books had pretty significant misprints in various problem sets too.
This is my first time taking a Data Mining course and this book so far, is beyond helpful. From examples throughout the book to the software tools of XLMiner, this book has taught me the fundamental tools that I needed in order to exceed in this course. XLMiner is easy to use and doesn't take that long for you to know the in's and out's of this tool. From the use of XLMiner, I have been able to understand and interpret my data in many ways. There are so many different models to test and compare your datasets all in one spot. This book is great for hands-on learning experience and applying real-life problem-solving skills.
Data Mining for Business Intelligence: Concepts, Techniques, and Applications in Microsoft Office Excel with XLMiner PDF
Data Mining for Business Intelligence: Concepts, Techniques, and Applications in Microsoft Office Excel with XLMiner EPub
Data Mining for Business Intelligence: Concepts, Techniques, and Applications in Microsoft Office Excel with XLMiner Doc
Data Mining for Business Intelligence: Concepts, Techniques, and Applications in Microsoft Office Excel with XLMiner iBooks
Data Mining for Business Intelligence: Concepts, Techniques, and Applications in Microsoft Office Excel with XLMiner rtf
Data Mining for Business Intelligence: Concepts, Techniques, and Applications in Microsoft Office Excel with XLMiner Mobipocket
Data Mining for Business Intelligence: Concepts, Techniques, and Applications in Microsoft Office Excel with XLMiner Kindle
Tidak ada komentar: