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Data Mining for Business Intelligence: Concepts, Techniques, and Applications in Microsoft Office Excel with XLMiner
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Data Mining for Business Intelligence: Concepts, Techniques, and Applications in Microsoft Office Excel with XLMiner |
Author: Galit Shmueli
Published: 2006-12-11 |
List price: $105.95
Our price: $84.76
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Usually ships in 8 to 9 days
As of: September 06th, 2008 02:49:56 AM
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Customer comments on this selection.
 Excellent MBA/B-School Data Mining Book
I've used this as textbook for three years (even before it was in print) for my "Business Intelligence Using Data Mining" elective MBA course at the Indian School of Business. Till last Fall, I used to structure my class around the four major data-mining techniques explained well in this book; classification, prediction, clustering and association rules (what goes with what). The last time I switched completely to driving the class using the six or seven excellent cases at the back of the book, and the Business students loved that.
The cases and the associated data are rich; providing a business context to anchor the learning for students in the B-School. They allow the instructor to naturally cover important practical issues, such as over-sampling (when events that one is interested in -- say load defaults -- are rare), and asymmetric classification costs.
My class typically has a group project, where students have to pull everything together, from identifying a data mining opportunity, to collecting the data (beg, borrow or crawl:-), to performing exploratory data analysis (a key chapter in the book), to analyzing and presenting the results. Its usually more work than the students expect, but also typically much more learning than they expect.
In summary, a great resource for teaching the principles of data mining to anyone, and particularly useful for those in a Business School setting.
An Excellent Introduction, Works with Excel
Data mining is the extraction of useful information from large amounts of data. Perhaps the best example of this is Amazon. If you go to Amazon to look at a book, you'll find such tidbits of information as a section on the page headlined 'Customers who bought this item also bought' and another 'What do customers ultimately buy after viewing this item?'
That's datamining, dozens or hundreds, or thousands of people looked at the page about this item. Then they went on to take these other actions. Among all the data that Amazon has collected they mine their database and pull out information to fill in these blocks.
This book, intended for MBA level students gives an excellent introduction to data mining. It further includes access to an Excel add-in called XLMiner that is specifically set up to allow the student to use Excel to learn how data mining is done.
The one thing I would ask the authors to do in their next edition is to provide a brief review of the commercially available data mining software products that are available. If not all of the software, perhaps just the top half dozen or so. In real life we aren't going to use Excel for data mining, our data resides in a database somewhere.
 Condensed Discussion of DataMining
This book discusses some of the techniques used
in Data Mining.
It goes into Data Exploration as well as Evaluating
Classification and Predictive Performance.
Some of the more advanced techniques such as
Neural Nets and Cluster Analysis are
also discussed.
To learn more about database design and relational data modeling visit
[...]
From the authors:
This book got its start as notes for a data mining class that one of us (Nitin Patel) was teaching at MIT, and was completed while another of us (Galit Shmueli) was teaching a similar course at Maryland. Both courses were part of an MBA program. We found that, while there are a lot of books on data mining, there were none that actually gave business students the skills and tools to implement data mining algorithms. So we set ourselves the task of writing a book that (1) provides real data sets with a business decision-making context and a hands-on orientation , (2) provides a theoretical and practical understanding of the key data mining methods of classification, prediction, data reduction and exploration at a level that is appropriate and useful for MBA's, and (3) bundles a powerful version of a commercial data mining tool that works in Excel (XLMiner). For this reason, we think our book will be appropriate not just for students, but also for business analysts with a quantitative orientation, on, indeed, anyone who wants to learn data mining via self-study. Have we succeeded? You be the judge! - P. Bruce (for G. Shmueli and N. Patel)
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