Business Modeling and Data Mining

by Dorian Pyle

Business Modeling and Data Mining demonstrates how real world business problems can be formulated so that data mining can answer them. The concepts and techniques presented in this book are the essential building blocks in understanding what models are and how they can be used practically to reveal hidden assumptions and needs, determine problems, discover data, determine costs, and explore the whole domain of the problem.

This book articulately explains how to understand both the strategic and tactical aspects of any business problem, identify where the key leverage points are and determine where quantitative techniques of analysis -- such as data mining -- can yield most benefit. It addresses techniques for discovering how to turn colloquial expression and vague descriptions of a business problem first into qualitative models and then into well-defined quantitative models (using data mining) that can then be used to find a solution. The book completes the process by illustrating how these findings from data mining can be turned into strategic or tactical implementations.

-Teaches how to discover, construct and refine models that are useful in business situations
-Teaches how to design, discover and develop the data necessary for mining
-Provides a practical approach to mining data for all business situations
-Provides a comprehensive, easy-to-use, fully interactive methodology for building models and mining data
-Provides pointers to supplemental online resources, including a downloadable version of the methodology and software tools.

Genres: Business

650 pages, Paperback

First published January 1, 2003

Reviews

[Terran M · Rating 4 out of 5]

This is a nontechnical book on data modeling and mining. It has a small chapter on specific algorithms and tools, but you shouldn't even read that chapter, because it's cursory and obsolete. The real value in this book is in understanding the business value of the things you can do as a data miner. It even has a survival guide in the back with concrete steps for each class of problem you might have, like "data is not suitable for requested purpose".

I recommend reading this book after you've learned and practiced the technical skills, when you're ready to start interfacing directly with the business stakeholders instead of a technical manager who defines and assigns tasks.

The biggest drawback to this book is that the author has used twice as many words as he should have for the number of ideas he conveyed. I'd give it 5 stars if it were half as long.

[Bernd · Rating 5 out of 5]

One of the most pragmatic books integrating business needs with data modeling & analysis challenges.