Knowledge Discovery Nuggets 97:13, e-mailed 97-04-16
From: "Anand, Tej" <
TAnand@HITC.AtlantaGA.ncr.com>Subject: book review for Nuggets
Date: Fri, 4 Apr 1997 16:58:14 -0500
Book Review: "Seven Methods for Transforming Corporate Data into Business
Intelligence" by Vasant Dhar and Roger Stein,
(Prentice-Hall, 1997).
(see http://www.prenhall.com/allbooks/be_0132820064.html for more
on this book. GPS)
It has been quite a while since I have been able to read a
technical/business book in its entirety, but recently I accomplished
this feat with "Seven Methods for Transforming Corporate Data into
Business Intelligence" by Vasant Dhar and Roger Stein. Usually I am
unable to complete a technical/business book because either it is so
high-level (and abstract) that I cannot appreciate how the material
would apply to me, or it is so detailed that I am totally lost "in the
trees".
Seven Methods... is different. This short book starts off by providing
a framework for representing objectives and requirements for
"intelligent systems" (systems that embed AI techniques or systems
that explicitly represent knowledge) using a business oriented
vocabulary. This framework not only helps select the "appropriate"
technique but it helps in formulating the problem that makes that
selection transparent. The business vocabulary helps explain the
selection to management and business types.
The book then describes seven data-intensive modeling techniques (tree
induction, analogical reasoning, fuzzy logic, rule-based systems,
neural nets, genetic algorithms, and OLAP) using the framework. While
these chapters are written to enable business-oriented people to get a
quick understanding of the techniques, they are also great for
technical folks because they can provide us knowledge about techniques
in which we are not experts. All techniques are treated with uniform
depth, which makes it a handy reference. The explanation of the
techniques is highly visual with almost every other page containing a
high quality graphic that explains how the techniques work. One
quibble: Chapter 10, titled Machine Learning, could have been more
aptly titled "Tree Induction".
The book ends with seven detailed (8-10 pages each) case studies of
successful applications of each of the techniques. Each case study is
described using the same framework. This is where the rubber meets the
road, and for the seven case studies selected the framework holds up
very well.
My only real complaint with this book is that it does not talk about using
multiple techniques together.
Btw: I felt this book was so well written that I promptly lent it to my
manager for weekend reading.
Disclaimer: Although we have never worked together, Roger Stein and I
for a brief time shared the same employer: Dun & Bradstreet, Roger at
Moody's and I at A.C Nielsen. One of the case studies is about
Spotlight, a system with which I was associated.
Tej Anand
NCR Corporation
Human Interface Technology Center