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