A Proposed Process for Performing Data Mining Projects

A Proposed Process for Performing Data Mining Projects

Karim K. Hirji (IBM Canada Ltd., Canada)
DOI: 10.4018/978-1-59140-057-8.ch005
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Abstract

There is an enormous amount of data generated by academic, business, and governmental organizations alike; however, only a small portion of the data that is collected and stored in databases is ever analyzed. Since data are the building blocks for both information and knowledge, the opportunity costs (to organizations) of ignoring data assets can range from competitive disadvantage to organizational demise. Data mining has thus emerged as a discipline focusing on unleashing the potential of data in organizations. The enthusiasm surrounding data mining at large continues to grow; however, at the same time, there are claims that data mining projects fail in delivering the expected value. Many of the causes of the failures can be traced back to strategy, process and technology variables. The purpose of this chapter is to discover a process for performing data mining projects and to propose this process to practitioners as a starting point when making decisions about planning, organizing, executing and closing data mining projects. Literature on package implementation, rapid application development and new product development together with results from a case study are used to arrive at the proposed data mining process. More research is needed to evaluate, refine and validate the proposed process before it can be used as the basis for developing a comprehensive methodology for performing data mining projects.

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Table of Contents
Foreword
Parag C. Pendharkar
Preface
Parag C. Pendharkar
Acknowledgments
Chapter 1
Witold Abramowicz, Marek Nowak, Joanna Sztykiel
The main purpose of this article is to discuss applicability of Bayesian belief networks (BBN) within the procedures of working-capital credit... Sample PDF
Bayesian Networks as a Decision Support Tool in Credit Scoring Domain
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Chapter 2
Marvin D. Troutt, Michael Hu, Murali Shanker, William Acar
Frontier Regression Models seek to explain boundary, frontier or optimal behavior rather than average behavior as in ordinary regression models.... Sample PDF
Frontier Versus Ordinary Regression Models for Data Mining
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Chapter 3
Parag C. Pendharkar, Sudhir Nanda, James A. Rodger, Rahul Bhaskar
This chapter illustrates how a misclassification cost matrix can be incorporated into an evolutionary classification system for medical diagnosis.... Sample PDF
An Evolutionary Misclassification Cost Minimization Approach for Medical Diagnosis
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Chapter 4
Aaron Ceglar, John Roddick, Paul Calder
Knowledge discovery is the process of eliciting interesting knowledge from data repositories. Due to the inability of computers to understand... Sample PDF
Guiding Knowledge Discovery Through Interactive Data Mining
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Chapter 5
Karim K. Hirji
There is an enormous amount of data generated by academic, business, and governmental organizations alike; however, only a small portion of the data... Sample PDF
A Proposed Process for Performing Data Mining Projects
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Chapter 6
Chi Kin Chan, Heung Wong, Wan Kai Pang, Marvin D. Troutt
This chapter is a case study in combining forecasts for inventory management in which the need for data mining in combination forecasts is... Sample PDF
Data Mining for Optimal Combination Demand Forecasts
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Chapter 7
David Paper, Kenneth B. Tingey, Wai Yin Mok
This chapter illustrates how IT-enabled business process reengineering can fail if top management fails to understand the underlying process... Sample PDF
The Myth of Enterprise Database Redesign
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Chapter 8
Sudhakar Kuppuraju, Girish Subramanian
Recent interest in relationship management and relationship marketing has led many firms to consider how to improve customer retention rates. The... Sample PDF
New Information Technologies and Other Pertinent Issues Impacting the Strategic Dimension of CRM for Business Excellence
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Chapter 9
James A. Rodger
Accounting information systems enable the process of internal control and external auditing to provide a first-line defense in detecting fraud... Sample PDF
Utilization of Data Mining Techniques to Detect and Predict Accounting Fraud: A Comparison of Neural Networks and Discriminant Analysis
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Chapter 10
Jose Maria Cavero, Carmen Costilla, Esperanza Marcos, Mario G. Piattini, Adolfo Sanchez
Data warehousing and online analytical processing (OLAP) technologies have become growing interest areas in recent years. Specific issues such as... Sample PDF
A Multidimensional Data Warehouse Development Methodology
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Chapter 11
Bahador Ghahramani
The telecommunications industry (TI) is challenged by a significant increase in the complexity of information transfer due to a recent proliferation... Sample PDF
A Telecommunications Model for Managing Complexity of Voice and Data Networks and Services
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Chapter 12
Wan Kai Pang, Heung Wong, Chi Kin Chan, Marvin D. Troutt
This chapter proposes an approach to the combination of forecasts from a new perspective and uses a new estimation methodology. Concepts from... Sample PDF
Combination Forecasts Based on Markov Chain Monte Carlo Estimation of the Mode
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Chapter 13
Roderick L. Lee
This chapter presents an overview of web mining. The three areas of web mining—Web content mining, Web usage mining, and Web structure mining—are... Sample PDF
Web Mining: Creating Structure out of Chaos
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Chapter 14
Parag C. Pendharkar, Girish Subramanian
Mining information and knowledge from very large databases is recognized as a key research area in machine learning and expert systems. In the... Sample PDF
Connectionist and Evolutionary Models for Learning, Discovering and Forecasting Software Effort
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About the Authors