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By harnessing the power of visual data mining tools and techniques, business analysts can quickly and easily retrieve information to solve common business problems from an entirely new perspective. Traditional data mining techniques generate huge amounts of numeric data that can be difficult to interpret and use. Visual data mining makes it easier for nontechnical business managers to understand their markets and make savvy business decisions, in addition to opening the world of visual tools to a much broader audience.
This book describes how various types of business problems can be solved using visual mining techniques. After introducing the business issues and fundamentals, it then presents a step-by-step methodology for implementing visual mining techniques into your own business intelligence project.
This methodology will explain how to:
The companion Web site includes:
Author Biography:TOM SOUKUP has more than fifteen years of experience in data management and analysis. He is currently with Konami Gaming, Inc., where he is involved in data mining and data warehousing projects for the gaming industry.
IAN DAVIDSON, PhD, has worked on commercial data mining applications, including insurance claim fraud detection, product cross-sell, customer retention, and credit card fraud detection. He is currently an Assistant Professor of Computer Science at the State University of New York, Albany.
|About the Authors|
|Pt. 1||Introduction and Project Planning Phase||1|
|Ch. 1||Introduction to Data Visualization and Visual Data Mining||3|
|Ch. 2||Step 1: Justifying and Planning the Data Visualization and Data Mining Project||25|
|Ch. 3||Step 2: Identifying the Top Business Questions||49|
|Pt. 2||Data Preparation Phase||65|
|Ch. 4||Step 3: Choosing the Business Data Set||67|
|Ch. 5||Step 4: Transforming the Business Data Set||129|
|Ch. 6||Step 5: Verify the Business Data Set||171|
|Pt. 3||Data Analysis Phase and Beyond||203|
|Ch. 7||Step 6: Choosing the Visualization or Visual Mining Tool||205|
|Ch. 8||Step 7: Analyzing the Visualization or Mining Tool||253|
|Ch. 9||Step 8: Verifying and Presenting the Visualizations or Mining Models||317|
|Ch. 10||The Future of Visual Data Mining||339|
Posted August 24, 2002
Great book. This book tells you exactly how to do data mining. From how to map business questions on to data mining tasks to how to deploy and monitor data mining models. The various other books on data mining are good for understanding the maths behind the algorithms, but didn't tell me how to use them. This book does this.Was this review helpful? Yes NoThank you for your feedback. Report this reviewThank you, this review has been flagged.
Posted July 13, 2002
To my knowledge this is the only book on data mining that takes you through all the steps of the data mining cycle. The authors have clearly done data mining in the real world and understand that data preparation and model deployment and monitoring are just as important to the success of a project as is building the most accurate model. Highly recommended. The books is applicable to most data mining projects, not just those centered around visualization.Was this review helpful? Yes NoThank you for your feedback. Report this reviewThank you, this review has been flagged.
Posted July 1, 2002
This is a very useful book on how to achieve a successful data mining project. It details 8 steps in a data mining project and how visualization can play a role in each. Mercifully it covers more than just algorithms and spends 3 chapters on data preparation, 2 chapters on model verification and deploymment.Was this review helpful? Yes NoThank you for your feedback. Report this reviewThank you, this review has been flagged.