Visual Data Mining: Techniques and Tools for Data Visualization and Mining; Tom Soukup, Ian Davidson; 2002

Visual Data Mining: Techniques and Tools for Data Visualization and Mining Upplaga 1

av Tom Soukup, Ian Davidson
Master the power of visual data mining tools and techniques 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: Justify and plan your project Identify your top business questions and map them into data visualization or data mining questions Identify and select data to address these questions Transform raw data into a visualization or data mining business data set and verify for accuracy Choose the appropriate visualization or visual data mining tool Analyze and evaluate the visualizations or data mining models to discover business insights, trends, and anomalies The companion Web site includes: Links to data visualization and visual data mining tools Links to real-world success stories using visual data mining The major example data sets used throughout the book

 
Master the power of visual data mining tools and techniques 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: Justify and plan your project Identify your top business questions and map them into data visualization or data mining questions Identify and select data to address these questions Transform raw data into a visualization or data mining business data set and verify for accuracy Choose the appropriate visualization or visual data mining tool Analyze and evaluate the visualizations or data mining models to discover business insights, trends, and anomalies The companion Web site includes: Links to data visualization and visual data mining tools Links to real-world success stories using visual data mining The major example data sets used throughout the book

 
Upplaga: 1a upplagan
Utgiven: 2002
ISBN: 9780471149996
Förlag: John Wiley & Sons
Format: Häftad
Språk: Engelska
Sidor: 416 st
Master the power of visual data mining tools and techniques 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: Justify and plan your project Identify your top business questions and map them into data visualization or data mining questions Identify and select data to address these questions Transform raw data into a visualization or data mining business data set and verify for accuracy Choose the appropriate visualization or visual data mining tool Analyze and evaluate the visualizations or data mining models to discover business insights, trends, and anomalies The companion Web site includes: Links to data visualization and visual data mining tools Links to real-world success stories using visual data mining The major example data sets used throughout the book

 
Master the power of visual data mining tools and techniques 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: Justify and plan your project Identify your top business questions and map them into data visualization or data mining questions Identify and select data to address these questions Transform raw data into a visualization or data mining business data set and verify for accuracy Choose the appropriate visualization or visual data mining tool Analyze and evaluate the visualizations or data mining models to discover business insights, trends, and anomalies The companion Web site includes: Links to data visualization and visual data mining tools Links to real-world success stories using visual data mining The major example data sets used throughout the book

 
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