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IBM Visual Table Analyzer
A tool that allow users to visually interact with, analyze, and reveal patterns in a large data set.
Date Posted: November 13, 2007
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What is IBM Visual Table Analyzer?
Are you working routinely with spreadsheets and trying to make sense of your data? Is there a pattern to be revealed on your sales or financial data or simply an outcome on your favorite sport?
This data visualization technology uses a novel concept called "FanLens" to visualize the data distribution in a table. FanLens visualizes quantitative data distribution using a tree-based data category view. Users can efficiently interact and easily navigate between the summary and detailed view of any data set in order to see underlying data patterns and relationships. In addition, the tool provides a flexible data manipulation mechanism and allows users to build their own data categories to augment the analysis of their data.
How does it work? IBM® Visual Table Analyzer is a Java™ application that allows user to analyze plain table data. After downloading and installing it, users can
- load a plain-text, delimited data table
- easily create a tree view of the relevant data
- analyze data using the zoom-in and zoom-out features to get both summary and detailed perspectives on the data.
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| | About the technology author(s):
Lou Xing Hua is a research and development engineer with the Information Visualization Team at the IBM China Research Lab. He graduated in 2006 and joined IBM in the same year. Mr. Hua is working on several visualization research porjects, including large-sized data visualization and time series data visualization.
Wang Tian Shu is a research staff member on the Information Visualziation Team. In 2002, he earned his Ph.D. in computer science and joined the IBM China Research Lab. Dr. Shu has worked on human computer interaction and collaboration-related projects.
Liu ShiXia manages the Information Visualization Team at the IBM China Research Lab. She graduated in 2002 and joined IBM. Dr Liu's research interests include information visualization, knowledge engineering, and data semantics.
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