DocumentCode :
1103103
Title :
Value-Cell Bar Charts for Visualizing Large Transaction Data Sets
Author :
Keim, Daniel A. ; Hao, Ming C. ; Dayal, Umeshwar ; Lyons, Martha
Author_Institution :
Univ. of Konstanz, Konstanz
Volume :
13
Issue :
4
fYear :
2007
Firstpage :
822
Lastpage :
833
Abstract :
One of the common problems businesses need to solve is how to use large volumes of sales histories, Web transactions, and other data to understand the behavior of their customers and increase their revenues. Bar charts are widely used for daily analysis, but only show highly aggregated data. Users often need to visualize detailed multidimensional information reflecting the health of their businesses. In this paper, we propose an innovative visualization solution based on the use of value cells within bar charts to represent business metrics. The value of a transaction can be discretized into one or multiple cells: high-value transactions are mapped to multiple value cells, whereas many small-value transactions are combined into one cell. With value-cell bar charts, users can 1) visualize transaction value distributions and correlations, 2) identify high-value transactions and outliers at a glance, and 3) instantly display values at the transaction record level. Value-cell bar charts have been applied with success to different sales and IT service usage applications, demonstrating the benefits of the technique over traditional charting techniques. A comparison with two variants of the well-known Tree map technique and our earlier work on pixel bar charts is also included.
Keywords :
bar charts; business data processing; customer profiles; data visualisation; sales management; Web transactions; business metrics; customers behavior; data visualization solution; pixel bar charts; sales histories; tree map technique; value-cell bar charts; Data analysis; Data mining; Data visualization; Decision trees; Displays; Graphics; History; Information analysis; Marketing and sales; Multidimensional systems; Information visualization; methodologies.; multivariate visualization; visualization techniques; Accounting; Color; Computer Graphics; Database Management Systems; Databases, Factual; Imaging, Three-Dimensional; Information Storage and Retrieval; Statistics as Topic;
fLanguage :
English
Journal_Title :
Visualization and Computer Graphics, IEEE Transactions on
Publisher :
ieee
ISSN :
1077-2626
Type :
jour
DOI :
10.1109/TVCG.2007.1023
Filename :
4293024
Link To Document :
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