iCoDA: Interactive and Exploratory Data Completeness Analysis

被引:0
作者
Liu, Ruilin [1 ]
Wang, Guan [1 ]
Wang, Wendy Hui [1 ]
Korn, Flip [2 ]
机构
[1] Stevens Inst Technol, Dept Comp Sci, Hoboken, NJ 07030 USA
[2] AT&T Shannon Labs, New York, NY 10017 USA
来源
2014 IEEE 30TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING (ICDE) | 2014年
关键词
Data completeness; graph tableau discovery; exploratory pattern analysis; pattern visualization;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The completeness of data is vital to data quality. In this demo, we present iCoDA, a system that supports interactive, exploratory data completeness analysis. iCoDA provides algorithms and tools to generate tableau patterns that concisely summarize the incomplete data under various configuration settings. During the demo, the audience can use iCoDA to interactively explore the tableau patterns generated from incomplete data, with the flexibility of filtering and navigating through different granularity of these patterns. iCoDA supports various visualization methods to the audience for the display of tableau patterns. Overall, we will demonstrate that iCoDA provides sophisticated analysis of data completeness.
引用
收藏
页码:1226 / 1229
页数:4
相关论文
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