ICoDA: Interactive and exploratory data completeness analysis

Ruilin Liu, Guan Wang, Wendy Hui Wang, Flip Korn

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

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.

Original languageEnglish
Title of host publication2014 IEEE 30th International Conference on Data Engineering, ICDE 2014
Pages1226-1229
Number of pages4
DOIs
StatePublished - 2014
Event30th IEEE International Conference on Data Engineering, ICDE 2014 - Chicago, IL, United States
Duration: 31 Mar 20144 Apr 2014

Publication series

NameProceedings - International Conference on Data Engineering
ISSN (Print)1084-4627

Conference

Conference30th IEEE International Conference on Data Engineering, ICDE 2014
Country/TerritoryUnited States
CityChicago, IL
Period31/03/144/04/14

Keywords

  • Data completeness
  • exploratory pattern analysis
  • graph tableau discovery
  • pattern visualization

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