reviewACM Computing SurveysJul 1, 2009Closed access

Methodologies for data quality assessment and improvement

University of Milano-Bicocca · Politecnico di Milano

Indexed incrossref

Abstract

The literature provides a wide range of techniques to assess and improve the quality of data. Due to the diversity and complexity of these techniques, research has recently focused on defining methodologies that help the selection, customization, and application of data quality assessment and improvement techniques. The goal of this article is to provide a systematic and comparative description of such methodologies. Methodologies are compared along several dimensions, including the methodological phases and steps, the strategies and techniques, the data quality dimensions, the types of data, and, finally, the types of information systems addressed by each methodology. The article concludes with a summary…

Citation impact

1,241
total citations
FWCI
56.18
Percentile
100%
References
84
Citations per year

Authors

4

Topics & keywords

Keywords
  • Computer science
  • Data science
  • Quality (philosophy)
  • Data quality
  • Personalization
  • Selection (genetic algorithm)
  • Management science
  • Data mining
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