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文章基本信息

  • 标题:The Challenges of Data Quality and Data Quality Assessment in the Big Data Era
  • 本地全文:下载
  • 作者:Li Cai ; Yangyong Zhu
  • 期刊名称:Data Science Journal
  • 电子版ISSN:1683-1470
  • 出版年度:2015
  • 卷号:14
  • DOI:10.5334/dsj-2015-002
  • 语种:English
  • 出版社:Ubiquity Press
  • 摘要:High-quality data are the precondition for analyzing and using big data and for guaranteeing the value of the data. Currently, comprehensive analysis and research of quality standards and quality assessment methods for big data are lacking. First, this paper summarizes reviews of data quality research. Second, this paper analyzes the data characteristics of the big data environment, presents quality challenges faced by big data, and formulates a hierarchical data quality framework from the perspective of data users. This framework consists of big data quality dimensions, quality characteristics, and quality indexes. Finally, on the basis of this framework, this paper constructs a dynamic assessment process for data quality. This process has good expansibility and adaptability and can meet the needs of big data quality assessment. The research results enrich the theoretical scope of big data and lay a solid foundation for the future by establishing an assessment model and studying evaluation algorithms.
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