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Date Submitted: 08/31/2015 11:49 AM
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Cai, L and Zhu, Y 2015 The Challenges of Data Quality and Data Quality
Assessment in the Big Data Era. Data Science Journal, 14: 2, pp. 1-10,
DOI: http://dx.doi.org/10.5334/dsj-2015-002
PROCEEDINGS PAPER
The Challenges of Data Quality and Data Quality
Assessment in the Big Data Era
Li Cai1,3 and Yangyong Zhu2
School of Computer and Science, Fudan University, No. 220, Han Dan Road, Shanghai, China
lcai@fudan.edu.cn
1
Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China
yyzhu@fudan.edu.cn
2
School of Software, Yunnan University, No. 2 North Road of Cui Hu, Kunming, China
3
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.
Keywords: Big data; Data quality; Quality assessment; Data science
1 Introduction
Many significant technological changes have occurred in the information technology industry since the
beginning of the 21st century, such as cloud computing, the Internet of Things, and social networking. The
development of...