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A Survey of Data Quality Assessment Methods for Big Data

  • Journal of Software Assessment and Valuation
  • Abbr : JSAV
  • 2023, 19(4), pp.89-97
  • Publisher : Korea Software Assessment and Valuation Society
  • Research Area : Engineering > Computer Science
  • Received : December 2, 2023
  • Accepted : December 20, 2023
  • Published : December 31, 2023

Okjoo Choi 1 Yukyong Kim 2

1강원대학교
2숙명여자대학교

Accredited

ABSTRACT

Data quality is very important in data-based information technologies such as big data analysis or machine learning. Even if high-performance data analysis algorithms or machine learning models are used, if the quality of the input data is not guaranteed, the results cannot be trusted. Therefore, in order to utilize and analyze big data, it is necessary to be able to extract high-quality data from massive and complex data. In this paper, we consider quality evaluation methods for big data that guarantee high quality. We examine international standardization trends for data life cycle and data quality factors for big data and define data quality characteristics that should be considered according to the big data life cycle. In addition, we compare and analyze existing major studies on data quality evaluation related to big data, and based on the result, we examine the elements necessary for big data quality evaluation. Based on the defined elements, we propose a big data quality evaluation process using goal-driven data quality metric. In the future, we expect that the proposed process will be used to develop evaluation indicators that can evaluate big data quality and to develop an integrated evaluation framework.

Citation status

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