Big Data Validation and Quality Assurance -- Issuses, Challenges, and Needs

J. Gao, Chunli Xie, Chuanqi Tao
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引用次数: 81

Abstract

With the fast advance of big data technology and analytics solutions, big data computing and service is becoming a very hot research and application subject in academic research, industry community, and government services. Nevertheless, there are increasing data quality problems resulting in erroneous data costs in enterprises and businesses. Current research seldom discusses how to effectively validate big data to ensure data quality. This paper provides informative discussions for big data validation and quality assurance, including the essential concepts, focuses, and validation process. Moreover, the paper presents a comparison among big data validation tools and several major players in industry are discussed. Furthermore, the primary issues, challenges, and needs are discussed.
大数据验证和质量保证——问题、挑战和需求
随着大数据技术和分析解决方案的快速发展,大数据计算与服务正在成为学术界、产业界和政府服务领域非常热门的研究和应用课题。然而,企业和业务中的数据质量问题越来越多,导致错误的数据成本。目前的研究很少讨论如何有效验证大数据以保证数据质量。本文为大数据验证和质量保证提供了翔实的讨论,包括基本概念、重点和验证过程。此外,本文还对大数据验证工具进行了比较,并对行业中的几个主要参与者进行了讨论。此外,还讨论了主要问题、挑战和需求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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