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

被引:54
|
作者
Gao, Jerry [1 ,2 ]
Xie, Chunli [3 ]
Tao, Chuanqi [4 ]
机构
[1] San Jose State Univ, San Jose, CA 95192 USA
[2] Taiyuan Univ Technol, Taiyuan Shi, Shanxi Sheng, Peoples R China
[3] Jiangsu Normal Univ, Xuzhou, Peoples R China
[4] Nanjing Univ Sci & Technol, Nanjing, Jiangsu, Peoples R China
关键词
Quality assurance; big data quality assurance; big data validation; data validation;
D O I
10.1109/SOSE.2016.63
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
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.
引用
收藏
页码:433 / 441
页数:9
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