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

J. Gao, Chunli Xie, Chuanqi Tao
{"title":"Big Data Validation and Quality Assurance -- Issuses, Challenges, and Needs","authors":"J. Gao, Chunli Xie, Chuanqi Tao","doi":"10.1109/SOSE.2016.63","DOIUrl":null,"url":null,"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.","PeriodicalId":153118,"journal":{"name":"2016 IEEE Symposium on Service-Oriented System Engineering (SOSE)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"81","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE Symposium on Service-Oriented System Engineering (SOSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SOSE.2016.63","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
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。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Internet of Things Application Using Tethered MSP430 to Thingspeak Cloud Creative Computing: An Approach to Knowledge Combination for Creativity? Software Crowdsourcing Practices and Research Directions Towards a Mobile Assistive System Using Service-Oriented Architecture A Practical Evaluation in Openstack Live Migration of VMs Using 10Gb/s Interfaces
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1