توضیحات
ABSTRACT
With the fast advance of big data technology and analytics solutions, building high-quality big data computing services in different application domains is becoming a very hot research and application topic among academic and industry communities, and government agencies. Therefore, big data based applications are widely-used currently, such as recommendation, predication, and decision system. Nevertheless, there are increasing quality problems resulting in erroneous testing costs in enterprises and businesses. Current research work seldom discusses how to effectively validate big data applications to assure system quality. This paper focuses on big data system validation
and quality assurance, and includes informative discussions about essential quality parameters, primary focuses, and validation process. Moreover, the paper discusses potential testing methods for big data application systems. Furthermore, the primary issues , challenges, and needs in testing big data application are presented,
INTRODUCTION
According to IDC [1], the Big Data technology market will billion through 2017″.Today, with the fast advance of big data science and analytics technologies, diverse data mining solutions, machine learning algorithms, open-source platforms & tools, and big data database technologies have been developed, and become available to be used for big data applications “grow at a 27% compound annual growth rate (CAGR) to
$32.4 . This suggests that big data computing and application services bring large-scale business requirements and demands in people’s daily life. Big data-based application system is widely-used nowadays, such as recommendation system, predictions, recognized patterns, statistical report applications, etc. Emergent big data computing and services can be used in many disciplines and diverse applications, including business management, library science, energy and environment, education, biomedical, healthcare and life science, social media and networking, smart city and travel, and transportation, etc.[2]. Nevertheless, due to the huge volume of generated data, the fast velocity of arriving data, and the large variety of heterogeneous data, the big data based applications brings new challenges and issues for QA engineers. For instance, it is a hard job to validate the correctness of a big data-based prediction system due to the large scale data size and the feature of timeliness
Year : 2016
Publisher : IEEE
By : Chuanqi Tao , Jerry Gao
File Information : English Language /7 Page /Size : 469 K
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سال : 2016
ناشر : IEEE
کاری از : Chuanqi Tao , Jerry Gao
اطلاعات فایل : زبان انگلیسی / 7 صفحه / حجم : 469 K
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