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Conference Papers Year : 2017

Simplifying Big Data Analytics Systems with a Reference Architecture

Go Muan Sang
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Lai Xu
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Paul De Vrieze
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The internet and pervasive technology like the Internet of Things (i.e. sensors and smart devices) have exponentially increased the scale of data collection and availability. This big data not only challenges the structure of existing enterprise analytics systems but also offer new opportunities to create new knowledge and competitive advantage. Businesses have been exploiting these opportunities by implementing and operating big data analytics capabilities. Social network companies such as Facebook, LinkedIn, Twitter and Video streaming company like Netflix have implemented big data analytics and subsequently published related literatures. However, these use cases did not provide a simplified and coherent big data analytics reference architecture as well as currently, there still remains limited reference architecture of big data analytics. This paper aims to simplify big data analytics by providing a reference architecture based on existing four use cases and subsequently verified the reference architecture with Amazon and Google analytics services.
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Dates and versions

hal-01674844 , version 1 (03-01-2018)





Go Muan Sang, Lai Xu, Paul De Vrieze. Simplifying Big Data Analytics Systems with a Reference Architecture. 18th Working Conference on Virtual Enterprises (PROVE), Sep 2017, Vicenza, Italy. pp.242-249, ⟨10.1007/978-3-319-65151-4_23⟩. ⟨hal-01674844⟩
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