Facilitating Role of Cloud Computing in Driving Big Data Emergence

Teah Yi Fan, Muhammad Ehsan Rana
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引用次数: 3

Abstract

Big data emerges as an important technology that addresses the storage, processing and analytics aspects of massive data characterized by 5V's (volume, velocity, variety, veracity, value) which has grown exponentially beyond the handling capacity traditional data architectures. The most significant technologies include the parallel storage and processing framework which requires entirely new IT infrastructures to facilitate big data adoption. Cloud computing emerges as a successful paradigm in computing technology that shifted the business landscape of IT infrastructures towards service-oriented basis. Cloud service providers build IT infrastructures and technologies and offer them as services which can be accessed through internet to the consumers. This paper discusses on the facilitating role of cloud computing in the field of big data analytics. Cloud deployment models concerning the architectural aspect and the current trend of adoption are introduced. The fundamental cloud services models concerning the infrastructural and technological provisioning are introduced while the emerging cloud services models related to big data are discussed with examples of technology platforms offered by the big cloud service providers - Amazon, Google, Microsoft and Cloudera. The main advantages of cloud adoption in terms of availability and scalability for big data are reiterated. Lastly, the challenges concerning cloud security, data privacy and data governance of consuming and adopting big data in the cloud are highlighted.
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云计算在推动大数据产生中的促进作用
大数据作为一项重要的技术出现,它解决了以5V(体积、速度、种类、准确性、价值)为特征的海量数据的存储、处理和分析方面的问题,这些数据的增长已经超出了传统数据架构的处理能力。最重要的技术包括并行存储和处理框架,这需要全新的IT基础设施来促进大数据的采用。云计算作为一种成功的计算技术范例出现,它将IT基础设施的业务环境转向面向服务的基础。云服务提供商构建IT基础设施和技术,并将其作为可通过互联网访问的服务提供给消费者。本文讨论了云计算在大数据分析领域的促进作用。介绍了有关体系结构方面的云部署模型和当前的采用趋势。介绍了有关基础设施和技术供应的基本云服务模型,并以大型云服务提供商(Amazon、b谷歌、Microsoft和Cloudera)提供的技术平台为例,讨论了与大数据相关的新兴云服务模型。在大数据的可用性和可扩展性方面,采用云计算的主要优势得到了重申。最后,重点介绍了在云中消费和采用大数据所面临的云安全、数据隐私和数据治理方面的挑战。
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