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A review of big data analytics over cloud

机译:云端大数据分析回顾

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摘要

As the volume of data is increasing exponentially, there is a need for better management of data to research and industry. This data, known as Big Data, is now used by various organizations to extract valuable information which can be analysed computationally to reveal patterns, trends and associations revealing the human interaction and behaviour for making various industrial decisions. Due to the large volume of data, it is stored in the cloud and all the analysis is done over Big Data over cloud since it is not possible for traditional systems to store such large amount of data. But the data must be optimized, integrated, secured and visualized to make any effective decision. Analysing of the large volume of data is not beneficial always unless it is analysed properly. The existing techniques are insufficient to analyse the Big Data and identify the frequent services accessed by the cloud users. Various services can be integrated to provide a better environment to work in. Using these services, people become widely vulnerable to exposure. That is, it becomes possible to collect more data than it is required which may lead to data leakage and hence security concerns. Results can be analysed in a better way by visuals like graphs, charts etc. and it helps in faster decision making. It also includes MapReduce Algorithm which will help in maintaining a log of user's activities in the cloud and show the frequently used services. This paper proposes a scheme for making Big Data Analytics more accurate, efficient and beneficial.
机译:随着数据量呈指数级增长,需要更好地管理数据与研究和行业的数据。这些数据,称为大数据,现在使用各种组织来提取有价值的信息,可以计算可以计算地分析,以揭示揭示制定各种工业决策的人类互动和行为的模式,趋势和关联。由于数据量大,它存储在云中,并且所有分析都在云上的大数据上完成,因为传统系统无法存储如此大量数据。但是必须优化数据,集成,安全和可视化以进行任何有效的决定。除非正确分析,否则分析大量数据并不有益。现有技术不足以分析大数据并确定云用户访问的频繁服务。可以集成各种服务,以提供更好的工作环境。使用这些服务,人们将广泛容易受到曝光。也就是说,可以收集比所需的更多数据,这可能导致数据泄漏并因此是安全问题。结果可以通过像图形,图表等更好的方式以更好的方式分析结果,并有助于更快地决策。它还包括MapReduce算法,它将有助于维护云中的用户活动的日志,并显示常用的服务。本文提出了一种使大数据分析更准确,高效和有益的方案。

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