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A study of big data evolution and research challenges

机译:大数据演化与研究挑战的研究

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摘要

The world is already into the information age. The huge growth of digital data has overwhelmed the traditional systems and approaches. Big data is touching almost all aspects of our life and the data-driven discovery approach is an emerging paradigm for computing. The ever-growing data provides a tidal wave of opportunities and challenges in terms of data capture, storage, manipulation, management, analysis, knowledge extraction, security, privacy and visualisation. Though the promise of big data seems to be genuine, still a wide gap exists between its potential and realisation. In last few years, there is a huge surge in research efforts in academia as well as industry to have a better understanding of big data. This article discusses the following: (1) big data evolution including a bibliometric study of academic and industry publications pertaining to big data during the period 2000-2017, (2) popular open-source big data stream processing frameworks and (3) prevalent research challenges which must be addressed to realise the true potential of big data.
机译:世界已经进入了信息时代。数字数据的巨大增长已经不堪重负传统的系统和方法。大数据几乎触及了我们生活的各个方面,数据驱动的发现方法是用于计算的新兴范式。在数据捕获,存储,操纵,管理,分析,知识提取,安全,隐私和可视化方面,不断增长的数据提供了潮汐机会和挑战。虽然大数据的承诺似乎是真实的,但其潜在和实现之间存在宽阔的差距。在过去的几年里,学术界的研究努力以及行业有更好地了解大数据的巨大飙升。本文讨论了以下内容:(1)大数据演进,包括在2000 - 2017年期间,(2)流行的开源大数据流处理框架和普遍研究的流行开源大数据流处理框架和(3)普遍研究的学术和行业出版物的大数据演变研究必须解决的挑战,以实现大数据的真正潜力。

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