Big Data Analytics: Key Technologies and Challenges

被引：1
|
作者：
Hu Shuijing [1 ]
机构：
[1] Shanghai Univ Polit Sci & Law, Shanghai 201701, Peoples R China
来源：
2016 INTERNATIONAL CONFERENCE ON ROBOTS & INTELLIGENT SYSTEM (ICRIS) | 2016年
关键词：
Big Data; Data Analytics; Cloud Computing; Hydoop; Privacy;
D O I：
10.1109/ICRIS.2016.30
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
We live in the era of big data. Big data generates immense economic and social value. Advances in data collection and the massive increase in cloud computing power are making technologies to effectively analyze large sets of heterogeneous data ubiquitous. Despite all the benefits of big data, the rise of "Big Data Analytics" in the private sector poses new challenges for privacy advocates. This paper discusses essential technologies and challenges related to big data analytics, namely (i) definition of big data analytics; (ii) essential technologies related to the big data analytics, with particular reference to the cloud computing, and hydoop etc.; (iii) risks arising from big data analytics, especially privacy harm.
引用
收藏
页码：141 / 145
页数：5
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