An Iterative Methodology for Big Data Management, Analysis and Visualization

被引:0
|
作者
Tardio, Roberto [1 ]
Mate, Alejandro [1 ]
Trujillo, Juan [1 ]
机构
[1] Univ Alicante, Lucentia Res Grp, Dept Software & Comp Syst, Alicante, Spain
来源
PROCEEDINGS 2015 IEEE INTERNATIONAL CONFERENCE ON BIG DATA | 2015年
关键词
Big Data; Business Intelligence; Data Warehousing; Hadoop; CHALLENGES;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Big Data constitutes an opportunity for companies to empower their analysis. However, at the moment there is no standard way for approaching Big Data projects. This, coupled with the complex nature of Big Data, is the cause that many Big Data projects fail or rarely obtain the expected return of investment. In this paper, we present a methodology to tackle Big Data projects in a systematic way, avoiding the aforementioned problems. To this end, we review the state of the art, identifying the most prominent problems surrounding Big Data projects, best practices and methods. Then, we define a methodology describing step by step how these techniques could be applied and combined in order to tackle the problems identified and increase the success rate of Big Data projects.
引用
收藏
页码:545 / 550
页数:6
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