BigDimETL: ETL for Multidimensional Big Data

被引：1
作者：
Mallek, Hana [1 ,2 ]
Ghozzi, Faiza [1 ,2 ]
Teste, Olivier [1 ,2 ]
Gargouri, Faiez [1 ,2 ]
机构：
[1] Univ Sfax, MIR CL Lab, BP 242, Sfax 3021, Tunisia
[2] Univ Toulouse, IRIT 5505, 118 Route Narbonne, F-31062 Toulouse, France
来源：
INTELLIGENT SYSTEMS DESIGN AND APPLICATIONS (ISDA 2016) | 2017年 / 557卷
关键词：
ETL; Data warehouse; Bigdata; Twitter; MapReduce; Parallel processing; Multidimensional structure;
D O I：
10.1007/978-3-319-53480-0_92
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
With the broad range of data available on the World Wide Web and the increasing use of social media such as Facebook, Twitter, YouTube, etc. a "Big Data" notion has emerged. This latter has become an important aspect in nowadays business since it is full of important knowledge that is crucial for effective decision making. However, this kind of data brings with it new problems and challenges for the Decision Support System (DSS) that must be addressed. In this paper, we propose a new approach called BigDimETL (Big Dimensional ETL) that deals with ETL (Extract-Transform-Load) development process. Our approach focuses on integrating Big Data taking into account the MultiDimensional Structure (MDS) through a MapReduce paradigm.
引用
收藏
页码：935 / 944
页数：10
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