Data Warehouses: Next Challenges

被引:0
|
作者
Vaisman, Alejandro [1 ]
Zimanyi, Esteban [1 ]
机构
[1] Univ Libre Bruxelles, Dept Comp & Decis Engn CoDE, Brussels, Belgium
来源
BUSINESS INTELLIGENCE | 2012年 / 96卷
关键词
data warehouses; OLAP; spatiotemporal data warehouses; real-time data warehouses; semantic data warehouses; MAPREDUCE;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Data Warehouses are a fundamental component of today's Business Intelligence infrastructure. They allow to consolidate heterogeneous data from distributed data stores and transform it into strategic indicators for decision making. In this tutorial we give an overview of current state of the art and point out to next challenges in the area. In particular, this includes to cope with more complex data, both in structure and semantics, and keeping up with the demands of new application domains such as Web, financial, manufacturing, genomic, biological, life science, multimedia, spatial, and spatiotemporal applications. We review consolidated resaerch in spatio-temporal databases, and open research fields, like real-time Business Intelligence and Semantic Web Data Warehousing and OLAP.
引用
收藏
页码:1 / 26
页数:26
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