The cube data model: a conceptual model and algebra for on-line analytical processing in data warehouses

被引:73
|
作者
Datta, A [1 ]
Thomas, H [1 ]
机构
[1] Univ Arizona, MIS Dept, Tucson, AZ 85721 USA
关键词
data warehouse; On-Line Analytical Processing (OLAP); relational OLAP (ROLAP); conceptual data models; algebra; multidimensional databases; decision support databases; data cube model;
D O I
10.1016/S0167-9236(99)00052-4
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Data warehousing and On-Line Analytical Processing (OLAP) are two of the most significant new technologies in the business data processing arena. A data warehouse can be defined as a "very large" repository of historical data pertaining to an organization. OLAP refers to the technique of performing complex analysis over the information stored in a data warehouse. The complexity of queries required to support OLAP applications makes it difficult to implement using standard relational database technology. Moreover, there is currently no standard conceptual model for OLAP. There is clearly a need for such a model and an algebra as evidenced by the numerous SQL extensions offered by many vendors of OLAP products. In this paper, we address this issue by proposing a model of a data cube and an algebra to support OLAP operations on this cube. The model we present is simple and intuitive, and the algebra provides a means to concisely express complex OLAP queries. (C) 1999 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:289 / 301
页数:13
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