A data model for supporting on-line analytical processing
Proceedings of the fifth international conference on Information and knowledge management - CIKM '96
A database application, called "on-line analytical processing" (or OLAP) and aimed at providing business intelligence through on-line multidimensional data analysis, has become increasingly important due to the existence of huge amounts of on-line data. This paper formalizes a multidimensional data (MDD) model for OLAP, and develops an algebraic query language called grouping algebra. The basic component of the MDD model is a multidimensional cube, consisting of a number of relations (called
... elations (called dimensions) and for each combination of tuples (called a coordinate), one from each dimension, there is an associated data value. Each dimension is viewed as a basic grouping, i.e., each tuple in the dimension corresponds to the group consisting of all the coordinates that contain this tuple. In order to express user queries, relational algebra expressions are then extended to those on basic groupings for obtaining complex groupings, including orderoriented groupings (for expressing, e.g., cumulative sum). The paper then considers the environment where the multidimensional cubes are materialized views derived from base data situated at remote sites. A multidimensional cube algebra is introduced in order to facilitate the data derivation. The purpose of the paper is to establish a formal foundation for further research regarding database support for OLAP applications.