Multidimensional Data Model for Data Warehouses
Date Issued
2002
Author(s)
Kon-Popovska, Margita
Abstract
Data Warehouses (DW) and Online Analytical Processing (OLAP)
are essential elements of Decision Support Systems (DSS), they enable business decision makers to creatively approach, analyze and understand business
problems.
OLAP data is frequently organized in the form of multidimensional data cubes
each of which is used to examine a set of data values, called facts. Each fact is
combination of multiple dimensions with multiple levels per dimension. The
goal of this paper is the introduction of a multidimensional data model. The
model is able to represent and capture natural hierarchical relationships among
members (attributes) within a dimension. Moreover the data model is able to
represent the relationships between dimension members and facts by mean of
cube cells.
are essential elements of Decision Support Systems (DSS), they enable business decision makers to creatively approach, analyze and understand business
problems.
OLAP data is frequently organized in the form of multidimensional data cubes
each of which is used to examine a set of data values, called facts. Each fact is
combination of multiple dimensions with multiple levels per dimension. The
goal of this paper is the introduction of a multidimensional data model. The
model is able to represent and capture natural hierarchical relationships among
members (attributes) within a dimension. Moreover the data model is able to
represent the relationships between dimension members and facts by mean of
cube cells.
Subjects
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