Reclassification queries in a geographical data warehouse

Abstract

A data warehouse is a specialized database designed to support decision-making and is usually modeled using a multidimensional view of data. A multidimensional model includes dimensions that are composed of levels. The levels of a dimension are organized in a hierarchy, e.g., salespersons are grouped into stores. Throughout its lifespan a member (instance) of a level can be associated with several members of a higher level of the hierarchy, e.g., the salespersons can rotate between the stores. This succession of associations enables the formulation of queries such as: “How much did a salesperson sell in his n-th season (stay) in the store X?” In this paper, we enrich this type of query, known as season queries, with spatial features. This enhancement enables the formulation of queries such as: “How much did a salesperson sell in his n-th season in a given geographic region?” (A spatial query window that contains a set of stores.) In order to facilitate their formulation, we propose and incorporate an operator into a multidimensional query language to demonstrate their feasibility of implementation.

Keywords

• temporal data warehouses
• spatial data warehouses
• OLAP
• members”™ reclassification
• season queries