The Approach for Data Warehouse to Answering Spatial OLAP Queries

Abstract

AbstractSpatial data are pervasive in traditional business applications like the customer address and store location. With the advance in mobile computing and digital earth, much more spatial data have been collected, stored and integrated into the business system. Analyzing these spatial data, to understand the relationships among them, and the relationships between spatial data and non-spatial data, would help companies gain deeper geographical insight into their business and customers, and explore more other potential business value. However, neither the design of data warehouse takes the spatial dimension of data into consideration, nor the data warehousing tools (e.g., ETL) support spatial data in the preprocessing stages. Consequently, the deployed data warehouses without spatial aware can not support spatial analysis. Research in spatial data warehousing and OLAP is an necessary to exploit the information and knowledge hidden in the spatial dimension and spatial relationships during the processing of data warehousing. This paper proposes a novel approach for data warehouses to be spatially aware and to provide certain spatial analysis capabilities. A spatial transformation builder is developed and deployed as an ETL tool to extract facts including complex spatial relationships from spatial data sources according to business requirements. The facts capturing the spatial relationships from original sources are presented by non-spatial relation model and stored in the data warehouse, where some kinds of spatial OLAP queries could be issued.KeywordsSpatial DataSpatial RelationshipData WarehouseSpatial ObjectStar SchemaThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.