Semantic data warehouse at the heart of competitive intelligence systems: Design approach

Competitive Intelligence (CI) is the process of managing information emanating from the business environment of an organization in order to support decision making process. CI enables the development of strategies that confer companies a significant competitive advantage. The appropriate decisions are taken when all required data are considered. As the amount of data grows very fast inside and outside of an enterprise, exploiting these mountains of data efficiently became a crucial need. Note that such data are usually multiples, heterogeneous, autonomous and distributed. The main issue is related to the identification and resolution of structural and semantic heterogeneity between data, usually spread in multiple sources. Data integration is a significant solution that addresses these problems. Data Warehouse (DW) is viewed as Data Integration System (DIS) that consolidates several data sources in the same target repository through an Extract-Transform-Load (ETL) process. In a decisional context, DW is a relevant solution to aggregate a huge amount of data and organizing them in order to facilitate their analysis and support decision making. In this paper, we propose an approach for designing Semantic Data Warehouse (SDW) to support CI process. Our proposal takes as inputs decision makers' requirements and a set of Semantic Databases (SDB) sources for building the SDW.