Aligning the Warehouse and the Web

Data warehouses have established themselves as necessary components of an effective IT strategy for large businesses. To augment the streams of data being siphoned from transactional/operational databases warehouses must also integrate increasing amounts of external data to assist in decision support. Modern warehouses can be expected to handle up to 100 Terabytes or more of data. (Berson and Smith, 1997; Devlin, 1998; Inmon 2002; Imhoff et al, 2003; Schwartz, 2003; Day 2004; Peter and Greenidge, 2005; Winter and Burns 2006; Ladley, 2007). The arrival of newer generations of tools and database vendor support has smoothed the way for current warehouses to meet the needs of the challenging global business environment ( Kimball and Ross, 2002; Imhoff et al, 2003; Ross, 2006). We cannot ignore the role of the Internet in modern business and the impact on data warehouse strategies. The web represents the richest source of external data known to man ( Zhenyu et al, 2002; Chakrabarti, 2002; Laender et al, 2002) but we must be able to couple raw text or poorly structured data on the web with descriptions, annotations and other forms of summary meta-data (Crescenzi et al, 2001). In recent years the Semantic Web initiative has focussed on the production of “smarter data”. The basic idea is that instead of making programs with near human intelligence, we rather carefully add meta-data to existing stores so that the data becomes “marked up” with all the information necessary to allow not-sointelligent software to perform analysis with minimal human intervention. (Kalfoglou et al, 2004) The Semantic Web builds on established building block technologies such as Unicode, URIs(Uniform Resource Indicators) and XML (Extensible Markup Language) (Dumbill, 2000; Daconta et al, 2003; Decker et al, 2000). The modern data warehouse must embrace these emerging web initiatives. In this paper we propose a model which provides mechanisms for sourcing external data resources for analysts in the warehouse.