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Abstract. Taking customer data as an example, the paper presents an approach to enhance the management of enterprise data by using Semantic Web technologies. Customer data is the most important kind of core business entity a company uses repeatedly across many business processes and systems, and customer data management (CDM) is becoming critical for enterprises because it keeps a single, complete and accurate record of customers across the enterprise. Existing CDM systems focus on integrating customer data from all customer-facing channels and front and back office systems through multiple interfaces, as well as publishing customer data to different applications. To make the effective use of the CDM system, this paper investigates semantic query and analysis over the integrated and centralized customer data, enabling automatic classification and relationship discovery. We have implemented these features over IBM Websphere Customer Center, and shown the prototype to our clients. We believe that our study and experiences are valuable for both Semantic Web community and data management community.

Information technology architects increasingly find themselves searching for better ways to access, integrate, and leverage their information, applications, and business processes. Information integration, in particular, is critical to the community of Web-based businesses, as firms that are able to leverage their information resources most effectively are best positioned to emerge as leaders in their industries. In this paper, we explore how companies can solve this complex business challenge by extending the reach of WebSphereா technology with DB2ா Information Integrator (II). DB2 II offers WebSphere developers a new approach to coping with diverse and distributed information sources, enabling them to reduce programming costs, shorten development cycles, and attain reasonable levels of performance for server-side components that need to integrate information throughout their enterprises and partner networks.

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