The integration of business intelligence and knowledge management

TLDR

Enterprise executives recognize that timely, accurate knowledge improves performance, and that business intelligence and knowledge management technologies—through data warehouses, mining, content management, and advanced search—are increasingly merging to analyze data and text together. The authors aim to describe business problems that demand integrated text and data analysis and the technical challenges associated with them. They propose an OLAP-based model enhanced with text analysis, implemented via the eClassifier text analyzer and the Sapient OLAP‑style integration tool. They coin the blended technology BIKM to combine business intelligence and knowledge management.

Abstract

Enterprise executives understand that timely, accurate knowledge can mean improved business performance. Two technologies have been central in improving the quantitative and qualitative value of the knowledge available to decision makers: business intelligence and knowledge management. Business intelligence has applied the functionality, scalability, and reliability of modern database management systems to build ever-larger data warehouses, and to utilize data mining techniques to extract business advantage from the vast amount of available enterprise data. Knowledge management technologies, while less mature than business intelligence technologies, are now capable of combining today's content management systems and the Web with vastly improved searching and text mining capabilities to derive more value from the explosion of textual information. We believe that these systems will blend over time, borrowing techniques from each other and inspiring new approaches that can analyze data and text together, seamlessly. We call this blended technology BIKM. In this paper, we describe some of the current business problems that require analysis of both text and data, and some of the technical challenges posed by these problems. We describe a particular approach based on an OLAP (on-line analytical processing) model enhanced with text analysis, and describe two tools that we have developed to explore this approach—eClassifier performs text analysis, and Sapient integrates data and text through an OLAP-style interaction model. Finally, we discuss some new research that we are pursuing to enhance this approach.