Integration of business process data and organizational data for evidence-based business intelligence

Abstract

Organizations require a unified view of business processes data and organizational data to improve their daily operations. However, it is infrequent for both kinds of data to be consistently unified. Organizational data (e.g., clients, orders, and payments) are usually stored in many different data sources. Process data (e.g., cases, activity instances, and variables) are generally handled manually or implicitly in information systems and coupled with organizational data without clear separation. It impairs the combined application of process mining and data mining techniques for a complete evaluation of an organization’s business process execution. In this paper, we deal with the integration of both kinds of data into a unified view. First, we analyze data integration scenarios and data matching problems considering intra-organizational and inter-organizational collaborative business processes. We also propose a model-driven approach to integrate several data sources, generating a unified model for evidence-based business intelligence.