An Integrated Approach to Process and Organizational Data Mining.

In recent years, the use of information systems has become increasingly important in organizations, generating vast amounts of heterogeneous data from various sources. Data Science encompasses data mining and process mining disciplines, among others, that allow the management, analysis, and discovery of valuable information from this data. However, these disciplines are often applied independently, over different datasets obtained from heterogeneous data sources which are not necessarily integrated, and thus can lead to partial views when analyzing the results. To address this issue, this research proposes a unified approach to data mining and process mining over process and organizational integrated data, which enables a comprehensive view of the daily operation of organizations for evidence-based decision making. In this paper we present a proposal for carrying out such integrated analysis, and a proof of concept prototype developed to support it. We also present an example of application with process and organizational data from a real university process.