Adaptable Privacy-Preserving Data Curation for Business Process Analysis Services

Abstract

Log-based business operation analysis is getting more and more attention from enterprise decision makers. However, at the very first step of the analysis service, two primary obstacles are always encountered: how to process a wide variety of local event log formats and how to handle personally identifiable information weaved in an event log. Due to these obstacles, typical business analysts who do not have programming skills have lost business opportunities at the early stages. We propose a privacy-preserving data curation specification language, BELAS, for such analysts and present experimental results that show how most of a real-life event log could be processed in process analysis services.