Main building – room E3.20
- Sareh Sadeghianasl, Queensland University of Technology, Australia
- Jochen De Weerdt, KU Leuven, Belgium
- Moe Thandar Wynn, Queensland University of Technology, Australia
The First International Workshop on Data Quality and Transformation in Process Mining (DQT-PM2022) aims to facilitate the exchange of research findings, ideas, and experiences on techniques and practices to data transformation and quality improvement at Stage 0 of a process mining project.
These days, the amount of available data is increased in organizations, so is its perceived value for stakeholders. A broad spectrum of process mining techniques (e.g., process discovery, conformance checking, and performance analysis) exists to derive actionable business insights from the recorded process data. As these process mining techniques rely on historical process data as ‘the single source of truth’, working with data that is of low and dubious quality poses significant hurdles to successfully translating data into actionable business insights.