An Event Data Extraction Approach from SAP ERP for Process Mining
Alessandro Berti, Gyunam Park, Majid Rafiei, Wil van der, Aalst

TL;DR
This paper presents a new method and tool for extracting event data from SAP ERP systems, addressing challenges of data size and structure to support process mining with object-centric logs.
Contribution
It introduces an approach and tool for efficient event data extraction from SAP ERP, enabling better process mining support with object-centric logs.
Findings
Successful implementation of the tool in real SAP environments
Effective extraction of object-centric event logs from SAP data
Feasibility demonstrated through case studies
Abstract
The extraction, transformation, and loading of event logs from information systems is the first and the most expensive step in process mining. In particular, extracting event logs from popular ERP systems such as SAP poses major challenges, given the size and the structure of the data. Open-source support for ETL is scarce, while commercial process mining vendors maintain connectors to ERP systems supporting ETL of a limited number of business processes in an ad-hoc manner. In this paper, we propose an approach to facilitate event data extraction from SAP ERP systems. In the proposed approach, we store event data in the format of object-centric event logs that efficiently describe executions of business processes supported by ERP systems. To evaluate the feasibility of the proposed approach, we have developed a tool implementing it and conducted case studies with a real-life SAP ERP…
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Taxonomy
TopicsBusiness Process Modeling and Analysis · Service-Oriented Architecture and Web Services · Collaboration in agile enterprises
