Functional Integration with Process Mining and Process Analyzing for Structural and Behavioral Properness Validation of Processes Discovered from Event Log Datasets

Abstract

In this paper, we propose an integrated approach for seamlessly and effectively providing the mining and the analyzing functionalities to redesigning work for very large-scale and massively parallel process models that are discovered from their enactment event logs. The integrated approach especially aims at analyzing not only their structural complexity and correctness but also their animation-based behavioral properness, and becomes concretized to a sophisticated analyzer. The core function of the analyzer is to discover a very large-scale and massively parallel process model from a process log dataset and to validate the structural complexity and the syntactical and behavioral properness of the discovered process model. Finally, this paper writes up the detailed description of the system architecture with its functional integration of process mining and process analyzing. More precisely, we excogitate a series of functional algorithms for extracting the structural constructs and for visualizing the behavioral properness of those discovered very large-scale and massively parallel process models. As experimental validation, we apply the proposed approach and analyzer to a couple of process enactment event log datasets available on the website of the 4TU.Centre for Research Data.

PRANAS: A Process Analytics System Based on Process Warehouse and Cube for Supply Chain Management

“…The integration between business and process analytics has been considered in different ways in a few studies [4][5][6]9,10]. A conceptual framework of a decision support system for business intelligence was presented by Görgülü and Pickl [4], which combined classical data-centric approaches such as data mining with a modern system engineering using the advanced concept of adaptive business intelligence.…”

“…Marjanovic argued that, in service-oriented industries, the operational business intelligence and business process management systems need to be integrated with case-handling [5], which could be done with the framework proposed in this paper. Kim presented an architecture to functionally integrate data analysis functions and process discovery functions [6]. Both systems coexist in what it is called a process-aware enterprise organization, which is usually the case of companies that participate in supply chain systems.…”

“…Meanwhile, business process analytics is a specialized system that helps to improve business process execution by analyzing operational data recorded in event logs that contain activity events, which have been recorded in process-aware information systems such as enterprise resource planning (ERP) and supply chain management (SCM) systems [3]. Although business analytics offers both types of data-oriented and process-oriented analysis tools, few studies have investigated how to integrate the two approaches in a concrete and effective manner [4][5][6].…”