Extracting Event Data from Databases to Unleash Process Mining

Abstract

Abstract. Increasingly organizations are using process mining to understand the way that operational processes are executed. Process mining can be used to systematically drive innovation in a digitalized world. Next to the automated discovery of the real underlying process, there are process-mining techniques to analyze bottlenecks, to uncover hidden inefficiencies, to check compliance, to explain deviations, to predict performance, and to guide users towards "better" processes. Dozens (if not hundreds) of process-mining techniques are available and their value has been proven in many case studies. However, process mining stands or falls with the availability of event logs. Existing techniques assume that events are clearly defined and refer to precisely one case (i.e. process instance) and one activity (i.e., step in the process). Although there are systems that directly generate such event logs (e.g., BPM/WFM systems), most information systems do not record events explicitly. Cases and activities only exist implicitly. However, when creating or using process models "raw data" need to be linked to cases and activities. This paper uses a novel perspective to conceptualize a database view on event data. Starting from a class model and corresponding object models it is shown that events correspond to the creation, deletion, or modification of objects and relations. The key idea is that events leave footprints by changing the underlying database. Based on this an approach is described that scopes, binds, and classifies data to create "flat" event logs that can be analyzed using traditional process-mining techniques.

A Goal-Driven Evaluation Method Based On Process Mining for Healthcare Processes

“…Various software products have PM capabilities [21]; e.g., ARIS Process Performance Manager (Software AG) [22], ProM (TU/e) [23], Disco (Fluxicon) [24], PALIA-ER [25], CELONIS [26], and pMineR [27]. Some of these products are still at the maturing stage since PM is a relatively young paradigm open to research and practice.…”

A Cross-Organizational Process Mining Framework for Obtaining Insights from Software Products: Accurate Comparison Challenges

“…Besides this, we talked with product owners and database administrators to discover the business logic inside the current product. As a result of these discussions, we created a rained class model [5]. The model shows the elements of the current product's business logic.…”

Ontology-Driven Extraction of Event Logs from Relational Databases

“…Process mining techniques can be used to discover the real process, to detect deviations from some normative process, to analyze bottlenecks and waste, and to predict flow times [13]. Normally, "flat" event logs serve as the starting point for process mining [13,14]. These logs are created with a particular process and a set of questions in mind.…”

“…We refer to the XES standard [10] for more information on the data possibly available in event logs. See [14] for logging guidelines and details on getting event data from databases using redo logs. It is apparent that a condition sine qua non for the application of process mining is the availability of faithful event logs, adhering to accepted standards (such as XES) and guaranteeing a certain quality level [15].…”

“…Moreover, commercial tools like Disco make it easy to convert a CSV or Excel file into a XES log. In [14] it is shown how event data can be extracted from the redo-logs of a database. However, none of the tools and approaches actually puts the domain ontology in the loop.…”