Bachelor / Master Thesis: Process Mining Demonstration System (all genders) - Bretten / Karlsruhe

<h2>Bachelor Thesis / Master Thesis<br/>  </h2> <h2>Process Mining Demonstration System</h2> <p> </p> <p> </p> <h2>Motivation</h2> <p><br/> Process Mining is used for the visualization and analysis of business processes and is based on the analysis of event logs. These contain information about the relationship and chronology of individual process steps of an IT system. Process Mining could be a valuable extension for the monitoring of the SEEBURGER BIS Integration Suite in the future. In this thesis, a technology demonstration system is to be created and evaluated on the basis of the pm4py framework from the Frauenhofer Institute.</p> <p> </p> <h2><br/> Objectives</h2> <p> </p> <ul> <li>Evaluation basis for further investments in the topic of Process Mining at SEEBURGER AG</li> <li>Evaluation of the benefits of process mining for business integration use cases</li> <li>Evaluation of the maturity level of available methods and software components</li> <li>Basics for the evaluation of the effort for the implementation of a</li> <li>Process Mining extension for SEEBURGER BIS Monitoring</li> </ul> <p> </p> <h2><br/> Tasks</h2> <p> </p> <p>1. Theoretical Part</p> <p> </p> <ul> <li>Presentation of the basic functionality of a process mining system</li> <li>Market overview of open source components and commercial systems</li> <li>Use Cases in the area of Business Integration</li> <li>Selection of suitable analysis and visualization methods</li> <li>Analysis of the SEEBURGER Business Integration Suite with respect to necessary extensions for data generation, analysis and visualization</li> </ul> <p> </p> <p>2. Practical Part</p> <p> </p> <ul> <li>Development of a prototype based on the pm4py framework</li> <li>Provision/generation of representative data (event log)</li> <li>Implementation of suitable analysis methods</li> <li>Implementation of the required visualization components</li> <li>Demonstration of selected use cases</li> </ul> <p> </p> <p> </p> <h2>Prerequisites</h2> <p> </p> <ul> <li>Python</li> <li>Java</li> </ul> <p> </p> <h2><br/> Advantageous</h2> <p> </p> <ul> <li>Petri Nets</li> <li>Mining Algorithms</li> <li>Statistical Methods</li> </ul> <p> </p> <p> </p> <p>Location: Bretten and/or Karlsruhe</p> <p> </p> <p> </p> <p><u>Contact Recruiting:</u></p> <p> </p> <p>Daniel Iwtschenko</p> <p><a href="tel:+497252962224">+49 7252 96-2224</a></p> <p><a href="https://www.linkedin.com/in/daniel-iwtschenko-4a33a1225/" target="_blank">LinkedIn</a> - <a href="https://www.xing.com/profile/Daniel_Iwtschenko/portfolio" target="_blank">XING</a></p>