University of Twente Student Theses

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Enterprise Architecture Mining

Ahmad, Fajri (2019) Enterprise Architecture Mining.

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Abstract:In order to maintain its competitive advantage, an enterprise needs to be adapted to changes and opportunities. EA is one of the tools that capable to grasp the current condition of the enterprise. Thus it is prevalent to maintain an up-to-date EA model. However, manually maintain the model is cost and time consuming. In order to automated maintenance process, there is available method called automated EA model documentation. They are tools, mechanisms that enabled an architect to maintain the EA model automatically. However, current tools and methods only limited to certain systems or products. In this research, we propose an alternative to conducting automated EA model documentation that can combine multiple data sources and inter-operable structure between systems. The research conducted a literature review to study current literature related to log, event log, types of the log, and how an event log produced based on the viewpoint of process mining. The literature study also discovers the definition of process mining, its categories, its type of perspective and the algorithms that support the mining process. The study also discovers possible data sources that available for automated EA model documentation, related work in the automated EA model documentation and lastly propose the conversion pattern between a process model and an EA model. The research also did an narrative review to select appropriate process mining algorithms that are needed for the validation process. We also proposed a log structure that can be populated from systems with the help of the log guideline. Moreover, we indicate possible relevant fields that can be added to the structure to gather additional EA elements. After that we propose EA mining that consists of three steps, to discover business process, elements that related to the workflows, and analysis function. Using both log structure and EA mining we were able to generate an EA model. We were also able to implement EA mining and create algorithms and a prototype. In the research, we also conducted validation to test both the structure and the EA mining. The validation is analysed if the user perception comply with the reality that are produced from running systems. The validation also consists of the accuracy of the conversion pattern and the performance of the prototype.
Item Type:Essay (Master)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:54 computer science
Programme:Business Information Technology MSc (60025)
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