Data Science - Analyse grosser Datenmengen zur Qualität unserer Dienstleistungen und Services

Data is useless if no information is extracted. Worldline is the biggest payment provider in Europe and provides terminals for electronic payment to their merchant clients. These terminals transfer events to the terminal management system. The project consists of the analysis of these events.

Haris Asani & Nelson Braillard & Pascal Schaller & Dominic Weber, 2020

Projektarbeit/Praxisprojekt, Worldline / Six Payment Services
Betreuende Dozierende: Holger Wache
Keywords: Data Science, Big Data, Data Analysis, Business Intelligence, Data Mining
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It can be possible that payment terminals that are installed and maintained by Worldline generate malfunctions or do irregular reboots throughout their lifetime. If a malfunction occurs, data is sent from the terminal to the servers of Worldline. This data describes the event that occurred with various attributes. The data that is sent from the terminals to the servers of Worldline provides valuable information for Worldline, which is not yet extracted. The key point of this project is therefore to extract knowledge from this data to improve the reliability of terminals in several ways.
The project was split into three agile phases. When a phase was completed, the results and findings of the previous phase are the foundation of the following phase. In the first phase, the data and the system environment were understood. Additionally, data were visualized in a user-friendly and understandable way. In a second phase, the results were used to define data mining methods and tools to continue to work with (MS Power BI, Python Pandas). The last phase consisted of implementing the selected data mining methods.
As previously mentioned, the logs that are sent from the terminals to the Worldline Servers provide valuable information for Worldline. With the help of the analysis, the client is able to start improving terminals (hardware), terminal software and processes. This will increase the quality of the services Worldline offers. 1. Glossary and priority of events 2. Identification of at least three data mining methods 3. Visualization of data identification 4. Knowledge for the client created based on the analysis of the provided data
Studiengang: Business Information Technology (Bachelor)
Fachbereich der Arbeit: Business Information System & IT-Management
Vertraulichkeit: öffentlich
Art der Arbeit
Projektarbeit/Praxisprojekt
Auftraggeber
Worldline / Six Payment Services, Zürich
Autorinnen und Autoren
Haris Asani & Nelson Braillard & Pascal Schaller & Dominic Weber
Betreuende Dozierende
Holger Wache
Publikationsjahr
2020
Sprache der Arbeit
Englisch
Vertraulichkeit
öffentlich
Studiengang
Business Information Technology (Bachelor)
Standort Studiengang
Basel
Keywords
Data Science, Big Data, Data Analysis, Business Intelligence, Data Mining