Abstract: SCA Tool is a university-led project that focuses on license compliance and Software Bill of Materials (SBOM) management. The system lacks the capability to analyze usage data and product-related metrics. Such an analysis is needed for data-driven decision-making for the continuous project and product development. This thesis addresses this issue and implements the Business Intelligence (BI) system for SCA Tool. The system utilizes Extract, Transform, Load (ETL) pipelines; these extract the data from the production environment. Then transforms the data into time-series metrics before loading the metrics into the data warehouse. Finally, the data is visualized using charts and dashboards. The system was built using an agile iterative approach to development and is ready to be integrated into the main deployment of SCA Tool. This system is capable of calculating 23 business metrics and implements the end-to-end process from production data to visual dashboards. The current system is limited by the fact that it is not integrated into the main production system. Therefore, no metrics were calculated on the production data, and no performance analysis is conducted.
Keywords: Business Intelligence, ETL, Kubernetes, SCA Tool
PDF: Master Thesis
Reference: Maximilian Krug. SCA Tool Admin Business Intelligence App. Master Thesis. Friedrich-Alexander-Universität Erlangen-Nürnberg: 2026.
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