Advanced Data Management for Maintenance and Cost Optimization in the Heavy-Duty Mobility Sector

In today’s data-driven world, the integration and analysis of data are paramount for enhancing business operations and decision-making processes. This thesis project, conducted for Company A, focuses on developing a comprehensive financial management tool aimed at predicting vehicle maintenance costs and improving operational efficiency. The project exploits machine learning models and cloud- based data warehousing solutions to provide accurate forecasts and insightful analytics. The project commenced in 2022 and is scheduled for completion in early 2025. Despite the challenges of integrating diverse data sources and ensuring seamless data flow, the project aims to deliver a robust financial management tool that significantly enhances Company A’s ability to predict and manage vehicle maintenance costs. By detailing the ETL process and the collaborative efforts of the different streams, this thesis provides a comprehensive overview of the methodologies and technologies employed in developing this innovative solution.