
Jelle Kuebler enhanced the OTAnalytics repository by focusing on code maintainability, data reliability, and user experience in analytics workflows. He refactored the image counting logic, centralizing and standardizing data classes to improve code clarity and future extensibility. Using Python, Pandas, and Matplotlib, Jelle improved the robustness of data export features by handling missing columns gracefully, ensuring reliable data outputs. He also introduced a modular plotting architecture that decouples plot generation from saving and enables automatic GUI updates, streamlining the visualization pipeline. These contributions reflect a thoughtful approach to backend development and data visualization, addressing both technical depth and usability.

May 2025 OTAnalytics: Focus on code health, data reliability, and analytics UX. Delivered key features that strengthen maintainability, data reliability, and visualization capabilities; improved business value through robust data export, clearer code organization, and responsive visualizations across the pipeline.
May 2025 OTAnalytics: Focus on code health, data reliability, and analytics UX. Delivered key features that strengthen maintainability, data reliability, and visualization capabilities; improved business value through robust data export, clearer code organization, and responsive visualizations across the pipeline.
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