Desktop User Data Tracker
Budget: $250 – $750 USD
I need a desktop program that focuses on pelacakan data pengguna. The application must collect the necessary user-data streams on the host machine, run light analysis, then present the insights in clear, interactive visualisations—charts, tables, maybe a timeline if it helps. Because Analisis data dan visualisasi is the only feature I ticked, that side of the workflow has to feel polished: quick filters, export to CSV/PNG, and a dashboard that refreshes smoothly.
Tech stack is flexible as long as the final build runs on Windows without extra runtime headaches. You can use Python (PyInstaller, PyQt, matplotlib, seaborn), C# with WPF and LiveCharts, or any other desktop-friendly framework you’re comfortable with; just pick one you can deliver confidently and document. Make sure the code is clean, commented, and separated into clear modules for data capture, processing, and UI.
Deliverables
• Compiled installer or portable executable
• Full, well-commented source code
• Brief README explaining setup, data paths, and how to extend the visual layer
I’ll test by running the program, generating sample activity, and checking that the visualisation updates correctly without crashes or noticeable lag. Looking forward to seeing how you structure the pipeline from raw data to insight.
Tech stack is flexible as long as the final build runs on Windows without extra runtime headaches. You can use Python (PyInstaller, PyQt, matplotlib, seaborn), C# with WPF and LiveCharts, or any other desktop-friendly framework you’re comfortable with; just pick one you can deliver confidently and document. Make sure the code is clean, commented, and separated into clear modules for data capture, processing, and UI.
Deliverables
• Compiled installer or portable executable
• Full, well-commented source code
• Brief README explaining setup, data paths, and how to extend the visual layer
I’ll test by running the program, generating sample activity, and checking that the visualisation updates correctly without crashes or noticeable lag. Looking forward to seeing how you structure the pipeline from raw data to insight.