Data ETL Application

Project Overview

Python-based desktop application for a traffic data collection company, streamlining the process of importing, visualizing, adjusting, and exporting traffic data. The application allows employees to load raw data from traffic counting devices, make necessary corrections through an intuitive interface, and export the refined data while maintaining the proprietary format required by the devices. This solution enhances data accuracy and workflow efficiency, reducing manual processing time and ensuring seamless integration with existing traffic data collection systems.

Tools Used

Project Details

• Designed and implemented an ETL (Extract, Transform, Load) pipeline to process traffic data from collection devices.
• Developed a Python-based application with an intuitive user interface for data visualization and manual adjustments.
• Implemented data import functionality to handle various proprietary data formats from traffic counting devices.
• Designed a user-friendly interface to streamline the workflow for employees with minimal technical expertise.
• Built interactive visualization tools to display traffic patterns, allowing users to detect and correct anomalies.
• Developed validation and correction mechanisms to ensure data accuracy before exporting.
• Implemented export functionality to preserve the required custom data format for seamless device integration.
• Ensured data integrity through validation rules and error-handling mechanisms.
• Used Pandas and NumPy for data manipulation and processing.
• Developed modular and maintainable code to facilitate future enhancements.
• Packaged the application using PyInstaller for easy deployment on employee workstations.
• Conducted testing and debugging to ensure accuracy and reliability.
• Deployed the application in an environment accessible to employees, ensuring ease of use and scalability.
• Authored comprehensive documentation and a user manual to guide employees on using the application effectively.