ETL Model for Pandemic Data Processing

This paper presents the development and implementation of an Extract-Transform-Load (ETL) model aimed at processing pandemic data. The model gathers data from various official sources, transforms it for easy analysis, and provides insights through graphical representations. Implemented using Python, the system automates data extraction and visualization, offering an accessible tool for understanding pandemic trends.