This project involves the thorough analysis of COVID-19 data utilizing SQL techniques to extract meaningful insights and trends. The main goal of this project is to gain a comprehensive understanding of the pandemic's impact on different regions and timeframes.
The project focuses on employing various SQL techniques to explore and analyze COVID-19 data. It utilizes joins, CTEs, temporary tables, window functions, aggregate functions, and creating views to achieve the following objectives: •Consolidate data from multiple sources to amalgamate case counts, deaths, and population data.
• Break down complex operations into manageable components using CTEs, enhancing query readability.
• Optimize query performance through temporary tables to reduce redundant calculations.
• Enhance reusability by creating a view named "PercentPopulationVaccinated" for vaccination percentage calculations.
Contains a series of SQL queries that explore various aspects of the COVID-19 data. Each query addresses a specific analysis objective, demonstrating different SQL techniques.