This project involves analyzing Covid-19 data using various SQL techniques, including joins, common table expressions (CTEs), temporary tables, window functions, aggregate functions, creating views, and converting data types. Key analyses include:

• Initial Data Selection: Filtering and ordering Covid-19 death data.
• Total Cases vs. Total Deaths: Calculating death percentage among confirmed cases in different locations.
• Total Cases vs. Population: Determining the percentage of the population infected with Covid-19.
• Infection Rates: Identifying countries with the highest infection rates compared to their populations.
• Death Counts: Finding countries and continents with the highest total death counts.
• Global Statistics: Summarizing global new cases and deaths, and calculating the global death percentage.
• Vaccination Analysis: Examining vaccination data to find the percentage of populations vaccinated using rolling sums.
• Using CTEs and Temp Tables: Performing calculations with CTEs and temporary tables to determine vaccination percentages.
• Creating Views: Storing vaccination data for future visualizations.

This project provides insights into Covid-19's impact across different regions and the effectiveness of vaccination campaigns.