COVID-19 is a contagious virus that caused a global pandemic, affecting millions of people worldwide.This project involves the exploration of COVID-19 data using various SQL techniques in Microsoft SQL Server. The purpose is to analyze and gain insights from the data related to COVID-19 cases, deaths, and population impacts across different locations.
The analysis is based on two datasets:
- CovidDeaths: This dataset contains information on COVID-19 cases and deaths, including details such as location, date, total cases, new cases, total deaths, population, and various health metrics.
- CovidVaccinations: This dataset includes data on COVID-19 vaccinations, such as the total number of vaccinations, people vaccinated, people fully vaccinated, and other related metrics.
Analysis of the COVID-19 data revealed that countries with higher total cases often had higher total deaths, with certain locations like the United States showing significant death percentages relative to their total cases. Infection rate analysis indicated that densely populated countries experienced higher infection percentages, underscoring the role of population density in virus spread. Additionally, vaccination data can provide insights into the effectiveness of vaccination campaigns and their correlation with reductions in COVID-19 cases and deaths.