COVID 19 DATA EXPLORATION (SQL)
About this project
This project demonstrates my proficiency in SQL data manipulation and analysis techniques, as well as my
ability to
derive actionable insights from complex datasets. The insights gained from this analysis can inform public
health
policies, vaccination strategies, and resource allocation efforts in combating the COVID-19 pandemic on a global
scale.
1 - Total COVID-19 Cases and Deaths:
Utilized SQL queries to retrieve data on total cases, new cases, total deaths, and population from the
CovidDeaths
table.
Calculated the percentage of deaths relative to total cases for each location.
2 - Infection Rate vs. Population:
Analyzed the relationship between total cases and population size to determine the infection percentage for
each
location.
3 - Countries with the Highest Infection Rates:
Identified countries with the highest infection rates compared to their respective populations, highlighting
the
severity of the pandemic's impact across different regions.
4 - Countries with the Highest Death Toll:
Investigated countries with the highest number of deaths, providing insights into the pandemic's mortality
rates
globally.
5 - Continental Analysis of Deaths:
Grouped COVID-19 deaths by continent to understand regional variations in mortality rates and identify
continents with
the highest death tolls.
6 - Global COVID-19 Statistics:
Calculated total cases, total deaths, and death percentages globally, offering a comprehensive overview of the
pandemic's global impact.
7 - Vaccination Analysis:
Integrated data from the CovidVaccination table to analyze vaccination rates relative to population size for
each
location.
7 - Visualization Data Preparation:
Created temporary tables and views to store and organize data for visualization purposes, ensuring efficient
data
retrieval and processing for future analysis.
