This repository contains a project focused on conducting statistical analysis of COVID-19 data using SQL queries and data visualization techniques. The goal of this project is to explore trends, patterns, and insights derived from comprehensive statistical analysis of COVID-19 data.
The project utilizes SQL queries to extract, transform, and analyze COVID-19 data from relevant databases. Advanced SQL techniques including joins, CTEs, temp tables, and window functions are employed to perform in-depth analysis of various factors such as total cases, total deaths, death percentages, population percentages, and vaccination rates.
Data visualizations are created to effectively communicate the findings of the analysis. These visualizations help in understanding the trends and patterns in COVID-19 data, enabling informed decision-making for public health strategies.
SQL_queries.sql: Contains the SQL queries used for data extraction, transformation, and analysis.CovidDeaths.xlsx: Excel file containing COVID-19 death data.CovidVaccinations.xlsx: Excel file containing COVID-19 vaccination data.