#COVID Analysis SQL Project
#Project Overview
This project involves analyzing COVID-19 data using SQL queries. The dataset includes tables related to COVID cases, deaths, and vaccinations. The goal is to derive meaningful insights such as death rates, vaccination coverage, and the pandemic's impact on different continents and populations.
#Dataset Description
CovidDeaths:
Contains information on COVID cases, deaths, and population data categorized by location and date.
Key fields: location, date, total_cases, new_cases, total_deaths, population.
CovidVaccinations:
Includes vaccination details across locations.
Key fields: location, date, total_vaccinations, population.
Key Analysis Tasks
General Data Exploration: View and understand the structure of the data.
Mortality Analysis:
Calculate the likelihood of dying from COVID by comparing total deaths to total cases.
Analyze daily death percentages based on new cases and deaths.
Continental Comparisons:
Total cases, deaths, and death percentages across continents.
Percentage of the population affected in each continent.
Vaccination Insights:
Percentage of vaccinated population by location.
Analyze the relationship between cases, deaths, and vaccination rates.
#SQL Queries Highlights
Summarize global and continental COVID statistics.
Compare vaccination rates and their effectiveness in reducing cases and deaths.
Merge data from CovidDeaths and CovidVaccinations to perform combined analysis.
#How to Use
Database Setup: Import the dataset into your SQL server.
Run Queries: Execute the provided SQL queries in a sequential manner for insights.
Modify Queries: Adapt the queries to focus on specific regions or timeframes if needed.
#Results
Insights into global and continental mortality and vaccination trends.
Identification of regions with the highest impact and lowest vaccination coverage.
#Tools Used
SQL for data querying and analysis.
SQL Server for managing the database.
License
This project is open-source and available under the MIT License.
Author
Levis Okoth Owuor