https://github.com/keerthanapalanikumar/data-exploration

This project focuses on exploring COVID-19 data using Microsoft SQL Server (MSSQL). The goal is to analyze various aspects of the pandemic, such as covid deaths, covid vaccinations, new case, population, and so on. By leveraging the power of MSSQL for data management and analysis
https://github.com/keerthanapalanikumar/data-exploration

Last synced: 6 days ago
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This project focuses on exploring COVID-19 data using Microsoft SQL Server (MSSQL). The goal is to analyze various aspects of the pandemic, such as covid deaths, covid vaccinations, new case, population, and so on. By leveraging the power of MSSQL for data management and analysis

• Host: GitHub
• URL: https://github.com/keerthanapalanikumar/data-exploration
• Owner: KeerthanaPalanikumar
• Created: 2024-05-08T16:26:57.000Z (6 months ago)
• Default Branch: main
• Last Pushed: 2024-06-16T05:32:56.000Z (5 months ago)
• Last Synced: 2024-06-16T06:34:33.042Z (5 months ago)
• Homepage:
• Size: 23.7 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# COVID-19 Data Exploration using MSSQL

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.