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This is an analysis of Covid 19 dataset using multiple SQL queries. The dataset used for this analysis includes various information regarding COVID-19 cases such as confirmed cases, deaths, and recoveries, segmented by different geographical locations and time periods.

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Tynoee/Covid19_Data_Analysis

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๐Ÿฆ  COVID-19 Data Analysis & Visualization

This project analyzes and visualizes global COVID-19 trends using SQL and Tableau. The dataset includes key metrics such as confirmed cases, deaths, vaccinations, and recoveries, segmented by country, continent, and time.

๐Ÿงน Data Cleaning & Preparation

  • The original dataset was cleaned and pre-processed using Microsoft Excel.
  • It was split into two main tables:
    • CovidDeaths
    • CovidVaccinations
  • These tables were then imported into SQL Server for querying and analysis.

๐Ÿ›  Tools & Technologies

  • Microsoft Excel โ€“ Initial data cleaning and formatting
  • SQL Server โ€“ Data querying and aggregation
  • Tableau Public โ€“ Interactive data visualization

๐Ÿ“Š Tableau Dashboard

The interactive dashboard visualizes global and regional COVID-19 trends, featuring:

  • Global Numbers
  • Percent Population Infected Per Country
  • Total Deaths Per Continent
  • Percent Population Infected

๐Ÿ”— View the COVID-19 Dashboard on Tableau Public

๐Ÿ“Œ Key Insights

  • Some countries had disproportionately high infection rates relative to population size.
  • Vaccination rollout pace varied widely by region.
  • Death rates showed stark contrasts between continents.

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This is an analysis of Covid 19 dataset using multiple SQL queries. The dataset used for this analysis includes various information regarding COVID-19 cases such as confirmed cases, deaths, and recoveries, segmented by different geographical locations and time periods.

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