{"id":28640360,"url":"https://github.com/tynoee/covid19_data_analysis","last_synced_at":"2026-02-16T13:05:04.146Z","repository":{"id":229665126,"uuid":"777317537","full_name":"Tynoee/Covid19_Data_Analysis","owner":"Tynoee","description":"This is an analysis of Covid 19 dataset using multiple SQL queries. 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The dataset includes key metrics such as confirmed cases, deaths, vaccinations, and recoveries, segmented by country, continent, and time.\n\n## 🧹 Data Cleaning \u0026 Preparation\n\n- The original dataset was cleaned and pre-processed using **Microsoft Excel**.\n- It was split into two main tables:\n  - `CovidDeaths`\n  - `CovidVaccinations`\n- These tables were then imported into **SQL Server** for querying and analysis.\n\n## 🛠 Tools \u0026 Technologies\n\n- **Microsoft Excel** – Initial data cleaning and formatting  \n- **SQL Server** – Data querying and aggregation  \n- **Tableau Public** – Interactive data visualization\n\n## 📊 Tableau Dashboard\n\nThe interactive dashboard visualizes global and regional COVID-19 trends, featuring:\n\n- **Global Numbers**  \n- **Percent Population Infected Per Country**  \n- **Total Deaths Per Continent**  \n- **Percent Population Infected**  \n\n🔗 [View the COVID-19 Dashboard on Tableau Public](https://public.tableau.com/app/profile/tinotenda.chidume/viz/Covid19Dashboard_17480847809640/Dashboard1?publish=yes)  \n\n## 📌 Key Insights\n\n- Some countries had disproportionately high infection rates relative to population size.\n- Vaccination rollout pace varied widely by region.\n- Death rates showed stark contrasts between continents.\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftynoee%2Fcovid19_data_analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftynoee%2Fcovid19_data_analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftynoee%2Fcovid19_data_analysis/lists"}