Mapping the Pandemic: Tableau Insights on COVID-19’s Global Impact

**Visit my GitHub for project details, code, queries, and documentation.

Objectives:

This project leverages advanced Tableau visualizations to analyze the COVID-19 pandemic's impact as of March 2021. Focused on presenting clear, digestible insights, the dashboard visualizes critical aspects of the pandemic, including infection rates, death rates, and geographical distributions of cases. The objective is to provide an accessible yet comprehensive view of the global health crisis across different regions.

Visualizing the Pandemic: Tableau Dashboard Insights into COVID-19

  1. Percent Population Infected per Country: Highlights the percentage of the population infected in each country, providing a visual representation of the global spread of the virus. This map allows users to instantly grasp which regions have been most affected by the pandemic, showcasing disparities in infection rates worldwide.

  2. Timeline of Infection Rates: Details the timeline of infection rates for selected countries, tracing the evolution of the pandemic over time. This visualization helps identify peaks and trends in infection rates.

  3. Global Figures: Simple statistics, including total cases, total deaths, and the overall death percentage. Provides a quick reference to the pandemic's scale and lethality, encapsulating the immense human impact in numerical terms.

  4. Total Deaths per Continent: Compares the total deaths across continents, illustrating the varying degrees of impact across different global regions. This visualization emphasizes the differential mortality rates and highlights regions that have been particularly hard-hit.

Comprehensive Data Analysis Using SQL and Tableau

All visualizations are underpinned by data analysis performed using SQL queries, with the processed datasets as the backbone for the interactive Tableau dashboard.

Each chart and map is designed to offer both macroscopic insights, ensuring viewers can understand the pandemic from multiple perspectives.

The SQL queries and datasets used in this project are openly available on my personal GitHub page, allowing for further exploration and verification of the analysis presented.