The Covid-19 Tracker Project is a dedicated initiative focused on cleaning, analyzing, and visualizing Covid-19 data to provide valuable insights. Leveraging SQL queries and Python scripts, this project aims to answer specific questions related to the Covid-19 pandemic. The primary data points of interest include infection rates, deaths, and vaccination statistics.

The project follows a meticulous process of data cleaning, ensuring accuracy and reliability in the analysis. SQL queries are employed to extract relevant data from the dataset, enabling in-depth exploration. Python scripts are then utilized to perform advanced analytics and generate meaningful insights from the extracted data.

To enhance the understanding and accessibility of the findings, the project utilizes Tableau Public for data visualization. With Tableau, interactive dashboards and visualizations are created to showcase the patterns, trends, and relationships within the data. This visual representation allows stakeholders to gain a comprehensive overview of the Covid-19 situation, facilitating informed decision-making and raising public awareness.

By analyzing infection rates, deaths, and vaccination data, the Covid-19 Tracker Project provides a holistic view of the pandemic's impact. It uncovers key insights such as hotspot regions, demographic patterns, vaccination progress, and the effectiveness of preventive measures. These insights serve as a valuable resource for policymakers, healthcare professionals, researchers, and the general public.

The Covid-19 Tracker Project offers a comprehensive overview of the pandemic through rigorous data analysis, providing actionable insights to combat the spread of the virus and mitigate its impact. By utilizing SQL, Python, and Tableau Public, this project demonstrates the power of data-driven approaches in understanding and responding to the Covid-19 crisis.

World Health Organization data sources :Click here

Tableau public dashboard :Click here