COVID-19 SQL Data Analysis

Summary:

This portfolio project showcases my SQL skills in analyzing COVID-19 data sourced from Our World In Data. Leveraging fundamental SQL features and techniques, I present insightful queries to gain valuable insights into the global pandemic. These queries demonstrate my proficiency in using basic SQL functionalities.

Key SQL Features Demonstrated:

1. Basic Retrieval:

- Utilizing SELECT statements to retrieve data from the "covid-deaths" and "covid-vaccinations" tables.

- Employing ORDER BY clause for result sorting.

2. Aggregate Functions:

- Calculating percentages using aggregate functions such as MAX, MIN, and SUM.

- Deriving metrics like the percentage of cases fatal and percentage of population infected.

3. Grouping and Filtering:

- Employing GROUP BY clause to aggregate data at the country and continent levels.

- Filtering data based on specific conditions, like excluding 'null' continents to only show countries.

4. Window Functions:

- Implementing window functions for rolling calculations.

- Showcasing the use of PARTITION BY for aggregating data over specific criteria.

5. Common Table Expressions (CTEs):

- Using CTEs for readability and efficiency in calculating the percent of a country's population vaccinated over time.

6. Temporary Tables:

- Employing temporary tables to store intermediate results for further analysis.

7. Creating Views:

- Creating a view for seamless data retrieval, facilitating data visualization.

Project Overview:

- Total Cases vs Total Deaths (UK): Analyzing the progression of COVID-19 cases and deaths in the United Kingdom.

- Infection and Death Rates (Global & Country Level): Calculating infection rates, death rates, and their variations across different countries.

- Death Count by Continent: Investigating total deaths by continent for a comprehensive overview.

- Global Vaccination Analysis: Utilizing CTEs, temporary tables, and views to analyze vaccination data globally and at the country level.

Project Source:

The dataset spans from 2020 to 2024 (https://ourworldindata.org/covid-deaths), with "covid-deaths" excluding vaccination statistics and "covid-vaccinations" excluding infection and death statistics. The project draws inspiration from the Alex The Analyst tutorial (

).

Feel free to explore the queries and gain insights into the dynamic analysis of COVID-19 data.

Available on GitHub:

https://github.com/SamMortimer4/COVID-19-SQL-Data-Analysis-Project