Data Exploration in SQL
About this project
This SQL project involves exploring Covid-19 data, showcasing a variety of skills and techniques used to perform data analysis in SQL. The project uses joins, CTEs, temp tables, window functions, aggregate functions, creating views, and converting data types to explore data in different ways.
The project begins by selecting and ordering data that will be used for subsequent analyses. The subsequent queries explore various aspects of the data, such as:
- The likelihood of dying if you contract Covid-19 in your country
- The percentage of the population infected with Covid-19
- Countries with the highest infection rate compared to their population
- Countries with the highest death count per population
The project also breaks down data by continent, showing continents with the highest death count per population. Additionally, the project looks at global numbers, including the total number of cases and deaths, as well as the percentage of the population that has received at least one Covid-19 vaccine.
The project uses CTEs and temp tables to perform calculations on partitioned data and create new tables that can be used for subsequent analyses. Finally, the project creates a view to store data for later visualizations.
