https://github.com/vidushibhadana/covid19-data-exploration-using-sql
Deployed diverse SQL techniques to analyze COVID-19 data for an improved understanding of pandemic's regression.
https://github.com/vidushibhadana/covid19-data-exploration-using-sql
data database database-management sql
Last synced: 10 months ago
JSON representation
Deployed diverse SQL techniques to analyze COVID-19 data for an improved understanding of pandemic's regression.
- Host: GitHub
- URL: https://github.com/vidushibhadana/covid19-data-exploration-using-sql
- Owner: vidushibhadana
- Created: 2024-10-15T20:59:44.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-10-24T10:57:54.000Z (over 1 year ago)
- Last Synced: 2025-01-11T00:12:39.535Z (over 1 year ago)
- Topics: data, database, database-management, sql
- Homepage:
- Size: 39.5 MB
- Stars: 0
- Watchers: 1
- Forks: 1
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# COVID-19 Data Exploration Project
This project involves the thorough analysis of COVID-19 data utilizing SQL techniques to extract meaningful insights and trends. The main goal of this project is to gain a comprehensive understanding of the pandemic's impact on different regions and timeframes.
# Project Overview
The project focuses on employing various SQL techniques to explore and analyze COVID-19 data. It utilizes joins, CTEs, temporary tables, window functions, aggregate functions, and creating views to achieve the following objectives: •Consolidate data from multiple sources to amalgamate case counts, deaths, and population data.
• Break down complex operations into manageable components using CTEs, enhancing query readability.
• Optimize query performance through temporary tables to reduce redundant calculations.
• Enhance reusability by creating a view named "PercentPopulationVaccinated" for vaccination percentage calculations.
Project Structure
Contains a series of SQL queries that explore various aspects of the COVID-19 data. Each query addresses a specific analysis objective, demonstrating different SQL techniques.