SQL PROJECTS

DATA CLEANING IN SQL

In this project, I tackle the challenge of transforming messy raw housing data into reliable, analyzable insights using SQL. Through data exploration, I identified and corrected inconsistencies, missing values, and formatting errors. My cleaning pipeline involved techniques like outlier detection, imputation strategies, and data standardization. This project not only honed my SQL proficiency but also demonstrated my ability to transform raw data into valuable assets, ultimately increasing data-driven decision-making capabilities.

COVID 19 DATA EXPLORATION

In this project, I delve into the complexities of global COVID-19 data to uncover impactful insights using a comprehensive SQL skillset. By leveraging joins, CTEs, and temporary tables, I integrated data from diverse sources like confirmed cases, deaths, vaccinations, and population statistics. Employing window functions and aggregate functions, I extracted and summarized key trends across countries and continents, analyzing infection rates, mortality patterns, and vaccination progress. By creating custom views and converting data types, I transformed raw data into readily digestible formats for further analysis and visualization.