This project focuses on data cleaning and formatting using Microsoft Excel, transforming raw and inconsistent datasets into structured, accurate, and analysis-ready information. The project includes handling missing values, removing duplicates, correcting formatting issues, standardizing data entries, and organizing datasets for better readability and efficiency. Various Excel features such as sorting, filtering, conditional formatting, formulas, and data validation were used to improve data quality and maintain consistency. The main objective of this project is to demonstrate practical data preprocessing skills that help businesses and analysts make reliable, data-driven decisions from clean and well-structured datasets.