In this data engineering project, we'll establish a high-quality data foundation for the ShopSmart retail platform by performing rigorous data cleaning and preprocessing. We'll utilize Python and the pandas library to load raw customer records, identify data quality issues, and handle missing values to ensure analytical integrity. Our process includes standardizing categorical variables and treating numerical inconsistencies to create a uniform dataset. Through exploratory data visualization with Matplotlib and seaborn, we uncover underlying patterns and outliers, ultimately verifying the data quality to support reliable downstream machine learning applications.