This checklist provides a practical, step-by-step framework for cleaning and validating data before analysis. It guides readers through identifying data quality issues, handling missing or inconsistent values, and checking distributions and outliers. Designed for analytics and data teams, it helps ensure datasets are reliable, well-structured, and ready for downstream use.