Sales CSV: 5% missing prices (impute median), 200 duplicate rows (drop), one $999999 price (outlier: cap or investigate), dates as strings (parse to datetime), 'NY' vs 'New York' (standardize). Cleaned data trains reliable models; dirty data silently corrupts.