Data Cleaning and Preparation
Before organizations can trust analytical insights, they must ensure the integrity and quality of their underlying data. Raw datasets are rarely perfect; they often contain missing values, duplicated entries, inconsistent formats, and structural errors. Data cleaning and preparation, therefore, represent the most critical—but often underestimated—phase of the analytical lifecycle. Without thorough preparation, even the most […]