Data Cleaning involves the process of identifying and correcting inaccuracies or inconsistencies within datasets. This step is crucial in data management to ensure the reliability and quality of insights drawn from data analysis. Techniques include removing duplicates, filling in missing values, and standardizing data formats. Effective data cleaning enhances the overall analytical process and facilitates better decision-making. Organizations that prioritize data cleanliness gain a competitive advantage by leveraging high-quality information, resulting in more accurate reporting and strategic planning.