What is the role of data cleaning in data management?

Data cleaning plays a critical role in data management by ensuring that the information being analyzed is accurate, complete, and consistent. This process involves identifying and correcting errors, removing duplicates, and addressing inconsistencies within the dataset. When data is clean, it enhances the reliability of the results derived from data analysis. Improved accuracy in data analysis leads to better decision-making, more effective strategies, and more trustworthy insights for stakeholders.

While collecting more data, storing data securely, and processing raw data are essential aspects of data management, they do not specifically address the quality of data that is available for analysis. Data cleaning focuses on refining and improving existing data, making it a vital step for achieving reliable outcomes from data-driven processes.