What is the purpose of data mining in the knowledge discovery process?

Data mining plays a crucial role in the knowledge discovery process by helping to uncover hidden patterns, correlations, or trends within large sets of data. This is essential for organizations, especially in healthcare, where vast amounts of data are generated daily. By identifying patterns, data mining can provide valuable insights that aid in decision-making, predictive modeling, and improving operational efficiency.

The purpose of data mining transcends simply securing information, deleting data, or creating new entries. While securing sensitive information is vital for data protection, it is not the main focus of data mining. Similarly, deleting redundant data is an important aspect of data management, but it does not involve the analysis or exploration of data patterns. Creating new data entries relates to data generation rather than the analytical process inherent in data mining. Thus, discovering correlations or patterns is the primary objective, making it a fundamental element of transforming raw data into actionable knowledge.