Data mining is the process of discovering patterns, correlations, and anomalies within large datasets to predict outcomes. By applying a variety of techniques from statistics, machine learning, and database systems, data mining transforms raw data into valuable insights. This paper explores the methodologies and applications of data mining, highlighting its significance in fields such as finance, healthcare, and marketing. Key techniques discussed include classification, clustering, regression, and association rule learning. The study also addresses the challenges and future directions in data mining, emphasizing the need for scalable and efficient algorithms to handle the ever-increasing volume of data.