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This review paper provides a concise overview of Data Mining, a multidisciplinary field focused on extracting valuable insights and patterns from extensive datasets. It highlights the use of statistical analysis, machine learning, and pattern recognition techniques to discover hidden relationships and trends within data. The paper emphasizes data mining's significance as a powerful technology that extracts predictive information from large databases, enabling businesses to prioritize crucial data. It showcases how data mining tools predict future trends, empowering proactive, knowledge-driven decision-making. Furthermore, it discusses the superiority of data mining over retrospective tools, offering automated, prospective analyses to resolve complex business questions efficiently. It uncovers hidden patterns and predictive information beyond human expectations. The core concepts of data mining encountered challenges, data analysis techniques, and their profound impact on various domains are also addressed in this paper. The proposed paper offers a comprehensive overview of data mining's importance, applications, and transformative potential in modern data-driven decision-making processes.
Prajapati et al. (Thu,) studied this question.