(untitled) (Journal of Advances and Scholarly Researches in Allied Education, 2019)
Data mining aims to discover hidden knowledge, unknown patterns, and new rules from large databases that are potentially useful and ultimately understandable for making crucial decisions. It applies data analysis and knowledge discovery techniques under acceptable computational efficiency limitations, and produces a particular enumeration of patterns over the data. The insights obtained via a higher level of understanding of data can help iteratively improve business practice.Data mining is able to uncover unknown patterns and predict future trends and behaviors in financial markets. It creates opportunities for companies to make proactive and knowledge-driven decisions in order to gain a competitive advantage. Data mining has been applied to a number of financial applications, including development of trading models, investment selection, loan assessment, portfolio optimization, fraud detection, bankruptcy prediction, real-estate assessment, and so on. The competitive advantages achieved by data mining include increased revenue, reduced cost, and much improved marketplace responsiveness and awareness.