DATA MINING METHODS FOR BUSINESS INTELLIGENCE

Abstract

Abstract - Data mining has become a fundamental component of Business Intelligence (BI), enabling organizations to discover hidden patterns, relationships, and trends within large volumes of data. By applying statistical techniques, machine learning algorithms, artificial intelligence, and database technologies, data mining transforms raw data into valuable knowledge that supports strategic planning and informed decision-making. Organizations across industries such as finance, healthcare, retail, manufacturing, education, telecommunications, and e-commerce use data mining to improve operational efficiency, predict customer behavior, detect fraud, optimize supply chains, and enhance business performance. Business Intelligence integrates data mining with data warehousing, data visualization, and analytical tools to provide timely and accurate information for managers and decision-makers. This paper discusses the concept, architecture, data mining methods, techniques, tools, applications, benefits, challenges, and future trends of data mining for Business Intelligence.

Keywords: Data Mining, Business Intelligence, Data Warehousing, Machine Learning, Predictive Analytics, Classification, Clustering, Association Rules, Decision Support Systems, Big Data.