Business Intelligence through Data Mining Process, Methods & Algorithms - Week 4A

In data-driven world, organizations rely on Business Intelligence (BI) and Data Mining techniques to transform raw data into valuable insights for strategic decision-making. This session provides a comprehensive introduction to the fundamental concepts, applications, processes, methods, and algorithms used in modern data modeleing. Topics Covered: Data Mining Concepts • What is Data Mining? • Relationship between Data Mining and Business Intelligence • Cross Industry Standard Process for Data Mining (CRISP-DM) • SEMMA • Knowledge Discovery in Databases (KDD) • Data, Information, and Knowledge Data Mining Applications • Marketing and Customer Analytics • Financial Analysis and Risk Assessment • Healthcare Analytics • Fraud Detection • E-commerce and Recommendation Systems Data Mining Process • Business Understanding • Data Collection and Integration • Data Preparation and Cleaning • Data Exploration Data Mining Methods and Algorithms • Classification • Clustering • Association Rule Mining • Regression Analysis • Decision Trees • Naïve Bayes • K-Means Clustering • Neural Networks • Receiver Operating Characteristic (ROC) curve Data Mining Tools and Issues • Popular Data Mining Software and Platforms