Data Mining and Business Intelligence

A guide for both beginners and experienced learners As the author of this textbook, I hope this book will be a guide for both beginners and experienced learners. The eight chapters of Data Mining and Business Intelligence open a window into the power and responsibility of analytics by weaving conceptual rigor with practical exercises. It starts by revealing why data mining and business intelligence matter and how the balance of OLAP and OLTP systems shapes organizational insight. You then explore techniques for cleaning and pre processing data and for building regression and classification models that stand up in messy real world scenarios. Discovering hidden patterns through association rules teaches you to quantify insight with measurements of support confidence and lift before applying the apriori algorithm to uncover unexpected relationships. The chapter on clustering brings methods like k means and more advanced approaches to life in R examples that show how grouping data can reveal new perspectives. A deep dive into the fundamentals of business intelligence will challenge your assumptions about market forces key vendors and the trends that will define the future. Building on this foundation you will design BI architecture model data effectively and learn to create compelling interactive dashboards with Power BI. In the next chapter you will confront the complexity of text mining cognitive analytics big data and real time analytics and develop a mindset for innovation. The exploration concludes with a thoughtful examination of data governance and ethics that privacy transparency and fairness at every step. Each chapter closes with probing questions multiple choice quizzes and exercises with worked solutions to ensure that when you finish this book you will be ready to face real world data challenges with confidence and insight. -- Dr Jyotiranjan