Overview

In an era where organizations are inundated with data yet often struggle to convert it into meaningful action, the convergence of Artificial Intelligence and Generative AI has redefined what is possible in analytics. AI and Generative AI for Data Analytics: From Raw Data to AI-Augmented Insights and Decisions explores this transformation end to end, beginning with the foundations of analytics and progressing toward the advanced capabilities enabled by modern AI systems. Whether predicting demand, segmenting customers, uncovering hidden patterns, or generating narratives that translate complexity into clarity, today's analytical workflows are more intelligent, adaptive, and automated than ever before. This book aims to demystify these capabilities and provide a structured pathway to building real-world AI-powered analytics solutions. The book guides readers through data foundations, feature engineering, supervised and unsupervised learning, time-series modeling, text analytics, and the emerging frontier of generative AI for simulation, enrichment, and storytelling. It emphasizes not only technical techniques but also responsible AI practices, governance, and operationalization, elements essential for sustainable, trustworthy analytics in modern enterprises. Whether you are a data practitioner, business leader, or student, this book equips you with the conceptual understanding, practical tools, and strategic frameworks needed to transform raw data into reliable, AI-augmented insights and decisions.

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