INTELLIGENT DATA ANALYTICS

This comprehensive textbook offers a complete guide to modern data analytics, bridging the gap between raw data and actionable intelligence. Structured around the CRISP-DM lifecycle, it progresses from foundational concepts through core techniques to advanced topics and real-world applications. Part I covers data fundamentals, preprocessing, and exploratory analysis. Part II details statistical methods, machine learning, deep learning, and data mining algorithms. Part III explores streaming analytics, data privacy/ethics, and scalable cloud architectures. Part IV presents cross-industry case studies in healthcare, finance, retail, and manufacturing, culminating in emerging trends like generative AI, causal inference, quantum computing, and agentic systems. Designed for students and practitioners, the book balances theoretical grounding with practical insights, hands-on exercises, and a focus on responsible AI. It emphasizes interpretability, MLOps, and human-AI collaboration, preparing readers for the evolving analytics landscape. With its structured roadmap, real-world vignettes, and comprehensive tool coverage, it serves as an essential resource for building and deploying.