Database management Using AI- Volume2: Paperback Edition

Volume 1Table of Contents (Pg. 1-36), Chapters 1-7 (Pg. 1-161)Chapter 1: Introduction to Database ManagementChapter 2: Data Models: Hierarchical, Network, Relational, and NoSQLChapter 3: Importance of Databases in Modern ApplicationsChapter 4: Evolution of Database TechnologiesChapter 5: Database Design: ER Diagrams and NormalizationChapter 6: Database Design: SQL Basics - Queries, Joins, TransactionsChapter 7: Introduction to Artificial IntelligenceChapters 8-12 (Pg. 162-326)Chapter 8: AI in Data Analysis and Decision MakingChapter 9: Role of AI in Modern DatabasesChapter 10: AI-Driven Database OptimizationChapter 11: Predictive Analytics and Data Mining in Database DesignChapter 12: Introduction to Machine LearningChapters 13-19 (Pg. 327-498)Chapter 13: Machine Learning in DatabasesChapter 14: Natural Language Processing (NLP) in DatabasesChapter 15: AI-Powered Database Design: Automated Schema DesignChapter 16: AI for Data Normalization and IntegrityChapter 17: Case Studies of AI-Driven Database DesignChapter 18: AI for Database Security: Threat Detection and PreventionChapter 19: AI for Database Security: Anomaly Detection in Database AccessVolume 2Chapters 20-23 (Pg. 499-623)Chapter 20: AI for Data Encryption and PrivacyChapter 21: AI in Data Integration and ETL Processes: Data Cleaning and TransformationChapter 22: Automated ETL PipelinesChapter 23: Real-Time Data Integration with AIChapters 24-25 (Pg. 624-768)Chapter 24: Query Optimization with AIChapter 25: Indexing Strategies and AIChapters 26-27 (Pg. 769-940)Chapter 26: Resource Management and Load BalancingChapter 27: Predictive Analytics in AI Data WarehousesVolume 3Chapters 28-29 (Pg. 941-1056)Chapter 28: Handling Large-Scale Data with AI for Big Data ManagementChapter 29: AI in Distributed Databases for Big DataChapters 30-32 (Pg. 1057-1175)Chapter 30: Big Data Analytics and AIChapter 31: Cloud Database Services and AIChapter 32: AI for Cloud Database ManagementChapters 33-36 (Pg. 1176-1521)Chapter 33: Real-Time Data Processing with AIChapter 34: AI in Database Maintenance and MonitoringChapter 35: Ethical Considerations in AI and DatabasesChapter 36: Innovations Shaping AI and Database ManagementVolume 4Chapters 37-38 (Pg. 1522-1637)Chapter 37: The Future of Autonomous DatabasesChapter 38: Tools and Technologies for AI in DatabasesChapter 39 and Appendix A-E (Pg. 1638-1737)Chapter 39: Database Management Tools with AI CapabilitiesAppendix F-G (Pg. 1738-1908)Each volume delivers a unique perspective on database management in the AI era, with comprehensive coverage from foundational design principles to ethical considerations in AI applications. Highlights include Chapter 10 on AI-driven optimization and Chapter 35 on ethical concerns, making this collection both an academic treasure and a professional essential.Whether you're exploring databases for academic purposes or incorporating AI into your professional toolkit, this hardcover set is designed to be a lasting reference in the evolving world of data management. Read more