Overview

Volume 1 Table of Contents (Pg. 1-36), Chapters 1-7 (Pg. 1-161) Chapter 1: Introduction to Database Management Chapter 2: Data Models: Hierarchical, Network, Relational, and NoSQL Chapter 3: Importance of Databases in Modern Applications Chapter 4: Evolution of Database Technologies Chapter 5: Database Design: ER Diagrams and Normalization Chapter 6: Database Design: SQL Basics - Queries, Joins, Transactions Chapter 7: Introduction to Artificial Intelligence Chapters 8-12 (Pg. 162-326) Chapter 8: AI in Data Analysis and Decision Making Chapter 9: Role of AI in Modern Databases Chapter 10: AI-Driven Database Optimization Chapter 11: Predictive Analytics and Data Mining in Database Design Chapter 12: Introduction to Machine Learning Chapters 13-19 (Pg. 327-498) Chapter 13: Machine Learning in Databases Chapter 14: Natural Language Processing (NLP) in Databases Chapter 15: AI-Powered Database Design: Automated Schema Design Chapter 16: AI for Data Normalization and Integrity Chapter 17: Case Studies of AI-Driven Database Design Chapter 18: AI for Database Security: Threat Detection and Prevention Chapter 19: AI for Database Security: Anomaly Detection in Database Access Volume 2 Chapters 20-23 (Pg. 499-623) Chapter 20: AI for Data Encryption and Privacy Chapter 21: AI in Data Integration and ETL Processes: Data Cleaning and Transformation Chapter 22: Automated ETL Pipelines Chapter 23: Real-Time Data Integration with AI Chapters 24-25 (Pg. 624-768) Chapter 24: Query Optimization with AI Chapter 25: Indexing Strategies and AI Chapters 26-27 (Pg. 769-940) Chapter 26: Resource Management and Load Balancing Chapter 27: Predictive Analytics in AI Data Warehouses Volume 3 Chapters 28-29 (Pg. 941-1056) Chapter 28: Handling Large-Scale Data with AI for Big Data Management Chapter 29: AI in Distributed Databases for Big Data Chapters 30-32 (Pg. 1057-1175) Chapter 30: Big Data Analytics and AI Chapter 31: Cloud Database Services and AI Chapter 32: AI for Cloud Database Management Chapters 33-36 (Pg. 1176-1521) Chapter 33: Real-Time Data Processing with AI Chapter 34: AI in Database Maintenance and Monitoring Chapter 35: Ethical Considerations in AI and Databases Chapter 36: Innovations Shaping AI and Database Management Volume 4 Chapters 37-38 (Pg. 1522-1637) Chapter 37: The Future of Autonomous Databases Chapter 38: Tools and Technologies for AI in Databases Chapter 39 and Appendix A-E (Pg. 1638-1737) Chapter 39: Database Management Tools with AI Capabilities Appendix 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.

Full Product Details

9798258470522

Table of Contents

Reviews

Author Information

Tab Content 6

Countries Available