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.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
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Da: PBShop.store UK, Fairford, GLOS, Regno Unito
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Da: CitiRetail, Stevenage, Regno Unito
Paperback. Condizione: new. Paperback. 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 Intelligence Chapters 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 Learning Chapters 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 Access Volume 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 AI Chapters 24-25 (Pg. 624-768) Chapter 24: Query Optimization with AIChapter 25: Indexing Strategies and AI Chapters 26-27 (Pg. 769-940) Chapter 26: Resource Management and Load BalancingChapter 27: Predictive Analytics in AI Data Warehouses Volume 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 Management Volume 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Codice articolo 9798258483249
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