π Overview
Database Management Using AI: A Comprehensive Guide is a definitive resource for understanding how artificial intelligence is transforming modern database systems.
Designed for database administrators, data scientists, developers, and technology professionals, this guide bridges the gap between traditional database concepts and AI-driven innovation.
It delivers a clear, practical, and industry-focused approach to integrating AI into data management.
π What This Book Covers
πΉ Foundation First
The guide begins with core database concepts, including:
Data models (Relational & NoSQL)
SQL fundamentals
Database design principles
πΉ AI-Powered Database Management
You will learn how AI enhances databases through:
Query optimization
Automated schema design
Intelligent data retrieval
Performance tuning
πΉ Real-World Applications
Unlike purely theoretical books, this guide emphasizes practical implementation with case studies across:
E-commerce
Healthcare
Finance
Logistics
π Demonstrating how AI improves efficiency, reduces errors, and enables smarter decision-making.
πΉ Advanced Concepts
The book explores:
Predictive analytics & data mining
AI-driven security and anomaly detection
Automation of repetitive database tasks
Big data and cloud database integration
πΉ Future of Databases
Gain insights into emerging trends:
Autonomous databases
Cloud-based AI solutions
Intelligent, self-managing systems
π― Key Value
π Move from theory β practical implementation β real-world impact
This book equips you with the skills needed to build, optimize, and manage AI-powered database systems.
π Database Management Using AI β 12 Volume Collection
Each volume is carefully structured to cover fundamentals, advanced concepts, and real-world AI applications in database management.
π Volume 1
Table of Contents (Pg. 1β36), Chapters 1β7 (Pg. 1β161)
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: SQL Basics β Queries, Joins, Transactions
Chapter 7: Introduction to Artificial Intelligence
π Order Volume 1: https://www.amazon.com/dp/B0DKXYVM2L
π Volume 2
Chapters 8β12 (Pg. 162β326)
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
Chapter 12: Introduction to Machine Learning
π Order Volume 2: https://www.amazon.com/dp/B0DL2HGRJH
π Volume 3
Chapters 13β19 (Pg. 327β498)
Chapter 13: Machine Learning in Databases
Chapter 14: Natural Language Processing (NLP) in Databases
Chapter 15: Automated Schema Design
Chapter 16: Data Normalization and Integrity
Chapter 17: Case Studies of AI-Driven Database Design
Chapter 18: Database Security: Threat Detection
Chapter 19: Anomaly Detection in Database Access
π Order Volume 3: https://www.amazon.com/dp/B0DL4H7XTT
π Volume 4
Chapters 20β23 (Pg. 499β623)
Chapter 20: AI for Data Encryption and Privacy
Chapter 21: AI in ETL Processes (Data Cleaning & Transformation)
Chapter 22: Automated ETL Pipelines
Chapter 23: Real-Time Data Integration with AI
π Order Volume 4: https://www.amazon.com/dp/B0DL45W9DK
π Volume 5
Chapters 24β25 (Pg. 624β768)
Chapter 24: Query Optimization with AI
Chapter 25: Indexing Strategies and AI
π Order Volume 5: https://www.amazon.com/dp/B0DL45CTPG
π Volume 6
Chapters 26β27 (Pg. 769β940)
Chapter 26: Resource Management and Load Balancing
Chapter 27: Predictive Analytics in AI Data Warehouses
π Order Volume 6: https://www.amazon.com/dp/B0DL4HHW2H
π Volume 7
Chapters 28β29 (Pg. 941β1056)
Chapter 28: Large-Scale Data Management with AI
Chapter 29: AI in Distributed Databases
π Order Volume 7: https://www.amazon.com/dp/B0DL4KKV5M
π Volume 8
Chapters 30β32 (Pg. 1057β1175)
Chapter 30: Big Data Analytics and AI
Chapter 31: Cloud Database Services
Chapter 32: AI for Cloud Database Management
π Order Volume 8: https://www.amazon.com/dp/B0DL572Q8F
π Volume 9
Chapters 33β36 (Pg. 1176β1521)
Chapter 33: Real-Time Data Processing with AI
Chapter 34: Database Monitoring and Maintenance
Chapter 35: Ethical Considerations in AI
Chapter 36: Innovations in AI and Database Management
π Order Volume 9: https://www.amazon.com/dp/B0DL5ZKKWG
π Volume 10
Chapters 37β38 (Pg. 1522β1637)
Chapter 37: Future of Autonomous Databases
Chapter 38: Tools and Technologies for AI in Databases
π Order Volume 10: https://www.amazon.com/dp/B0DL61DBBW
π Volume 11
Chapter 39 & Appendix AβE (Pg. 1638β1737)
Chapter 39: Database Management Tools with AI Capabilities
π Order Volume 11: https://www.amazon.com/dp/B0DL617RXJ
π Volume 12
Appendix FβG (Pg. 1738β1908)
π Order Volume 12: https://www.amazon.com/dp/B0DLB9N9ZB
π About the Collection
Each volume delivers a unique perspective on database management in the AI era, covering everything from foundational design principles to advanced AI applications and ethical considerations.
π Key highlights include:
AI-driven database optimization (Chapter 10)
Ethical considerations in AI (Chapter 35)
π― Why This Collection Matters
This 12-volume series is both:
π An academic reference
πΌ A practical guide for professionals
π Helping readers stay ahead in a data-driven, AI-powered world
π Connect with the Author
π LinkedIn:
https://www.linkedin.com/in/anthem-purushotham-reddy
β Medium Articles:
https://medium.com/@reddyapuru
π Official Website:
https://www.latest2all.com
π Amazon Author Page:
https://www.amazon.com/author/anthem-purushotham-reddy
βΆοΈ YouTube Channel Page:
https://www.youtube.com/@Artificial-intelligence-1985
Book intro @ https://youtu.be/pkhPG8Rq1gY
π§ Email: For bulk orders please contact @
reddyapuru@gmail.com
A. Purushotham Reddy is a software engineer and AI practitioner focused on turning artificial intelligence into real-world applications, data-driven decisions, and practical outcomes.
He holds an M.Tech in VLSI Design and Embedded Systems and has contributed to academic research through his publication, βApplication with MUCOS RTOS on Embedded Systems,β in the International Journal of Innovative Research in Electrical, Electronics, Instrumentation and Control Engineering (Vol. 2, Issue 12, December 2014).
He is a Certified Data Science and PMP professional, combining expertise in AI, data analytics, and structured problem-solving to build scalable and impactful solutions.
With over 8 years of experience in the education sector, he has specialized in developing content that simplifies complex technologies and makes them accessible, actionable, and industry-relevant.
His work centers on helping learners and professionals:
Apply AI and data analytics to real-world problems
Build intelligent systems and automation workflows
Make smarter, data-driven decisions
Through his book Database Management Using AI, he provides a practical approach to integrating AI with database systems, enabling readers to move from theory to implementation and measurable results.
His mission is to make AI usable, actionable, and valuable for career growth and real-world impact.
Contributed to the initial conceptual design of the e-book by outlining Table-of-Contents (TOC).
Reviewed Graphics design for good visual-feel of e-book