AI and the Revival of Big Data / edited by Madan Mohan Tito Ayyalasomayajula.

Table Of Contents” -- “Title Page” -- “Copyright Page” -- “Table of Contents” -- “Detailed Table of Contents” -- “Preface” -- “Chapter 1: The Dawn of Big Data” -- “Chapter 2: Big Data Revolution” -- “Chapter 3: Hype vs. Reality” -- “Chapter 4: Technical Challenges in Scaling Data Infrastructure” -- “Chapter 5: Review on Big Data Analytics Applications” -- “Chapter 6: Shaping the Future” -- “Chapter 7: Optimizing AI Through Data Mining and Statistical Tools for Enhanced Model Performance” -- “Chapter 8: Optimizing Load Distribution in Big Data Ecosystems” -- “Chapter 9: Swarm Intelligence and Meta-Heuristics for Enhanced Optimization in Big Data Analytics” -- “Chapter 10: Resuming Transfer Technique for Two-Level Sharding Point of Rupture for a Single Table” -- “Chapter 11: Quantifying the Fiscal Ramifications of Big Data Integration in Service Organisations” -- “Chapter 12: Big Universe, Big Data Machine Learning, and Image Analysis for Astronomy” -- “Chapter 13: Artificial Intelligence, Machine Learning, and the Revival of Big Data in Pharmaceutical Sciences” -- “Chapter 14: AI-Based Automated Disease Detection Based on Symptoms Healthcare for Pets and Birds” -- “Chapter 15: Advanced Machine Learning Algorithms for Personalized Diabetic Foot Ulcer Treatment” -- “Compilation of References” -- “About the Contributors” -- “Index

The primary aim of this book is to offer a thorough analysis of Big Data's trajectory, focusing on its resurgence through AI technologies. It provides relevant theoretical frameworks and up-to-date empirical research findings to illuminate the strategic role of Big Data at different levels of the information and knowledge society

Description based on print version record.

Electronic reproduction. Ann Arbor, MI : ProQuest, 2018. Available via World Wide Web. Access may be limited to ProQuest affiliated libraries.