AI and the Revival of Big Data

AI and the Revival of Big Data

Madan Mohan Tito Ayyalasomayajula (Aspen University, USA)
Release Date: February, 2025|Copyright: © 2025 |Pages: 442
DOI: 10.4018/979-8-3693-8472-5
ISBN13: 9798369384725|ISBN13 Softcover: 9798369384732|EISBN13: 9798369384749
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Description & Coverage
Description:

The interplay between big data and Artificial Intelligence has redefined how organizations process, analyze, and utilize information in the modern era. By leveraging AI, big data has transitioned from a static resource to a dynamic force capable of driving innovation, creating strategic insights, and transforming industries. This evolution underscores the importance of building trust in both human and technological systems to manage data responsibly and effectively. As the reliance on data-driven decision-making grows, understanding this relationship is vital for advancing societal progress and fostering sustainable development.

AI and the Revival of Big Data offers a nuanced understanding of the evolution of big data and its enduring significance in the digital age. Additionally, the discussion of AI's role in revitalizing big data will inspire new avenues of research and collaboration across disciplines. Covering topics such as load distribution, financial malfeasance, image analysis, this book is an excellent resource for data scientists, business leaders, practitioners, policymakers, and industry professionals, professionals, researchers, scholars, academicians, and more.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Artificial Intelligence (AI)
  • Automated Disease Detection
  • Big Data
  • Big Data Ecosystems
  • Data Extraction
  • Data Infrastructure
  • Data Mining
  • Financial Malfeasance
  • Fiscal Ramification
  • Image Analysis
  • Load Distribution
  • Machine Learning (ML) Algorithms
  • Meta-Heuristics
  • Pharmaceutical Sciences
  • Process Optimization
  • Service Organizations
  • Statistical Tools
  • Swarm Intelligence
  • Text Preprocessing
  • Veterinary Medical Healthcare Systems
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Editor/Author Biographies
Madan Mohan Tito Ayyalasomayajula , a Doctorate holder in Computer Science from Aspen University, Arizona, USA, is a seasoned expert in the realms of AI, ML, Big Data, and emerging technologies. Currently serving as a Senior Technology Architect at Infosys in the United States, Dr. Ayyalasomayajula leverages over two decades of industry experience to drive innovation and strategic advancements in technology. Through his writings, he aims to empower readers with deep insights and practical knowledge, fostering the next generation of innovators and leaders in the technology sector. As a research scholar and industry expert, Dr. Ayyalasomayajula has made significant academic contributions through his published articles, including groundbreaking work on AI-driven decision support systems, explainable artificial intelligence (XAI) for emotion detection, and advanced strategies for privacy-preserving machine learning. His extensive research encompasses analyzing language patterns for depression detection on social media, innovative fraud detection techniques using Red Deer Optimization and LSTM Attention Mechanism, and optimizing hyperparameter strategies in cloud-based machine learning models. Additionally, Dr. Ayyalasomayajula has contributed to optimizing photometric light curve analysis for cataclysmic variables and enhancing federated learning evaluation with instance-level insights in image classification models. In addition to his published work, several more scholarly articles are underway, further cementing his role as a thought leader in the field. Dr. Ayyalasomayajula has also served as a judge at the Regeneron International Science and Engineering Fair (ISEF), the world's largest pre-college science competition, reflecting his commitment to fostering the next generation of innovators. In “The Rise and Fall of Big Data,” Dr. Ayyalasomayajula aims to impart his extensive knowledge and insights, empowering readers to navigate and innovate within the complex landscape of big data.
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