Hardcover. Distributed Data Ecosystems in the Age of AI: Technologies, Challenges, and Innovations explores how artificial intelligence is transforming the design, management, and governance of modern data ecosystems. Covering distributed databases, cloud and edge computing, real-time analytics, intelligent data pipelines, MLOps, security, governance, and globally distributed architectures, the book provides a comprehensive guide to the technologies driving AI-powered enterprises. It also examines emerging innovations such as data mesh, data fabric, federated learning, autonomous data platforms, digital twins, and quantum computing while addressing critical challenges in scalability, privacy, sustainability, and regulatory compliance. Combining foundational concepts with practical insights and future research directions, this book is an essential resource for researchers, graduate students, data architects, AI professionals, and technology leaders seeking to build resilient, intelligent, and scalable data ecosystems for the next generation of digital transformation This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

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Bibliographic Details

Title: Distributed Data Ecosystems in the Age of AI Technologies, Challenges, and Innovations (Hardcover)
Publisher: Notion Press
Publication Date: 2026
Language: English
ISBN 13: 9798906069153
Binding: Hardcover
Condition: new

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Distributed Data Ecosystems in the Age of AI: Technologies, Challenges, and Innovations explores how artificial intelligence is transforming the design, management, and governance of modern data ecosystems. Covering distributed databases, cloud and edge computing, real-time analytics, intelligent data pipelines, MLOps, security, governance, and globally distributed architectures, the book provides a comprehensive guide to the technologies driving AI-powered enterprises. It also examines emerging innovations such as data mesh, data fabric, federated learning, autonomous data platforms, digital twins, and quantum computing while addressing critical challenges in scalability, privacy, sustainability, and regulatory compliance. Combining foundational concepts with practical insights and future research directions, this book is an essential resource for researchers, graduate students, data architects, AI professionals, and technology leaders seeking to build resilient, intelligent, and scalable data ecosystems for the next generation of digital transformation.

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