Data Fabric And Data Mesh Approaches With Ai
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Data Fabric and Data Mesh Approaches with AI
Understand modern data fabric and data mesh concepts using AI-based self-service data discovery and delivery capabilities, a range of intelligent data integration styles, and automated unified data governance—all designed to deliver "data as a product" within hybrid cloud landscapes. This book teaches you how to successfully deploy state-of-the-art data mesh solutions and gain a comprehensive overview on how a data fabric architecture uses artificial intelligence (AI) and machine learning (ML) for automated metadata management and self-service data discovery and consumption. You will learn how data fabric and data mesh relate to other concepts such as data DataOps, MLOps, AIDevOps, and more. Many examples are included to demonstrate how to modernize the consumption of data to enable a shopping-for-data (data as a product) experience. By the end of this book, you will understand the data fabric concept and architecture as it relates to themes such as automated unified data governance and compliance, enterprise information architecture, AI and hybrid cloud landscapes, and intelligent cataloging and metadata management. What You Will Learn Discover best practices and methods to successfully implement a data fabric architecture and data mesh solution Understand key data fabric capabilities, e.g., self-service data discovery, intelligent data integration techniques, intelligent cataloging and metadata management, and trustworthy AI Recognize the importance of data fabric to accelerate digital transformation and democratize data access Dive into important data fabric topics, addressing current data fabric challenges Conceive data fabric and data mesh concepts holistically within an enterprise context Become acquainted with the business benefits of data fabric and data mesh Who This Book Is For Anyone who is interested in deploying modern data fabric architectures and data mesh solutions within an enterprise, including IT and business leaders, data governance and data office professionals, data stewards and engineers, data scientists, and information and data architects. Readers should have a basic understanding of enterprise information architecture.
Leveraging Advanced Technologies: Business Model Innovation and the Future
Author: Bahaaeddin Alareeni
language: en
Publisher: Springer Nature
Release Date: 2025-07-30
This book examines how next-generation tools such as artificial intelligence, blockchain, and the Internet of Things are transforming not only the way companies operate, but also how they create value, define strategy, and drive growth. As emerging technologies reshape the business landscape, innovation has become a necessity rather than a choice. It offers an in-depth exploration of the evolving business model innovation landscape, combining diverse methodologies and real-world industry cases to illustrate the powerful intersection of technology and strategic transformation. Through practical insights, evidence-based analysis, and compelling case studies, this book equips decision-makers to adapt, innovate, and lead in a rapidly evolving digital environment. What You’ll Discover: !-- [if !supportLists]--· !--[endif]--The role of AI, blockchain, and IoT in reinventing business models !-- [if !supportLists]--· !--[endif]--Frameworks and strategies for leveraging disruptive technologies !-- [if !supportLists]--· !--[endif]--Policy and managerial insights to guide innovation in practice !-- [if !supportLists]--· !--[endif]--Case studies illustrating sector-specific applications and outcomes !-- [if !supportLists]--· !--[endif]--Multidisciplinary research perspectives supporting innovation management Ideal for scholars, professionals, executives, and policymakers, this book delivers the tools, clarity, and inspiration needed to navigate the future of business with confidence and creativity.
Database and Expert Systems Applications
The two-volume set LNCS 14910 and 14911 constitutes the proceedings of the 35th International Conference on Database and Expert Systems Applications, DEXA 2024, which took place in Naples, Italy, in August 2024. The 27 full and 20 short papers included in the proceedings set were carefully reviewed and selected from 102 submissions. They were organized in topical sections as follows: Part I: Financial and economic data analysis; graph theory and network analysis; database management and query optimization; machine learning and large language models; recommender systems and personalization; Part II: Blockchain and supply management; data mining and knowledge discovery; spatiotemporal data and mobility analysis; computer vision and image processing; data security and privacy; database indexing and query processing; specialized applications and case studies.