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Indigo AI-Driven Data Supply Chain: From Data Chaos to Intelligent Value Chains | Erin Mills Town Centre
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This book explores the transformation of data management through AI-driven solutions, emphasizing the critical role of an intelligent and adaptive data supply chain. It covers essential topics such as AI-powered data discovery, automated data pipelines, data governance, and real-time analytics. The book also examines practical applications, including cost optimization in cloud environments, security and privacy considerations, and real-world case studies. Key features:
Defines a new data foundation based on the concept of a data supply chain and bridges the gap between theory and implementation through AI-driven approaches.
Promotes the development of a comprehensive Data and AI ecosystem.
Presents a focused blend of theoretical concepts and practical applications, supported by hands-on examples and step-by-step frameworks.
Focuses on AI-powered data lifecycle management, with automation and visibility at its core.
Applies the shift-left principle by embedding Generative AI into data foundation practices, proposing and implementing innovative and improved methodologies.
This book is intended for data professionals, AI practitioners, IT managers, business analysts, senior executives, product managers, and academics specializing in data science and supply chain management.
This book explores the transformation of data management through AI-driven solutions, emphasizing the critical role of an intelligent and adaptive data supply chain. It covers essential topics such as AI-powered data discovery, automated data pipelines, data governance, and real-time analytics. The book also examines practical applications, including cost optimization in cloud environments, security and privacy considerations, and real-world case studies. Key features:
Defines a new data foundation based on the concept of a data supply chain and bridges the gap between theory and implementation through AI-driven approaches.
Promotes the development of a comprehensive Data and AI ecosystem.
Presents a focused blend of theoretical concepts and practical applications, supported by hands-on examples and step-by-step frameworks.
Focuses on AI-powered data lifecycle management, with automation and visibility at its core.
Applies the shift-left principle by embedding Generative AI into data foundation practices, proposing and implementing innovative and improved methodologies.
This book is intended for data professionals, AI practitioners, IT managers, business analysts, senior executives, product managers, and academics specializing in data science and supply chain management.
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