Generative Ai Powered Data Architectures (16 results)

Hardback. Condition: New.

Hardback. Condition: New.

hardcover. Condition: Very Good.

Condition: New.

Condition: New.

Condition: New.

PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Paperback. Condition: new. Paperback. Generative AI rapidly transforms data architectures, reshaping how organizations govern, manage, and analyze data. As organizations face growing demands for real-time insights, scalability, and compliance, traditional data systems struggle to keep pace. Generative AI-powered data architectures offer a shift, enabling intelligent data governance, automated management, and analytics that evolve autonomously. These architectures streamline complex data operations while enhancing decision-making through proactive, AI-driven insights. Further exploration of these infrastructures may reveal more adaptive, explainable, and capable data to support new innovations in enterprise analytics. Generative AI-Powered Data Architectures: From Governance to Autonomous Analytics explores how generative AI can be effectively integrated with modern data architectures to build scalable, secure, and intelligent systems. It addresses the entire data lifecycle from governance and ingestion to transformation, storage, and autonomous analytics empowering organizations to leverage AI-driven processes. This book covers topics such as data analytics, learning systems, and ethics and law, and is a useful resource for engineers, educators, business owners, academicians, researchers, and data scientists. "This book aims to bridge the gap between data architecture and AI advancements by exploring how generative technologies can influence data modeling, orchestration, privacy, and ethics"-- Provided by publisher. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

HRD. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

HRD. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Paperback. Condition: new. Paperback. Generative AI rapidly transforms data architectures, reshaping how organizations govern, manage, and analyze data. As organizations face growing demands for real-time insights, scalability, and compliance, traditional data systems struggle to keep pace. Generative AI-powered data architectures offer a shift, enabling intelligent data governance, automated management, and analytics that evolve autonomously. These architectures streamline complex data operations while enhancing decision-making through proactive, AI-driven insights. Further exploration of these infrastructures may reveal more adaptive, explainable, and capable data to support new innovations in enterprise analytics. Generative AI-Powered Data Architectures: From Governance to Autonomous Analytics explores how generative AI can be effectively integrated with modern data architectures to build scalable, secure, and intelligent systems. It addresses the entire data lifecycle from governance and ingestion to transformation, storage, and autonomous analytics empowering organizations to leverage AI-driven processes. This book covers topics such as data analytics, learning systems, and ethics and law, and is a useful resource for engineers, educators, business owners, academicians, researchers, and data scientists. "This book aims to bridge the gap between data architecture and AI advancements by exploring how generative technologies can influence data modeling, orchestration, privacy, and ethics"-- Provided by publisher. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Hardcover. Condition: new. Hardcover. Generative AI rapidly transforms data architectures, reshaping how organizations govern, manage, and analyze data. As organizations face growing demands for real-time insights, scalability, and compliance, traditional data systems struggle to keep pace. Generative AI-powered data architectures offer a shift, enabling intelligent data governance, automated management, and analytics that evolve autonomously. These architectures streamline complex data operations while enhancing decision-making through proactive, AI-driven insights. Further exploration of these infrastructures may reveal more adaptive, explainable, and capable data to support new innovations in enterprise analytics. Generative AI-Powered Data Architectures: From Governance to Autonomous Analytics explores how generative AI can be effectively integrated with modern data architectures to build scalable, secure, and intelligent systems. It addresses the entire data lifecycle from governance and ingestion to transformation, storage, and autonomous analytics empowering organizations to leverage AI-driven processes. This book covers topics such as data analytics, learning systems, and ethics and law, and is a useful resource for engineers, educators, business owners, academicians, researchers, and data scientists. "This book aims to bridge the gap between data architecture and AI advancements by exploring how generative technologies can influence data modeling, orchestration, privacy, and ethics"-- Provided by publisher. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Hardcover. Condition: new. Hardcover. Generative AI rapidly transforms data architectures, reshaping how organizations govern, manage, and analyze data. As organizations face growing demands for real-time insights, scalability, and compliance, traditional data systems struggle to keep pace. Generative AI-powered data architectures offer a shift, enabling intelligent data governance, automated management, and analytics that evolve autonomously. These architectures streamline complex data operations while enhancing decision-making through proactive, AI-driven insights. Further exploration of these infrastructures may reveal more adaptive, explainable, and capable data to support new innovations in enterprise analytics. Generative AI-Powered Data Architectures: From Governance to Autonomous Analytics explores how generative AI can be effectively integrated with modern data architectures to build scalable, secure, and intelligent systems. It addresses the entire data lifecycle from governance and ingestion to transformation, storage, and autonomous analytics empowering organizations to leverage AI-driven processes. This book covers topics such as data analytics, learning systems, and ethics and law, and is a useful resource for engineers, educators, business owners, academicians, researchers, and data scientists. "This book aims to bridge the gap between data architecture and AI advancements by exploring how generative technologies can influence data modeling, orchestration, privacy, and ethics"-- Provided by publisher. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Paperback. Condition: new. Paperback. Generative AI rapidly transforms data architectures, reshaping how organizations govern, manage, and analyze data. As organizations face growing demands for real-time insights, scalability, and compliance, traditional data systems struggle to keep pace. Generative AI-powered data architectures offer a shift, enabling intelligent data governance, automated management, and analytics that evolve autonomously. These architectures streamline complex data operations while enhancing decision-making through proactive, AI-driven insights. Further exploration of these infrastructures may reveal more adaptive, explainable, and capable data to support new innovations in enterprise analytics. Generative AI-Powered Data Architectures: From Governance to Autonomous Analytics explores how generative AI can be effectively integrated with modern data architectures to build scalable, secure, and intelligent systems. It addresses the entire data lifecycle from governance and ingestion to transformation, storage, and autonomous analytics empowering organizations to leverage AI-driven processes. This book covers topics such as data analytics, learning systems, and ethics and law, and is a useful resource for engineers, educators, business owners, academicians, researchers, and data scientists. "This book aims to bridge the gap between data architecture and AI advancements by exploring how generative technologies can influence data modeling, orchestration, privacy, and ethics"-- Provided by publisher. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Hardcover. Condition: new. Hardcover. Generative AI rapidly transforms data architectures, reshaping how organizations govern, manage, and analyze data. As organizations face growing demands for real-time insights, scalability, and compliance, traditional data systems struggle to keep pace. Generative AI-powered data architectures offer a shift, enabling intelligent data governance, automated management, and analytics that evolve autonomously. These architectures streamline complex data operations while enhancing decision-making through proactive, AI-driven insights. Further exploration of these infrastructures may reveal more adaptive, explainable, and capable data to support new innovations in enterprise analytics. Generative AI-Powered Data Architectures: From Governance to Autonomous Analytics explores how generative AI can be effectively integrated with modern data architectures to build scalable, secure, and intelligent systems. It addresses the entire data lifecycle from governance and ingestion to transformation, storage, and autonomous analytics empowering organizations to leverage AI-driven processes. This book covers topics such as data analytics, learning systems, and ethics and law, and is a useful resource for engineers, educators, business owners, academicians, researchers, and data scientists. "This book aims to bridge the gap between data architecture and AI advancements by exploring how generative technologies can influence data modeling, orchestration, privacy, and ethics"-- Provided by publisher. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.