Building an Intelligent Enterprise with SAP Business AI

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Building an Intelligent Enterprise with SAP Business AI

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Lieferung am Fr. 20.03.2026
 
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Produktdetails

Generative AI (Gen AI) represents a transformational technological shift by enabling the rapid creation of text, images, audio, and video through learning from vast amounts of human-generated data. Unlike traditional programming that relies on explicit instructions, Gen AI leverages machine learning to recognize patterns and generate content autonomously. SAP has embraced this revolution with its SAP BTP Generative AI Hub—a comprehensive platform designed to safely integrate generative AI and large language models into enterprise applications, with seamless support across its product suite including S/4 HANA, CRM, and HXM. This book provides a complete roadmap for understanding and applying these groundbreaking technologies. It begins by exploring the origins and core concepts of AI, deep learning, and transformer architectures, before delving into SAP’s AI Core and Generative AI Hub offerings. Through detailed, step-by-step examples, readers will learn to build enterprise use cases and discover the potential of Agentic AI for addressing real-world business challenges, making this a must-read for professionals seeking to drive innovation and efficiency in their organizations. You Will: Gain a solid understanding of artificial intelligence, deep learning, and transformer architectures, and how these concepts power generative AI. Dive into SAP’s innovative AI offerings, exploring how the SAP BTP Generative AI Hub integrates generative AI and large language models safely into enterprise applications. Understand how SAP’s generative AI capabilities are embedded across its product suite including S/4 HANA, CRM, and HXM. This book is for: Enterprise IT Professionals and Developers, Solution Architects.

Infotabelle

Produktspezifikationen

Autor
Avijit Dhar
Format
gebundene Ausgabe
Sprachfassung
Englisch
Seiten
226
Erscheinungsdatum
2026-02-14
Verlag
APRESS

Produktkennung

Artikelnummer m0000SI5IY
EAN 9798868819797
GTIN 09798868819797

Zusatzinfo und Downloads

Generative AI (Gen AI) represents a transformational technological shift by enabling the rapid creation of text, images, audio, and video through learning from vast amounts of human-generated data. Unlike traditional programming that relies on explicit instructions, Gen AI leverages machine learning to recognize patterns and generate content autonomously. SAP has embraced this revolution with its SAP BTP Generative AI Hub—a comprehensive platform designed to safely integrate generative AI and large language models into enterprise applications, with seamless support across its product suite including S/4 HANA, CRM, and HXM. This book provides a complete roadmap for understanding and applying these groundbreaking technologies. It begins by exploring the origins and core concepts of AI, deep learning, and transformer architectures, before delving into SAP’s AI Core and Generative AI Hub offerings. Through detailed, step-by-step examples, readers will learn to build enterprise use cases and discover the potential of Agentic AI for addressing real-world business challenges, making this a must-read for professionals seeking to drive innovation and efficiency in their organizations. You Will: Gain a solid understanding of artificial intelligence, deep learning, and transformer architectures, and how these concepts power generative AI. Dive into SAP’s innovative AI offerings, exploring how the SAP BTP Generative AI Hub integrates generative AI and large language models safely into enterprise applications. Understand how SAP’s generative AI capabilities are embedded across its product suite including S/4 HANA, CRM, and HXM. This book is for: Enterprise IT Professionals and Developers, Solution Architects.

Produktspezifikationen

Autor
Avijit Dhar
Format
gebundene Ausgabe
Sprachfassung
Englisch
Seiten
226
Erscheinungsdatum
2026-02-14
Verlag
APRESS

Produktkennung

Artikelnummer m0000SI5IY
EAN 9798868819797
GTIN 09798868819797

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