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Digital business managementtransforming to a data-driven organization using AI /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Digital business managementby Swen Schneider, Lutz Anderie.
其他題名:	transforming to a data-driven organization using AI /
作者:	Schneider, Swen.
其他作者:	Anderie, Lutz.
出版者:	Cham :Springer Nature Switzerland :2025.
面頁冊數:	xiv, 250 p. :ill. (chiefly color), digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Artificial intelligenceBusiness applications.
電子資源:	https://doi.org/10.1007/978-3-031-83177-5
ISBN:	9783031831775$q(electronic bk.)

Digital business managementtransforming to a data-driven organization using AI /
Schneider, Swen.

Digital business managementtransforming to a data-driven organization using AI /[electronic resource] :by Swen Schneider, Lutz Anderie. - Cham :Springer Nature Switzerland :2025. - xiv, 250 p. :ill. (chiefly color), digital ;24 cm.

Effective AI Prompting -- From E Business to Digital Business -- Digital Business Strategies -- Digital Infrastructure -- ECommerce Shops and Web Presence -- Digital Marketing and Advertising -- Social and Mobile Commerce with Location Based Services -- Content Management Online Media Ethics and Fake News -- Digital Business to Business Integration -- Digital Business Analysis and Digital Transformation -- Industry and Business Cases.

This book is a concise guide on using generative artificial intelligence to drive digital business management and transformation. It is divided into three parts. The first part, "How to Work with AI and Generate Success in Business," outlines the core concepts of artificial intelligence and prompt engineering and explores how these can be leveraged in a business environment. It places special emphasis on the AI Prompt Schema (AIPS) for structured prompting. The second part, "From Digital Business to a Data-Driven Organization," focuses on the essential knowledge and advanced techniques for successful Digital Business Management. It covers relevant topics, including digital business strategies, digital infrastructure, e-commerce, digital marketing and advertising, content management, the metaverse, and more. The third part, "Industry and Business Case Prompt Engineering," demonstrates how the concepts, knowledge, and techniques can be applied in real-world scenarios. This includes technology companies like Waymo, Tesla, Google/Alphabet, Meta/Facebook, Microsoft/LinkedIn, OpenAI/ChatGPT, and Google/Gemini, as well as e-commerce giants like Amazon, Alibaba, Temu, Shein, and Otto, and entertainment platforms like Netflix, Sony PlayStation, and Spotify. Drawing from many years of experience in business practice and university teaching, the authors include interactive elements such as video tutorials to support learning and the practical application of the concepts outlined. This book will be valuable to anyone interested in expanding their knowledge of digital business strategies, particularly practitioners, students, entrepreneurs, and executives.

ISBN: 9783031831775$q(electronic bk.)

Standard No.: 10.1007/978-3-031-83177-5doiSubjects--Topical Terms:

996997
Artificial intelligence
--Business applications.

LC Class. No.: HF5548.2

Dewey Class. No.: 658.0563

Digital business managementtransforming to a data-driven organization using AI /
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520 $a This book is a concise guide on using generative artificial intelligence to drive digital business management and transformation. It is divided into three parts. The first part, "How to Work with AI and Generate Success in Business," outlines the core concepts of artificial intelligence and prompt engineering and explores how these can be leveraged in a business environment. It places special emphasis on the AI Prompt Schema (AIPS) for structured prompting. The second part, "From Digital Business to a Data-Driven Organization," focuses on the essential knowledge and advanced techniques for successful Digital Business Management. It covers relevant topics, including digital business strategies, digital infrastructure, e-commerce, digital marketing and advertising, content management, the metaverse, and more. The third part, "Industry and Business Case Prompt Engineering," demonstrates how the concepts, knowledge, and techniques can be applied in real-world scenarios. This includes technology companies like Waymo, Tesla, Google/Alphabet, Meta/Facebook, Microsoft/LinkedIn, OpenAI/ChatGPT, and Google/Gemini, as well as e-commerce giants like Amazon, Alibaba, Temu, Shein, and Otto, and entertainment platforms like Netflix, Sony PlayStation, and Spotify. Drawing from many years of experience in business practice and university teaching, the authors include interactive elements such as video tutorials to support learning and the practical application of the concepts outlined. This book will be valuable to anyone interested in expanding their knowledge of digital business strategies, particularly practitioners, students, entrepreneurs, and executives.
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