This book explores different aspects of and provides concrete suggestions to meet the three main challenges for becoming a “Digital Enterprise”: the transition to the digital age, the emergence of service ecosystems, and the growing role of data as a key underlying resource. As a result of these intertwined and mutually amplifying trends, today’s enterprises are confronted with several challenges that profoundly impact their design, from the definitions of products and services offered to their clients via the business processes that deliver these products and services to the underlying IT infrastructure.The contributions which are written by leading enterprise architecture researchers and managers of large corporations cover four key aspects which form each one part of the book: Part I presents experiences how different enterprises currently already need to embrace and exploit new challenges like blockchain, customer-centric services, or value co-creation networks. Part II looks at the need for a new design logic, i.e. the need for new ways of thinking regarding the design of enterprises. Part III is concerned with the coordination needed among different stakeholders of the ensuing continuous transformations. Part IV eventually reflects on the ongoing consequences for enterprise modeling as used to capture both the current affairs of an enterprise, as well as design/study its possible future affairs. The target audience of this book are both master and PhD level students who want to gain insights into key aspects of the challenges confronting digital enterprises, as well as enterprise architects and information managers working in enterprises that are on their way to become digital.

Data is an increasingly important asset for many organizations. This book shows how to model data in a way that allows to exploit this asset effectively and in every respect. To this end, it combines and exploits scientific (semiotics, relational model, etc.) and pragmatic theories (most prominently: the DAMA wheel) and provides a coherent overview from a business and an IT/ICT perspective. After a brief introduction, the remaining book consists of three parts. In Part I “Data”, the focus is on understanding data. It includes theories in semiotics, the relational model, and normalization, as well as related theories around understanding data/designing sound data structures. This part is complemented by an extensive chapter on how to design effective data structures and a smaller one on the topic of create versus use context. Part II “Data Management” then focuses on managing data as an asset. This part is based on the DMBOK and each of the functional areas is discussed in a separate chapter. Part III “Parting Thoughts” presents conclusions which are based on a synthesis of Part I and Part II, leading up to a summary of the main contributions of this book as well as a critical reflection on these results. This book is written for a rather broad audience, ranging from professionals to students, both from business, computer science, and information management. The writing style is adjusted specifically for these groups. At the end of each chapter reflection questions are included that distinguish between questions for practitioners and for students and help both audiences to benefit from the book and check their comprehension.