Most existing companies struggle currently because they lack the tools and strategies to move product departments into independent platforms that can be retrofitted to form dynamic new products based on consumer demands. This book provides managers and professionals with the necessary approaches for designing software and hardware architectures to support data platform organizations. Specifically, it demonstrates how to automate the decomposition of existing platforms into smaller parts that can be reused to form new variations. This task requires significant analysis and design methodologies and procedures to create an infrastructure based on data as opposed to products. These new knowledge bases allow data-centric professionals to pursue actions that can better predict and respond to the unexpected.
Featuring case examples from companies such as Lego, FedEx, General Electric (GE), Pfizer, P&G and more, this book is appropriate for C-level executives engaged in the digital transformation of their firms; entrepreneurs of digital platform companies; and senior software engineers that need to design Internet of Things (IoT) devices and integrate them with block chain and multi-cloud architectures. In addition, this book is also useful for graduate-level coursework in data science.
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Arthur Langer is Associate Vice Provost and the Director of the Center forTechnology Management and Digital Leadership at Northeastern Univeristy. He is Professor of Professional Practice in Northeastern’s Department of Entrepreneurship and Innovation at the D’Amore-McKim School of Business (Boston, MA, USA). He is also Honorary Professor of Professional Practice in the Department of Organization and Leadership at Columbia University’s Graduate School of Education (Teachers College). Dr. Langer has numerous published articles and papers relating to service learning for underserved populations, IT organizational integration, mentoring, and staff development. He consults with corporations and universities worldwide on information technology, staff development, management transformation, and curriculum development. He is also the Chairman and Founder of Workforce Opportunity Services (www.wforce.org), a nonprofit social venture that provides scholarships and careers to underserved populations around the world.
Arka Mukherjee is CEO of Global IDs Inc., a data management software company based in New York City. The company provides software and services for solving complex data analysis and integration problems in global companies. Dr. Mukherjee was formerly a principal in IBM, leading the ERP data warehousing area, and brings leadership expertise from consulting firms Accenture and KPMG.
This book provides managers and professionals with the necessary approaches for designing software and hardware architectures that support data platform organizations, specifically how to achieve hyper-automation that requires the decomposition of existing platforms to smaller parts that can reused to form new variations. This task requires significant analysis and design methodologies and procedures to create an infrastructure based on data as opposed to products. These new knowledge bases will allow those with data-centric minds to pursue actions that can better predict and respond to the unexpected. Indeed, most existing companies are struggling because of the lack of best practices to move product departments to independent platforms that can be retrofitted to form new products dynamically based on consumer demands.
Featuring exercises at the end of each chapter and online ancillary materials, this book is appropriate for C-level executives engaged in the digital transformation of their firms; entrepreneurs that are planning on forming digital platform companies; and senior software engineers that need to understand how to design Internet of Things (IoT) devices and integrate them with block chain and multi-cloud architectures. In addition, this book is also useful for graduate level professional university coursework in data science.
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Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Most existing companies struggle currently because they lack the tools and strategies to move product departments into independent platforms that can be retrofitted to form dynamic new products based on consumer demands. This book provides managers and professionals with the necessary approaches for designing software and hardware architectures to support data platform organizations. Specifically, it demonstrates how to automate the decomposition of existing platforms into smaller parts that can be reused to form new variations. This task requires significant analysis and design methodologies and procedures to create an infrastructure based on data as opposed to products. These new knowledge bases allow data-centric professionals to pursue actions that can better predict and respond to the unexpected.Featuring case examples from companies such as Lego, FedEx, General Electric (GE), Pfizer, P&G and more, this book isappropriate for C-level executives engagedin the digital transformation of their firms; entrepreneurs of digital platform companies; and senior software engineers that need to design Internet of Things (IoT) devices and integrate them with block chain and multi-cloud architectures. In addition, this book is also useful for graduate-level coursework in data science. Bestandsnummer des Verkäufers 9783031264009
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Buch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Most existing companies struggle currently because they lack the tools and strategies to move product departments into independent platforms that can be retrofitted to form dynamic new products based on consumer demands. This book provides managers and professionals with the necessary approaches for designing software and hardware architectures to support data platform organizations. Specifically, it demonstrates how to automate the decomposition of existing platforms into smaller parts that can be reused to form new variations. This task requires significant analysis and design methodologies and procedures to create an infrastructure based on data as opposed to products. These new knowledge bases allow data-centric professionals to pursue actions that can better predict and respond to the unexpected.Featuring case examples from companies such as Lego, FedEx, General Electric (GE), Pfizer, P&G and more, this book isappropriate for C-level executives engaged in the digital transformation of their firms; entrepreneurs of digital platform companies; and senior software engineers that need to design Internet of Things (IoT) devices and integrate them with block chain and multi-cloud architectures. In addition, this book is also useful for graduate-level coursework in data science. 304 pp. Englisch. Bestandsnummer des Verkäufers 9783031264009
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Buch. Zustand: Neu. Neuware -Most existing companies struggle currently because they lack the tools and strategies to move product departments into independent platforms that can be retrofitted to form dynamic new products based on consumer demands. This book provides managers and professionals with the necessary approaches for designing software and hardware architectures to support data platform organizations. Specifically, it demonstrates how to automate the decomposition of existing platforms into smaller parts that can be reused to form new variations. This task requires significant analysis and design methodologies and procedures to create an infrastructure based on data as opposed to products. These new knowledge bases allow data-centric professionals to pursue actions that can better predict and respond to the unexpected.Featuring case examples from companies such as Lego, FedEx, General Electric (GE), Pfizer, P&G and more, this book is appropriate for C-level executives engagedin the digital transformation of their firms; entrepreneurs of digital platform companies; and senior software engineers that need to design Internet of Things (IoT) devices and integrate them with block chain and multi-cloud architectures. In addition, this book is also useful for graduate-level coursework in data science.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 304 pp. Englisch. Bestandsnummer des Verkäufers 9783031264009
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