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Developing a Path to Data Dominance [electronic resource] : Strategies for Digital Data-Centric Enterprises / by Arthur Langer, Arka Mukherjee.

By: Contributor(s): Material type: TextTextLanguage: English Series: Publication details: Cham : Springer International Publishing : Imprint: Springer, 2023.Edition: 1st ed. 2023Description: XVII, 283 p. 158 illus. online resourceISBN:
  • 9783031264016
Subject(s): DDC classification:
  • 658.05 23
Online resources:
Contents:
An Introduction to Data Dominance -- The Digital Data-Centric Enterprise: Case Studies -- The Product Strategy -- The Data Strategy -- Data: Organizing the Data Ecosystem -- Process: Building Digital Data-Centric Products -- Culture: Friction in Scaling the Product Portfolio -- Alignment: Data Strategy Management and Leadership -- Effects of Wireless Communications and IoT on Data Aggregation -- Blockchain Data Architecture -- Transforming Legacy Systems to Data Platforms -- Conclusion.
Summary: 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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Item type Current library Call number Materials specified Status Date due Barcode Item holds
E-Books E-Books National Library of India Online Resource 658.05 (Browse shelf(Opens below)) Available EBK000042103ENG
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An Introduction to Data Dominance -- The Digital Data-Centric Enterprise: Case Studies -- The Product Strategy -- The Data Strategy -- Data: Organizing the Data Ecosystem -- Process: Building Digital Data-Centric Products -- Culture: Friction in Scaling the Product Portfolio -- Alignment: Data Strategy Management and Leadership -- Effects of Wireless Communications and IoT on Data Aggregation -- Blockchain Data Architecture -- Transforming Legacy Systems to Data Platforms -- Conclusion.

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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