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Developing a Path to Data Dominance

Über Developing a Path to Data Dominance

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.

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  • Sprache:
  • Englisch
  • ISBN:
  • 9783031264009
  • Einband:
  • Gebundene Ausgabe
  • Seitenzahl:
  • 304
  • Veröffentlicht:
  • 26 April 2023
  • Ausgabe:
  • 23001
  • Abmessungen:
  • 160x22x241 mm.
  • Gewicht:
  • 623 g.
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Beschreibung von Developing a Path to Data Dominance

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.

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