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Modern Data Strategy

  • Mike Fleckenstein
  • Lorraine Fellows

Table of contents

  1. Front Matter
    Pages i-xix
  2. Data Strategy Considerations

    1. Front Matter
      Pages 1-1
    2. Mike Fleckenstein, Lorraine Fellows
      Pages 3-5
    3. Mike Fleckenstein, Lorraine Fellows
      Pages 7-10
    4. Mike Fleckenstein, Lorraine Fellows
      Pages 11-14
    5. Mike Fleckenstein, Lorraine Fellows
      Pages 15-22
  3. Data Strategy

    1. Front Matter
      Pages 23-23
    2. Mike Fleckenstein, Lorraine Fellows
      Pages 25-34
    3. Mike Fleckenstein, Lorraine Fellows
      Pages 35-54
    4. Mike Fleckenstein, Lorraine Fellows
      Pages 55-59
  4. Data Management Domains

    1. Front Matter
      Pages 61-61
    2. Mike Fleckenstein, Lorraine Fellows
      Pages 63-76
    3. Mike Fleckenstein, Lorraine Fellows
      Pages 77-91
    4. Mike Fleckenstein, Lorraine Fellows
      Pages 93-99
    5. Mike Fleckenstein, Lorraine Fellows
      Pages 101-119
    6. Mike Fleckenstein, Lorraine Fellows
      Pages 121-131
    7. Mike Fleckenstein, Lorraine Fellows
      Pages 133-142
    8. Mike Fleckenstein, Lorraine Fellows
      Pages 143-163
    9. Mike Fleckenstein, Lorraine Fellows
      Pages 165-177
    10. Mike Fleckenstein, Lorraine Fellows
      Pages 179-193
    11. Mike Fleckenstein, Lorraine Fellows
      Pages 195-207
  5. Back Matter
    Pages 209-263

About this book

Introduction

This book contains practical steps business users can take to implement data management in a number of ways, including data governance, data architecture, master data management, business intelligence, and others. It defines data strategy, and covers chapters that illustrate how to align a data strategy with the business strategy, a discussion on valuing data as an asset, the evolution of data management, and who should oversee a data strategy. This provides the user with a good understanding of what a data strategy is and its limits.

Critical to a data strategy is the incorporation of one or more data management domains. Chapters on key data management domains—data governance, data architecture, master data management and analytics, offer the user a practical approach to data management execution within a data strategy. The intent is to enable the user to identify how execution on one or more data management domains can help solve business issues.

This book is intended for business users who work with data, who need to manage one or more aspects of the organization’s data, and who want to foster an integrated approach for how enterprise data is managed. This book is also an excellent reference for students studying computer science and business management or simply for someone who has been tasked with starting or improving existing data management.

Keywords

Data strategy Data management Data governance Data architecture Data analytics Data privacy Data security Metadata Data Information management Information Strategy Data asset

Authors and affiliations

  • Mike Fleckenstein
    • 1
  • Lorraine Fellows
    • 2
  1. 1.MITREMcLeanUSA
  2. 2.MITREMcLeanUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-68993-7
  • Copyright Information Springer International Publishing AG 2018
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-68992-0
  • Online ISBN 978-3-319-68993-7
  • Buy this book on publisher's site