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Data Resource Simplexity: How Organizations Choose Data Resource Success or Failure

Book Description

Do you fully understand all the data in your organization's data resource? Can you readily find and easily access the data you need to support your business activities? If you find multiple sets of the same data, can you readily determine which is the most current and correct? No? Then consider this book essential reading. It will help you develop a high quality data resource that supports business needs.

Data Resource Simplexity explains how a data resource goes disparate, how to stop that trend toward disparity, and how to develop a high quality, comparate data resource. It explains how to stop the costly business impacts of disparate data. It explains both the architectural and the cultural aspects of developing a comparate data resource. It explains how to manage data as a critical resource equivalent to the other critical resources of an organization - finances, human resource, and real property.

Drawing from his nearly five decades of data management experience, plus his leveraging of theories, concepts, principles, and techniques from disciplines as diverse as human dynamics, mathematics, physics, agriculture, chemistry, and biology, Michael Brackett shows how you can transform your organization's data resource into a trusted invaluable companion for both business and data management professionals.

Chapter 1 reviews the trend toward rampant data resource disparity that exists in most public and private sector organizations today - why the data resource becomes complex. Chapter 2 introduces the basic concepts of planned data resource comparity - how to make the data resource elegant and simple. Chapter 3 presents the concepts, principles, and techniques of a Common Data Architecture within which all data in the organization are understood and managed.

Chapters 4 through 8 present the five architectural aspects of data resource management. Chapter 4 explains the development of formal data names. Chapter 5 explains the development of comprehensive data definitions. Chapter 6 explains the development of proper data structures. Chapter 7 explains the development of precise data integrity rules. Chapter 8 explains the management of robust data documentation. Chapters 9 through 13 present the five cultural aspects of data resource management. Chapter 14 presents a summary explaining that development of a comparate data resource is a cultural choice of the organization and the need for a formal data resource management profession.

From the Foreword, by Chris Potts, author of fruITion and recrEAtion:

The challenge, as Michael observes in the very first chapter, is that you can't actually administer, manage, or govern data, only people's choices about data. This crucial and valuable insight - and what to do about it - is one of many that the author offers us from more than 40 years in the 'data game', as he calls itâ€|As Michael recounts from his own experiences and others, in the intervening time, much has changed and nothing has changed. New business ideas and technologies come, and some old ones go. But truths survive. Data are assets, and we choose how to manage them. These are the essential truths on which good data management strategies will always be built.

Every data management professional needs to read this book and be emboldened in their strategies for influencing how their organization creates value from the truth that data are assets. There are benefits for the organization itself, and for its contribution to the economy and society. Every one of us needs to know how best to manage the data we hold or use, whether those data are ours or not. As members of society and as organizations, we have yet to realize the true potential of good data management, and of the professionals who know how it's done.

Table of Contents

  1. FIGURES
  2. FOREWORD
  3. PREFACE
  4. ACKNOWLEDGEMENTS
  5. ABOUT THE AUTHOR
  6. Chapter 1 RAMPANT DATA DISPARITY
    1. IMPORTANT OBSERVATIONS
    2. DISPARATE DATA
    3. DATA DISPARITY CONTRIBUTORS
    4. CHOOSING SUCCESS OR FAILURE
    5. SUMMARY
    6. QUESTIONS
  7. Chapter 2 PLANNED DATA COMPARITY
    1. SIMPLICITY
    2. DATA AS A RESOURCE
    3. DATA RESOURCE QUALITY
    4. DATA RESOURCE MANAGEMENT CONCEPTS
    5. SUPPORTING PRINCIPLES
    6. SUPPORTING THEORIES
    7. ACHIEVING DATA COMPARITY
    8. SUMMARY
    9. QUESTIONS
  8. Chapter 3 COMMON DATA ARCHITECTURE
    1. THE PARADIGM
    2. CONCEPTS
    3. DATA ARCHITECHNOLOGY
    4. OPPORTUNITY TO CHOOSE
    5. SUMMARY
    6. QUESTIONS
  9. Chapter 4 FORMAL DATA NAMES
    1. INFORMAL DATA NAMES
    2. FORMAL DATA NAME CONCEPT
    3. FORMAL DATA NAME PRINCIPLES
    4. SUMMARY
    5. QUESTIONS
  10. Chapter 5 COMPREHENSIVE DATA DEFINITIONS
    1. VAGUE DATA DEFINITIONS
    2. COMPREHENSIVE DATA DEFINITION CONCEPT
    3. COMPREHENSIVE DATA DEFINITION PRINCIPLES
    4. SUMMARY
    5. QUESTIONS
  11. Chapter 6 PROPER DATA STRUCTURE
    1. IMPROPER DATA STRUCTURES
    2. PROPER DATA STRUCTURE CONCEPT
    3. PROPER DATA STRUCTURE PRINCIPLES
    4. SUMMARY
    5. QUESTIONS
  12. Chapter 7 PRECISE DATA INTEGRITY RULES
    1. IMPRECISE DATA INTEGRITY RULES
    2. PRECISE DATA INTEGRITY RULE CONCEPT
    3. PRECISE DATA INTEGRITY RULE PRINCIPLES
    4. SUMMARY
    5. QUESTIONS
  13. Chapter 8 ROBUST DATA DOCUMENTATION
    1. LIMITED DATA DOCUMENTATION
    2. ROBUST DATA DOCUMENTATION CONCEPT
    3. ROBUST DATA DOCUMENTATION PRINCIPLES
    4. SUMMARY
    5. QUESTIONS
  14. Chapter 9 REASONABLE DATA ORIENTATION
    1. UNREASONABLE DATA ORIENTATION
    2. REASONABLE DATA ORIENTATION CONCEPT
    3. REASONABLE DATA ORIENTATION PRINCIPLES
    4. SUMMARY
    5. QUESTIONS
  15. Chapter 10 ACCEPTABLE DATA AVAILABILITY
    1. UNACCEPTABLE DATA AVAILABILITY
    2. ACCEPTABLE DATA AVAILABILITY CONCEPT
    3. ACCEPTABLE DATA AVAILABILITY PRINCIPLES
    4. SUMMARY
    5. QUESTIONS
  16. Chapter 11 ADEQUATE DATA RESPONSIBILITY
    1. INADEQUATE DATA RESPONSIBILITY
    2. ADEQUATE DATA RESPONSIBILITY CONCEPT
    3. ADEQUATE DATA RESPONSIBILITY PRINCIPLES
    4. SUMMARY
    5. QUESTIONS
  17. Chapter 12 EXPANDED DATA VISION
    1. RESTRICTED DATA VISION
    2. EXPANDED DATA VISION CONCEPT
    3. EXPANDED DATA VISION PRINCIPLES
    4. SUMMARY
    5. QUESTIONS
  18. Chapter 13 APPROPRIATE DATA RECOGNITION
    1. INAPPROPRIATE DATA RECOGNITION
    2. APPROPRIATE DATA RECOGNITION CONCEPT
    3. APPROPRIATE DATA RECOGNITION PRINCIPLES
    4. SUMMARY
    5. QUESTIONS
  19. Chapter 14 A CULTURAL CHOICE
    1. DATA ARE A CRITICAL RESOURCE
    2. A BUSINESS ORIENTATION
    3. A CULTURAL ORIENTATION
    4. FORGING A FORMAL PROFESSION
    5. CHOOSING DATA RESOURCE MANAGEMENT
    6. SUMMARY
    7. QUESTIONS
  20. GLOSSARY
  21. BIBLIOGRAPHY
  22. INDEX