You are previewing Data and Reality: A Timeless Perspective on Perceiving and Managing Information in Our Imprecise World, 3rd Edition.
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Data and Reality: A Timeless Perspective on Perceiving and Managing Information in Our Imprecise World, 3rd Edition

Book Description

Let's step back to the year 1978. Sony introduces hip portable music with the Walkman, Illinois Bell Company releases the first mobile phone, Space Invaders kicks off the video game craze, and William Kent writes Data and Reality. We have made amazing progress in the last four decades in terms of portable music, mobile communication, and entertainment, making devices such as the original Sony Walkman and suitcase-sized mobile phones museum pieces today. Yet remarkably, the book Data and Reality is just as relevant to the field of data management today as it was in 1978.

Data and Reality gracefully weaves the disciplines of psychology and philosophy with data management to create timeless takeaways on how we perceive and manage information. Although databases and related technology have come a long way since 1978, the process of eliciting business requirements and how we think about information remains constant. This book will provide valuable insights whether you are a 1970s data-processing expert or a modern-day business analyst, data modeler, database administrator, or data architect.

This third edition of Data and Reality differs substantially from the first and second editions. Data modeling thought leader Steve Hoberman has updated many of the original examples and references and added his commentary throughout the book, including key points at the end of each chapter.

The important takeaways in this book are rich with insight yet presented in a conversational writing style. Here are just a few of the issues this book tackles:

  • Has "business intelligence" replaced "artificial intelligence"?

  • Why is a map's geographic landscape analogous to a data model's information landscape?

  • Where do forward and reverse engineering fit in our thought process?

  • Why are we all becoming "data archeologists"?

  • What causes the communication chasm between the business professional and the information technology professional, and how can the logical data model bridge this gap?

  • Why do we invest in hardware and software to solve business problems before determining what the business problems are in the first place?

  • What is the difference between oneness, sameness, and categories?

  • Why does context play a role in every design decision?

  • Why do the more important attributes become entities or relationships?

  • Why do symbols speak louder than words?

  • What's the difference between a data modeler, a philosopher, and an artist?

  • Why is the 1975 dream of mapping all attributes still a dream today?

  • What influence does language have on our perception of reality?

  • Can we distinguish between naming and describing?

Table of Contents

  1. Copyright
  2. Praise for Data and Reality
  3. A Note by Chris Date on the Republication of Data and Reality
  4. Foreword to the New Edition of Data and Reality
  5. Preface to the Third Edition
  6. Preface to the Second Edition
  7. Preface to the First Edition
  8. 1. Entities
    1. One Thing
      1. ONENESS (WHAT IS "ONE THING"?)
      2. SAMENESS (HOW MANY THINGS IS IT?)
        1. Change
        2. The Murderer and the Butler
      3. CATEGORIES (WHAT IS IT?)
    2. Existence
      1. HOW REAL?
      2. HOW LONG?
  9. 2. The Nature of an Information System
    1. Data Description
      1. LEVELS OF DESCRIPTION
      2. THE TRADITIONAL SEPARATION OF DESCRIPTIONS AND DATA
    2. Records and Representatives
  10. 3. Naming
    1. How Many Ways?
    2. What Is Being Named?
    3. Uniqueness, Scope, and Qualifiers
      1. DELIBERATE NON-UNIQUENESS
      2. EFFECTIVE QUALIFICATION
        1. Uniqueness Within Qualifier
        2. Singularity of Qualifier
        3. Existence of Qualifier
        4. Invariance of Qualifiers
    4. Scope of Naming Conventions
    5. Changing Names
    6. Versions
    7. Names, Symbols, Representations
    8. Why Separate Symbols and Things?
      1. DO NAMES "REPRESENT"?
      2. SIMPLE AMBIGUITY
      3. SURROGATES, INTERNAL IDENTIFIERS
    9. Sameness (Equality)
      1. TESTS
      2. FAILURES
  11. 4. Relationships
    1. Degree, Domain, and Role
    2. Forms of Binary Relationships
      1. COMPLEXITY
      2. CATEGORY CONSTRAINTS
      3. SELF-RELATION
      4. OPTIONALITY
      5. THE NUMBER OF FORMS
    3. Other Characteristics
      1. TRANSITIVITY
      2. SYMMETRY
      3. ANTI-SYMMETRY
      4. IMPLICATION (COMPOSITION)
      5. CONSISTENCY (SUBSET)
      6. RESTRICTIONS
      7. ATTRIBUTES AND RELATIONSHIPS OF RELATIONSHIPS
      8. NAMES
    4. Naming Conventions
      1. NO NAME
      2. ONE NAME
      3. TWO NAMES
    5. Relationships and Instances Are Entities
  12. 5. Attributes
    1. Some Ambiguities
    2. Attribute vs. Relationship
    3. Are Attributes Entities?
    4. Attribute vs. Category
    5. Options
    6. Conclusion
  13. 6. Types and Categories and Sets
    1. "Type": A Merging of Ideas
      1. GUIDELINES
      2. CONFLICTS
    2. Extended Concepts
      1. ARBITRARY SETS
      2. GENERAL CONSTRAINTS
      3. TYPES, IF YOU WANT THEM
    3. Sets
      1. SETS AND ATTRIBUTES
      2. TYPE VS. POPULATION (INTENSION VS. EXTENSION)
      3. REPRESENTATION OF SETS
  14. 7. Models
    1. General Concept of Models
    2. The Logical Model: Sooner, or Later?
    3. Models of Reality vs. Models of Data
  15. 8. The Record Model
    1. Semantic Implications
    2. The Type/Instance Dichotomy
      1. AN INSTANCE OF EXACTLY ONE TYPE
      2. DESCRIPTIONS ARE NOT INFORMATION
      3. REGULARITY (HOMOGENEITY)
    3. Naming Practices
      1. STRUCTURED NAMES
      2. COMPOSITE NAMES AND THE SEMANTICS OF RELATIONSHIPS
    4. Implicit Constraints
  16. 9. Philosophy
    1. Reality and Tools
    2. Points of View
    3. A View of Reality
  17. Bibliography