NoSQL and SQL Data Modeling: Bringing Together Data, Semantics, and Software

How do we design for data when traditional design techniques cannot extend to new database technologies? In this era of big data and the Internet of Things, it is essential that we have the tools we need to understand the data coming to us faster than ever before, and to design databases and data processing systems that can adapt easily to ever-changing data schemas and ever-changing business requirements. There must be no intellectual disconnect between data and the software that manages it. It must be possible to extract meaning and knowledge from data to drive artificial intelligence applications. Novel NoSQL data organization techniques must be used side-by-side with traditional SQL databases. Are existing data modeling techniques ready for all of this?

The Concept and Object Modeling Notation (COMN) is able to cover the full spectrum of analysis and design. A single COMN model can represent the objects and concepts in the problem space, logical data design, and concrete NoSQL and SQL document, key-value, columnar, and relational database implementations. COMN models enable an unprecedented level of traceability of requirements to implementation. COMN models can also represent the static structure of software and the predicates that represent the patterns of meaning in databases.

This book will teach you:

  • the simple and familiar graphical notation of COMN with its three basic shapes and four line styles
  • how to think about objects, concepts, types, and classes in the real world, using the ordinary meanings of English words that aren't tangled with confused techno-speak
  • how to express logical data designs that are freer from implementation considerations than is possible in any other notation
  • how to understand key-value, document, columnar, and table-oriented database designs in logical and physical terms
  • how to use COMN to specify physical database implementations in any NoSQL or SQL database with the precision necessary for model-driven development

A quick reference guide to COMN is included in an appendix. The full notation reference is available at http: //www.tewdur.com/.

1124056076
NoSQL and SQL Data Modeling: Bringing Together Data, Semantics, and Software

How do we design for data when traditional design techniques cannot extend to new database technologies? In this era of big data and the Internet of Things, it is essential that we have the tools we need to understand the data coming to us faster than ever before, and to design databases and data processing systems that can adapt easily to ever-changing data schemas and ever-changing business requirements. There must be no intellectual disconnect between data and the software that manages it. It must be possible to extract meaning and knowledge from data to drive artificial intelligence applications. Novel NoSQL data organization techniques must be used side-by-side with traditional SQL databases. Are existing data modeling techniques ready for all of this?

The Concept and Object Modeling Notation (COMN) is able to cover the full spectrum of analysis and design. A single COMN model can represent the objects and concepts in the problem space, logical data design, and concrete NoSQL and SQL document, key-value, columnar, and relational database implementations. COMN models enable an unprecedented level of traceability of requirements to implementation. COMN models can also represent the static structure of software and the predicates that represent the patterns of meaning in databases.

This book will teach you:

  • the simple and familiar graphical notation of COMN with its three basic shapes and four line styles
  • how to think about objects, concepts, types, and classes in the real world, using the ordinary meanings of English words that aren't tangled with confused techno-speak
  • how to express logical data designs that are freer from implementation considerations than is possible in any other notation
  • how to understand key-value, document, columnar, and table-oriented database designs in logical and physical terms
  • how to use COMN to specify physical database implementations in any NoSQL or SQL database with the precision necessary for model-driven development

A quick reference guide to COMN is included in an appendix. The full notation reference is available at http: //www.tewdur.com/.

39.95 In Stock
NoSQL and SQL Data Modeling: Bringing Together Data, Semantics, and Software

NoSQL and SQL Data Modeling: Bringing Together Data, Semantics, and Software

by Ted Hills
NoSQL and SQL Data Modeling: Bringing Together Data, Semantics, and Software

NoSQL and SQL Data Modeling: Bringing Together Data, Semantics, and Software

by Ted Hills

Paperback

$39.95 
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Overview

How do we design for data when traditional design techniques cannot extend to new database technologies? In this era of big data and the Internet of Things, it is essential that we have the tools we need to understand the data coming to us faster than ever before, and to design databases and data processing systems that can adapt easily to ever-changing data schemas and ever-changing business requirements. There must be no intellectual disconnect between data and the software that manages it. It must be possible to extract meaning and knowledge from data to drive artificial intelligence applications. Novel NoSQL data organization techniques must be used side-by-side with traditional SQL databases. Are existing data modeling techniques ready for all of this?

The Concept and Object Modeling Notation (COMN) is able to cover the full spectrum of analysis and design. A single COMN model can represent the objects and concepts in the problem space, logical data design, and concrete NoSQL and SQL document, key-value, columnar, and relational database implementations. COMN models enable an unprecedented level of traceability of requirements to implementation. COMN models can also represent the static structure of software and the predicates that represent the patterns of meaning in databases.

This book will teach you:

  • the simple and familiar graphical notation of COMN with its three basic shapes and four line styles
  • how to think about objects, concepts, types, and classes in the real world, using the ordinary meanings of English words that aren't tangled with confused techno-speak
  • how to express logical data designs that are freer from implementation considerations than is possible in any other notation
  • how to understand key-value, document, columnar, and table-oriented database designs in logical and physical terms
  • how to use COMN to specify physical database implementations in any NoSQL or SQL database with the precision necessary for model-driven development

A quick reference guide to COMN is included in an appendix. The full notation reference is available at http: //www.tewdur.com/.


Product Details

ISBN-13: 9781634621090
Publisher: Technics Publications
Publication date: 04/29/2016
Pages: 260
Product dimensions: 7.50(w) x 9.20(h) x 0.60(d)

Table of Contents

Acknowledgements xiii

Introduction 1

Taking Care of Data 3

Plant Change Control 2.0 5

Where did the Savings Come From? 5

Why Model? 8

Why COMN? 11

Book Outline 12

Book Audience 13

NoSQL Database Developer 13

SQL Database Developer 14

Data Modeler 14

Software Developer 14

Ontologist 15

Part I Real Words in the Real World 17

Chapter 1 It's All about the Words 19

References 21

Chapter 2 Things: Entities, Objects, and Concepts 23

Chapter Glossary 28

Chapter 3 Containment and Composition 29

Containment 29

Composition 31

Chapter Glossary 33

Chapter 4 Types and Classes in the Real World 35

Collections of Objects 35

Sets of Concepts 37

Sets of Objects 38

Types and Classes 38

Types Designate Sets 39

Classes Describe Objects 40

Three Aspects of Types and Classes 41

Chapter Glossary 41

Part II The Tyranny of Confusion 43

Chapter 5 Entity-Relationship Modeling 45

Logical E-R Data Models 45

Multiple Levels of Abstraction 48

Limitations of E-R Modeling Notation 50

NoSQL Arrays and Nested Data Structures 50

Lack of Reusable Composite Types 51

Lack of Place 54

Modeling the Real World 54

Representing Individual Entities 55

Mapping Between Models 55

Data in Software 56

Terminology 56

Entity 56

Conceptual 57

E-R Terms Mapped to COMN Terms 57

References 58

Chapter 6 The Unified Modeling Language 59

Class Diagrams 59

Stereotyping 60

Limitations of the UML 61

Lack of Keys 61

Middling Level of Abstraction 61

Lack of Concept 62

Subclassing versus Subtyping 62

Terminology 63

Relationship, Composition and Aggregation 63

Type and Implementation Class 64

UML Terms Mapped to COMN Terms 64

References 65

Chapter 7 Fact-Based Modeling Notations 67

Facts and Relationships 67

Limitations of Fact-Based Modeling 69

Lack of Instances 70

Incompleteness 70

Difficulty 71

Terminology 71

Fact-Based Modeling Terms Mapped to COMN Terms 72

References 74

Chapter 8 Semantic Notations 75

Predicates and RDF Statements 75

Doubles and Quadruples 78

OWL 79

Graphical Notations for Semantics 80

Terminology 80

Chapter 9 Object-Oriented Programming Languages 83

Classes, Objects, Types, and Variables 83

Terminology 85

Part III Freedom in Meaning 87

Chapter 10 Objects and Classes 89

Material Objects 90

Objects with States 90

Meaning of States 91

Objects with More States 92

Even More States 93

Methods 94

Material Objects in Computers 94

Summary 96

Computer Object Defined 97

Composing Objects 98

Software Object Composition 98

Authorizing Certain Routines 101

Summary 102

Chapter Glossary 104

Chapter 11 Types in Data and Software 105

Types in Programming and Databases 105

What does a Type tell us? 106

Classes in Object-Oriented Software 107

Separating Type and Class 108

Simple Types 112

References 116

Chapter Glossary 116

Chapter 12 Composite Types 117

Composite Types as Logical Record Types 117

Types Representing Things in the Real World: Identification 119

Stepwise Refinement and Completeness 122

Types Representing Other Types 123

Measures as Composite Types 125

Nested Types 128

Modeling Documents 130

Arrays 132

Chapter Glossary 135

References 135

Chapter 13 Subtypes and Subclasses 137

Subtypes 137

Restriction is Subtyping 143

Subclasses 144

Subtypes and Extensions: Perfect Together 146

Inheritance 151

Using Subtype Variables and Values 151

Using Extending Types and Classes 152

Projection: The inverse of Extension 153

Chapter Glossary 154

Chapter 14 Data and Information 155

Information 155

Is Information Always True? 157

From Information to Data 157

Data en Masse 159

Variable Names 160

Summary 160

Information and Data as Colloquialisms 161

Information En Masse 161

It's Just Data 161

Putting it all Together 162

"Unstructured Data" and "Semi-Structured Data" 163

Data Object 165

Chapter Glossary 166

Chapter 15 Relationships and Roles 167

Arrivals and Departures 167

Labeling Relationship Lines 170

Cleaning up the Model 171

Roles, Predicates, and Relationships 174

Chapter Glossary 175

Chapter 16 The Relational Theory of Data 177

What is a Relation? 178

The Order of Rows 178

The Uniqueness of Rows 180

The Significance of Columns 181

Summary 182

Technical Relational Terminology 182

Tuple and Relation Schemes 185

Giving Data to the System 185

Data Attribute Versus Attribute 186

Relational Terminology Reprise 187

Composite Data Attributes 187

Relational Operations 190

NoSQL Versus the Relational Model 191

SQL Versus the Relational Model 192

Terminology 193

Chapter Glossary 194

Chapter 17 NoSQL and SQL Physical Design 197

What's Different about NoSQL? 197

Database Performance 198

ACID versus BASE and Scalability 199

ACID 199

Atomicity 200

Consistency 200

Isolation 200

Durability 201

BASE and CAP 201

NoSQL and SQL Data Organization 203

Key/Value DBMS 204

Graph DBMS 205

Document DBMS 206

Columnar DBMS 207

Tabular DBMS 208

Summary 211

References 211

Part IV Case Study 213

Chapter 18 The Common Coffee Shop 215

Analysis: Documenting Real-World Entities 215

Logical Data Modeling: Designing the Data 220

Physical Data Modeling: Designing the Implementation 226

Appendix: COMN Quick Reference 231

Glossary 235

Photo and Illustration Credits 239

Index 241

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