Graph Data Modeling for NoSQL and SQL by Frisendal, Thomas -- Read -- Imperial Library of Trantor

Index

Foreword By Karen Lopez Chapter 1 Introduction

1.1. Motivation 1.2. Audience 1.3. Outline 1.4. Acknowledgments

Chapter 2 Why Model?

2.1. Model What? 2.2. Providing Business Value from Big Data and NoSQL 2.3. Data Modeling Heritage

2.3.1. Evolution of Database 2.3.2. Pointer Database (DBOMP) 2.3.3. Hierarchical Workhorses 2.3.4. Programmer as Navigator 2.3.5. Chen, Entities, Attributes and Relationships 2.3.6. Relational Model 2.3.7. The Great Database War of the Eighties 2.3.8. Objects Galore! 2.3.9. Graph Models 2.3.10. Object Role Model (ORM) and Fact Modeling 2.3.11. New Keys in the Models 2.3.12. Data Modeling Conclusions

2.4. Perception, Cognition and Psychology

2.4.1. Perception and Cognition 2.4.2. Concept Maps 2.4.3. Conceptual Spaces 2.4.4. Knowledge Graphs 2.4.5. Cognitive Computing Example: Saffron 2.4.6. Ubiquitous Pointer 2.4.7. Think Spatially

Chapter 3 Real Requirements of Data Modeling

3.1. Post-relational Data Modeling 3.2. Finding Meaning and Structure

3.2.1. Working with Business People 3.2.2. Concept Models as Part of User Stories 3.2.3. Functional Dependency Profiling 3.2.4. Mining the Semantics

3.3. Visualization of Models

3.3.1. Functional Dependency Visualization 3.3.2. Understanding Structure and Content 3.3.3. Property Graphs 3.3.4. Progressive Visualization of Data Models 3.3.5. Tool Support for Property Graphs

3.4. Data Modeling Requirements

3.4.1. Solution Architecture 3.4.2. Business Concept Model Requirements 3.4.3. Solution Data Model Requirements 3.4.4. On Using Property Graphs 3.4.5. Physical Data Model Requirements 3.4.6. Keeping it Simple

Chapter 4 Data Modeling Described

4.1. Solution Modeling (Solution Model)

4.1.1. Business Concept Model 4.1.2. Power of Dependencies 4.1.3. Names Matter 4.1.4. Finding Patterns 4.1.5. Cardinality and Optionality 4.1.6. Housekeeping 4.1.7. Modeling the Subject Area Overview 4.1.8. Data Types 4.1.9. Identifiers, Keys, and Pointers 4.1.10. Keys 4.1.11. Handling Time 4.1.12. Design Involves Decisions 4.1.13. Abstraction, Specialization, and Generalization 4.1.14. Unusual Concepts

4.2. Transform, Optimize, and Deploy (Physical Model)

4.2.1. Creating the Physical Models 4.2.2. Denormalize with a Smile 4.2.3. Key / Value Targets 4.2.4. Document Stores 4.2.5. RDF and Triplestores 4.2.6. Property Graphs 4.2.7. Multidimensional Models 4.2.8. SQL Targets

Chapter 5 Selected Detailed Examples

5.1. From Relational Model to Property Graph Model 5.2. A Multidimensional Model 5.3. A Survey Form 5.4. FIBO Indices and Indicators Model

Chapter 6 Before Your Expedition Begins

Literature Index