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Hands-On Big Data Modeling

You're reading from   Hands-On Big Data Modeling Effective database design techniques for data architects and business intelligence professionals

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Product type Paperback
Published in Nov 2018
Publisher Packt
ISBN-13 9781788620901
Length 306 pages
Edition 1st Edition
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Authors (3):
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James Lee James Lee
Author Profile Icon James Lee
James Lee
Tao Wei Tao Wei
Author Profile Icon Tao Wei
Tao Wei
Suresh Kumar Mukhiya Suresh Kumar Mukhiya
Author Profile Icon Suresh Kumar Mukhiya
Suresh Kumar Mukhiya
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Table of Contents (17) Chapters Close

Preface 1. Introduction to Big Data and Data Management 2. Data Modeling and Management Platforms FREE CHAPTER 3. Defining Data Models 4. Categorizing Data Models 5. Structures of Data Models 6. Modeling Structured Data 7. Modeling with Unstructured Data 8. Modeling with Streaming Data 9. Streaming Sensor Data 10. Concept and Approaches of Big-Data Management 11. DBMS to BDMS 12. Modeling Bitcoin Data Points with Python 13. Modeling Twitter Feeds Using Python 14. Modeling Weather Data Points with Python 15. Modeling IMDb Data Points with Python 16. Other Books You May Enjoy

Graph-data models

A graph is a just a collection of vertices and edges. The most convincing example of a graph-data model is a social network. Each piece of information in this world is connected. To store and process information correctly, a database must embrace and store the entity and its connectivity with another entity. This is where the graph-data model kicks in. Storing and accessing nodes and relationships in a graph database is an easy, efficient, and constant-time operation that permits a user to quickly traverse and get correct information.

Mathematically, a graph is a pair G = (V, E) of sets that satisfy E ( V X V). The elements of V are the vertices or nodes of the graph, G, and the elements of E are its edges or relationships.

Let's see a graph model of movies and actors.

Figure 5.6: Labeled graph model of movies and actors

From the movie data model given...

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