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Graph Data Modeling in Python

You're reading from   Graph Data Modeling in Python A practical guide to curating, analyzing, and modeling data with graphs

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Product type Paperback
Published in Jun 2023
Publisher Packt
ISBN-13 9781804618035
Length 236 pages
Edition 1st Edition
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Authors (2):
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Gary Hutson Gary Hutson
Author Profile Icon Gary Hutson
Gary Hutson
Matt Jackson Matt Jackson
Author Profile Icon Matt Jackson
Matt Jackson
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Table of Contents (16) Chapters Close

Preface 1. Part 1: Getting Started with Graph Data Modeling
2. Chapter 1: Introducing Graphs in the Real World FREE CHAPTER 3. Chapter 2: Working with Graph Data Models 4. Part 2: Making the Graph Transition
5. Chapter 3: Data Model Transformation – Relational to Graph Databases 6. Chapter 4: Building a Knowledge Graph 7. Part 3: Storing and Productionizing Graphs
8. Chapter 5: Working with Graph Databases 9. Chapter 6: Pipeline Development 10. Chapter 7: Refactoring and Evolving Schemas 11. Part 4: Graphing Like a Pro
12. Chapter 8: Perfect Projections 13. Chapter 9: Common Errors and Debugging 14. Index 15. Other Books You May Enjoy

Data Model Transformation – Relational to Graph Databases

Up until this point, we have been getting you ready to work with graph data structures in a real-world environment. This will transition your knowledge even further, taking you from setting up your own MySQL database instances to building a recommendation system. This is an important step forward since many solutions out there in the wild are based on data being extracted from relational database environments, such as MySQL.

In this chapter, we will start with setting up your MySQL graph database and then move on to how to work with graph data and querying the database engine. Carrying on from there, we will look at path-based methods for carrying out your analysis. This will be followed by considerations of schema design for graph solutions and building a recommendation solution so that you can use a user’s gaming history on the popular platform Steam, along with a graph to predict, or highlight, games that...

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