Book Image

Graph Data Modeling in Python

By : Gary Hutson, Matt Jackson
Book Image

Graph Data Modeling in Python

By: Gary Hutson, Matt Jackson

Overview of this book

Graphs have become increasingly integral to powering the products and services we use in our daily lives, driving social media, online shopping recommendations, and even fraud detection. With this book, you’ll see how a good graph data model can help enhance efficiency and unlock hidden insights through complex network analysis. Graph Data Modeling in Python will guide you through designing, implementing, and harnessing a variety of graph data models using the popular open source Python libraries NetworkX and igraph. Following practical use cases and examples, you’ll find out how to design optimal graph models capable of supporting a wide range of queries and features. Moreover, you’ll seamlessly transition from traditional relational databases and tabular data to the dynamic world of graph data structures that allow powerful, path-based analyses. As well as learning how to manage a persistent graph database using Neo4j, you’ll also get to grips with adapting your network model to evolving data requirements. By the end of this book, you’ll be able to transform tabular data into powerful graph data models. In essence, you’ll build your knowledge from beginner to advanced-level practitioner in no time.
Table of Contents (16 chapters)
Part 1: Getting Started with Graph Data Modeling
Part 2: Making the Graph Transition
Part 3: Storing and Productionizing Graphs
Part 4: Graphing Like a Pro

Refactoring reasoning

As an organization grows and develops, its needs can change, including its data storage requirements. Data that is sufficient to operate a service or process can change over time, and it often pays to plan for changing requirements in advance. Managing change in database systems varies in difficulty depending on your current schema and database type, and in this chapter, we will discuss and demonstrate the advantages of using a graph data model when dealing with evolving data structures.

In this section, you will learn about the tools to help you prepare for refactoring effectively. This will include changes in relational schema, the impacts these can have on substantial schema rework, and what you should consider at the point of design, relating to evolving schemas that can effectively handle these changes.

Change in relational and graph databases

In more traditional relational database systems, adding new types of data can sometimes be challenging,...