Book Image

Learning Neo4j 3.x - Second Edition

By : Jerome Baton
Book Image

Learning Neo4j 3.x - Second Edition

By: Jerome Baton

Overview of this book

Neo4j is a graph database that allows traversing huge amounts of data with ease. This book aims at quickly getting you started with the popular graph database Neo4j. Starting with a brief introduction to graph theory, this book will show you the advantages of using graph databases along with data modeling techniques for graph databases. You'll gain practical hands-on experience with commonly used and lesser known features for updating graph store with Neo4j's Cypher query language. Furthermore, you'll also learn to create awesome procedures using APOC and extend Neo4j's functionality, enabling integration, algorithmic analysis, and other advanced spatial operation capabilities on data. Through the course of the book you will come across implementation examples on the latest updates in Neo4j, such as in-graph indexes, scaling, performance improvements, visualization, data refactoring techniques, security enhancements, and much more. By the end of the book, you'll have gained the skills to design and implement modern spatial applications, from graphing data to unraveling business capabilities with the help of real-world use cases.
Table of Contents (24 chapters)
Title Page
Credits
About the Authors
Acknowledgement
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface

Summary


In this chapter, we saw how to import data from different kinds of sources into our graph and saw which one is preferable. We know we can do funny and interesting things like importing the 1€ cafés dataset and a dataset of free wifi credentials.

More seriously, we know how to import datasets and how to combine them. It is up to you to find the datasets of your interest. This can really open the doors of perception of the world when you import data and then look at your graph.

Imagine you can combine statistics of crime rates, poverty, alcohol sales, and education levels.

We will now get back to Earth and deal with geolocalized data in the next chapter, Chapter 9, Going Spatial.