In the previous chapters, we have studied about how to work with different aspects of the incredible graph database, Neo4j, from its installation, querying, and traversals, to performance optimizations at the production level. We have also had a peek under the hood of Neo4j in order to understand its functionality. Neo4j has a wide range of practical applications. Typically, any scenario that includes connected data represented graphically, Neo4j proves to be the perfect resource for storage and processing needs. With rapidly increasing connected devices and sensor driven technology, graph-based analytics solutions are becoming more popular in the business world, especially because they are simpler to interpret and visualize. Graph databases like Neo4j find extensive use in the route generation, fraud analysis, and impact analysis in networks. However, the latest and most popular use case of graph technologies is in the realm of...