Imagine you are building an online game application. In your application, users can follow other players as a way to make friends, track their progress, and find opponents to play against. Users can also indicate different interests they have as a way to find people with similar interests.
As part of your application, you want to generate recommendations of people that users should follow. These recommendations should be intelligent based on the existing interests and friends that a user has.
In this lab, you learn how to use Amazon Neptune to store user connections and to recommend new connections for users. A graph-based database is perfect for this use case as you can analyze existing connections in a graph to identify high-value missing connections.
In Module 1, you configure your environment and download the code that you use during the lab.
Time to Complete Module: 20 Minutes
In this module, you learned about the example application you build in this lab. You also set up an AWS account and configured an AWS Cloud9 instance.
You are now ready to start the lab. In the next module, you provision your Amazon Neptune database.