Great, you have cleared your first hurdle by building your data model and loading your data into a graph, but you know that there’s more. Now the real fun begins, finding out what secrets reside within you data.
We will use a data model we are all familiar with, family trees, and a common language, Apache Tinkerpop, to demonstrate how you can begin applying some common graph analytical techniques (e.g. Path analysis, centrality analysis, community detection) to pull interesting information from within your data.
- Who's married their 1st cousin?
- Who is the most influential person in my family?
- Am I really only 6 degrees from Kevin Bacon?
By the end of this session you will have enough knowledge to begin running useful analytics on your graphs, or at least have a better appreciation for how you can use analytics to provide valuable insight into your data.