How to use Neo4j to analyse the Offshore Leaks : the case of Azerbaijan by Jean Villedieu.
From the post:
Introduction to Problem
The Offshore Leaks released in 2013 by the ICIJ is a rarity. It is a big dataset of real information about some of the most secret places on earth : the offshore financial centers. The investigation of the ICIJ brought to the surface many interesting stories including the suspicious activities of the President of Azerbaijan. We are going to see how graph technologies can help us make sense of the complex data in the Offshore Leaks.
Our data model for the Offshore Leaks
We want to know how the President of Azerbaijan is connected to offshore accounts. This means that we will need to focus on the network he uses to control his assets stored in offshore entities. These networks includes family members and a complex set of intermediaries or partners. We want to see how things are connected so we are going to have to represent each of these entities as distinct nodes in a graph.
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A good tutorial on Neo4j, Cypher (query language) and modeling data.
Notice I didn’t say “modeling data with graphs.” That is the result in this case but modeling data should inform your choice of storage or analytical solutions. Saying that graphs can model any data is a truism that doesn’t lead to informed IT choices.
In this particular case I would suggest using graphs, in part because the relationships between actors and their types aren’t known in advance. Some aspects of stock trading systems would not present the same issues.
Graphs don’t have this as an inherent limitation but if several groups were gathering information about President Ilham Aliyev and quite easily using different names/identifiers, how would you merge those graphs together? Would you have to re-create the relationships between actors if new nodes had to replace old ones?
Graphs are very good for some data. Distributed and collaborative graphs are even better.
Further information on Offshore Leaks.
I first saw this in a tweet by GraphemeDB.