This is a customer fidality analysis project using a graph-based NoSQL database called HyperGraphDB.
A graph database is a database that uses graph structures with nodes, and edges to represent and store information. In a graph database:
- Nodes: represent entities such as people, businesses, accounts, or any other item you might want to keep track of.
- Edges: are the lines that connect nodes to nodes or Edges to other Edges, and they represent the relationship between the two. Most of the important information is really stored in the edges.
Meaningful patterns emerge when one examines the connections and interconnections of nodes, and edges.
The technology I have used for this project is called HyperGraphDB which is an open source graph-based database. IDEs for using HyperGraphDB are the following:
- There is a IDE designed on HyperGraphDB called Seco which is a software scripting, prototyping environment for the Java platform.
- Eclipse.
HyperGraphDB is a general purpose, extensible, portable, distributed, embeddable, open-source data storage mechanism. It is written in Java. It is a graph database designed specifically for artificial intelligence and semantic web projects, it can also be used as:
- an embedded object-oriented database for projects of all sizes.
- a graph database.
- a (non-SQL) relational database.
We chose these two requirements to implement:
- Management of the chain of resellers, customers affiliated to the loyalty program (through the resellers), relations among resellers, and so on.
- Sales statistics (by date, period, location, user segment,... )
For more details, feel free to review the attached presentation and the report.