The Graph Database

In general, a graph database consists of nodes and edges connecting the nodes; that can be compared to the cells and synapses of a human brain. By using this structure, known as a graph, modelling complex relationships between any kind of information in an intuitive way becomes possible. In addition, sophisticated algorithms exist that allow quickly extracting information from the database.

BlitzMinds uses a graph database to store all information related to a project. The steps in a Design Thinking project connect, group and reorganize the information from previous steps, requiring a high amount of data flexibility. The connections need to be stored losslessly and in an easily retrievable and traceable way in order for no information to be lost; this crucial part of Design Thinking processes that need to be implemented on a large scale is handled extraordinarily well by graph databases, resulting in them being the best choice for InsideUX®.

Integrating Artificial Intelligence

The versatile and highly scalable properties of graph databases allow them to be the ideal base for machine learning approaches, resulting in the database being used as a knowledge graph. Specifically, BlitzMinds’ Innovation Solution InsideUX® provides a recommendation engine, which uses state of the art intelligent retrieval algorithms to recommend the right information at the right time.

For example, if the system detects that another employee has previously gained insights from a similar customer or persona, the current user is connected directly to them, resulting in effortless exchange of valuable experiences. Apart from that, intelligent recommendation systems empower the generation of even deeper relationships between the pieces of information an industry-scale project consists of naturally.