Finding patterns in procurements and tenders using a graph database
Michael Swords · KTH Publication Database DiVA (KTH Royal Institute of Technology) · 2019
Graph databases are becoming more and more prominent as a result of the increasing amount of connected data. Storing data in a graph database allows for greater insight into the relationships between the data and not just the data itself.An area that has a large focus on relationship is the area of public procurements. Relationships such as who created which procurement and who was the winner. The procurement data today can be very unstructured or inaccessible which means that there is a low amount of analysis available in the area. To make it easier to analyse the procurement market there is a need for a proficient way of storing the data. This thesis provides a proof of concept of the combination of public procurements and graph databases. A comparison is made between two models of different granularity, measuring both query speed and storage size. There has also been an exploration of what interesting patterns that can be extrapolated from the public procurement data using centrality and community detection.The result of the model comparison shows a distinct increase in query speed at the cost of storage size. The result of the exploration is several examples of interesting patterns retrieved using a graph database with public procurement data, which show the potential of graph databases.