The POLE (Person, Object, Location, Event) data model is being leveraged by practitioners to work with crime data, and it's a great fit for graph database technology and graph algorithms. A proof of concept using publicly available datasets showed that authorities can gain useful insights into investigations by analyzing connections in complex data. Graph technology excels at mining connected data, which is hard to capture through conventional database technologies like RDBMS. By building a Neo4j graph database of 29,000 crimes and generating 106,000 relationships, practitioners were able to find deep and complex networks of connections that suggested obscure family relationships, social associations, and clusters of people and crimes. These insights could support ongoing criminal investigations or initiate new ones, enabling data-driven decision making and maximizing police resources in the face of budget constraints.