The POLE data model - Person, Object, Location, Event - is commonly applied to security and investigative use cases such as policing, anti-terrorism, border control, and social services. It’s also a great fit for the graph and graph algorithms. Joe Depeau demonstrates how Neo4j, graph algorithms, and the POLE data model can support police and social services investigations and generate real-time insights using the Neo4j browser as well as some sample Tableau visualisations.
Originally from the USA but now living in the UK, Joe has over 20 years of varied experience in the IT industry across a number of domains and specialties. Most recently, Joe has focused on technical pre-sales and solution architecture in the data and analytics space. When not geeking out over data and technology he enjoys camping, tending to his garden and allotment, reading, and playing boardgames and RPGs. He also bakes a mean cheesecake.
Lee Hong is a Senior Data Scientist at ICC in the Advanced Analytics Practice, which is responsible for delivering predictive analytics and insights across a range of industry verticals. He holds a PhD in Kinesiology from The Pennsylvania State University and is a former Neuroscience professor and researcher.
Kelsey Bieri is a Data Governance Analyst at ICC in the Master Data Management and Data Governance Practice. She has contributed to numerous data governance and data lineage projects in the Banking industry, helping organizations build a better understanding of their data universe. Kelsey holds a degree in Management Information Systems from the College of Business at Ohio University.