What does Justin Bieber have to do with our relationships to, well, anything? If nothing else, his staggering 105.8 million followers on Twitter (at the time of this conversation) is a real challenge for data scientists. If you wanted to know how The Bieb’s assemblage relates to him and one another, you could never achieve it with an entity-first relationship model — you know, columns, rows and spreadsheets, or, as Wikipedia calls it, “a simple relational database implementation, each row of a table represents one instance of an entity type, and each field in a table represents an attribute type.” If you really want to begin to understand the reasoning behind The Beib’s broad fanbase, you’d need to organize data relationship-first.

This is just one of the real-world examples Dr. Denise Gosnell offered regarding the importance of graph databases and the tech behind them that is shifting how we think about and organize data. The head of global Graph practice at DataStax and one of the world’s foremost researchers on graph theory, graph algorithms, graph databases, and applications of graph data across all industry verticals offered more business use cases as well, including the interrelatedness of your primary and secondary LinkedIn connections and the growing popularity of smart meters.