Knewton explores Graph Databases, Neo4j and Cypher
Knewton, online educational technology and creator of The Knewton Adaptive Learning Platform, recently attended last week’s NYC Graph Meetup on Big Data and featuring Dr. Jim Webber, Chief Scientist of Neo Technology.
Jordan Lewis and Urjit Bhatia, Knewton Software engineers, also known as Knewton Knerds, commented on Neo4j and exploring the role of graph databases with complex, high-connected data, and how that could apply with Knewton business objectives.
As the size of datasets being generated, processed, and presented continues to grow, the relative strengths and weaknesses of different data structures, including graphs, have become more and more significant in everyday applications.
With Knewton, for instance, we need to understand the proficiencies of each student in relation to the proficiencies of all other students in the network. This is how it works: in isolation, each student’s response to each question is only a tiny scrap of information, but when propagated through the entire system and understood in context, the value of that information is amplified tremendously. So yeah, I think the popularity of NY Graph Meetup reflects the fact that we’re at an inflection point as a community regarding graphs. Everyone is realizing how complex their data is and grappling with its complexity. It’s so intricate that it’s difficult to model in any conventional way.
Cypher, a graph query language, is something that would be great to have at Knewton. It will make it easier to validate the data we have. We also learned about how people are dealing with things like super-nodes, sometimes called “Britney Spears Nodes” after her popular fan following on Twitter. Such nodes have millions of connections while others have only a couple hundred.