Scalable, Fast Analytics with Graph - Why and How 


Thomas Cook, Director, Cambridge Semantics

Tom Zeppenfeldt, Founder, Graphileon

data analysisWhen it comes to dealing with large, complex, and disparate data sets, traditional database technologies are unable to keep pace with the rich analytics necessary to power today’s data-driven applications. Graph analytics databases are becoming the underlying infrastructure for AI and machine learning. These databases allow users to ask complex questions across complex data, which is not always practical or even possible at scale using other approaches. They also enable faster insights against massive data sets when combined with pattern recognition, statistical analysis, and AI/machine learning. And in the case of standards-based graph databases, they connect with popular visualization tools like Graphileon, allowing users to easily explore their data stores and quickly build compelling graph-based applications.

Watch Cambridge Semantics’ graph database guru, Thomas Cook, and Graphileon's founder, Tom Zeppenfeldt, in this on-demand webinar as they demonstrate how AnzoGraph DB, an analytical graph database, can be used to do difficult-to-perform analytics on large data sets and to explore and uncover new opportunities using the Graphileon user interface.