Graph Analytics for Data Scientists

Analyzing data using conventional statistical methods involves looking at tabular data where data points are independent of each other, e.g. a person’s age is independent of any other person’s age.

These approaches limit the insight that can be gained as there’s often knowledge hidden in how one data point relates to another. For example, two people can be deemed similar if they have entirely different purchase histories but each have purchase histories similar to a third user.

This talk will go over how graph analytics can gain these sorts of insights not easily achievable through conventional data analysis performed on tabular data.

Meet Our Speaker

Paul Nguyen

Former Associate Software Engineer at Anaconda

Paul was an open-source software engineer at Anaconda, where he worked on Metagraph, a hardware backend independent graph algorithm solver. Prior to Anaconda, Paul was at Cycorp, where he worked on methods to enhance data insights via knowledge graph integration.