Graphs as the front end for machine learning

The O’Reilly Data Show Podcast: Leo Meyerovich on building large-scale, interactive applications that enable visual investigations.

In this episode of the Data Show, I spoke with Leo Meyerovich, co-founder and CEO of Graphistry. Graphs have always been part of the big data revolution (think of the large graphs generated by the early social media startups). In recent months, I’ve come across companies releasing and using new tools for creating, storing, and (most importantly) analyzing large graphs. There are many problems and use cases that lend themselves naturally to graphs, and recent advances in hardware and software building blocks have made large-scale analytics possible.

Starting with his work as a graduate student at UC Berkeley, Meyerovich has pioneered the combination of hardware and software acceleration to create truly interactive environments for visualizing large amounts of data. Graphistry has built a suite of tools that enables analysts to wade through large data sets and investigate business and security incidents. The company is currently focused on the security domain—where it turns out that graph representations of data are things security analysts are quite familiar with.

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