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Tom Sawyer Software CEO Gives Graph Visualization and Analysis Talk

Brendan Madden Gives Presentation to SF Data Mining Meetup

Berkeley, CA, March 18, 2013— Brendan Madden, the CEO of Tom Sawyer Software, will give a technical talk to the SF Data Mining Meetup group on Monday, March 18th at 6:30 p.m. at Trulia's San Francisco office. The talk will focus on "Graph Visualization and Analysis."

Data relationships are everywhere, among employees in an organization, devices in a network, genes in a biochemical pathway, and producers and consumers in a supply chain. Graphs provide a fundamental means to help represent relationships inherent in data. Using Tom Sawyer Perspectives, Brendan will demonstrate various advanced graph visualization, layout, and analysis techniques developed over many years of practical experience. He will also discuss some of the software engineering challenges that we face in the era of Big Data.

Among the important features Brendan plans to demonstrate are viewing, editing, and interaction methods. Further, he'll show various scalable, incremental and constraint-based layout algorithms and their usage in various industries, and demonstrate problems and solutions in graph analysis. Brendan will also discuss data representation, federated data integration, model management, rules, filters, and synchronized views of data in both desktop and web architectures.

The presentation will be recorded and made available for later viewing for those who are unable to attend.

About Tom Sawyer Software

Tom Sawyer Software is the leading provider of software and services that enable organizations to build highly scalable and flexible graph and data visualization and analysis applications. These applications are used to discover hidden patterns, complex relationships, and key trends in large and diverse datasets. Tom Sawyer Software serves clients with needs in link analysis; network topology; architectures and models; schematics and maps; and dependencies, flows, and processes. We help clients federate and integrate their data from multiple sources and build the graph and data visualization applications that are critical to analyzing and gaining insight into their data.

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