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Tom Sawyer Software Hosts Networking and Service Topology Webinar

Use Data Relationship Visualization and Analysis to Generate More Accurate Understanding of Your Network Operations.

Berkeley, CA, March 27, 2014—Tom Sawyer Software will host a telecommunications and networking webinar on March 27th, 2014 at 9 a.m. Pacific Time to demonstrate how its flagship product, Tom Sawyer Perspectives, can be used by those in the telecom and networking industries to generate more accurate understanding of their network operations.

Those who are assessing and building visualization applications are encouraged to join. Attendees will learn how to use data relationship storage, visualization, and analysis to gain insights from their data and to understand their networks and customers. They will also learn more about Tom Sawyer Perspectives, and its advanced technology and latest features, including the latest support for Neo4j Cypher Query data integration.

See some examples of how network visualization and analysis can be configured and used for:

For the second half of our webinar, we are pleased to invite the Lead Engineer of CenturyLink, David Gunawan, to explain why and how CenturyLink turned to Tom Sawyer Software solutions for their telecom and networking needs.

To register for this webinar, click here.

This presentation will be recorded and made available 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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