Oakland, CA, March 22, 2004—Tom Sawyer® Software, a leading provider of high-performance graph visualization, layout and analysis solutions, today released Tom Sawyer (TS) Analysis, Version 6.0, a sophisticated component technology that enables software developers to simplify and automate the analysis of complex systems found in applications ranging from biology and transportation to networking and intelligence.
TS Analysis lets developers integrate algorithmic analysis within their applications and perform highly sophisticated analytic queries on relational information models. The software facilitates clustering, structured graph traversal, dependency analysis, network flow analysis, impact analysis, cycle detection, process analysis, and other complex queries on the relational model. TS Analysis products are available for Java and C++.
"Searching for answers and solutions within complex systems can be time-consuming and counterproductive without the right tools," said Brendan P. Madden, Tom Sawyer's president and CEO. "TS Analysis helps you quickly find information that is implicitly inherent in data that is not readily apparent. As a result, you are provided with information, patterns and trends to help you make better-informed and faster decisions."
New features included in version 6.0 are clustering, XML integration, undirected edges and reachable nodes. Clustering classifies items into disjoint or separate sets in order to group relational entities. In the intelligence industry, for example, clusterings or groupings of connected telephone numbers within a data source of thousands of telephone numbers can be revealed quickly and accurately. Tom Sawyer Analysis integrates algorithmic analysis within the application and performs highly sophisticated analytic queries, establishing associations between telephone numbers that are not obvious in the original format (i.e., spreadsheets or printouts).
XML integration exchanges and integrates data between Tom Sawyer products and other applications quickly and easily, and vice versa. Undirected edges can be specified to connect nodes bidirectionally in a graph, resulting in a larger set of situations to model. Reachable nodes weigh the edges to more efficiently control the size of the search range.
TS Analysis can be bundled with the Tom Sawyer Visualization product line (Graph Editor Toolkit and Graph Editor Layout) to maximize the benefits of a combined high-performance algorithmic and visual analysis solution. The combined algorithmic and visual queries enable a new class of applications that help developers with efficient and faster decision making.
The Tom Sawyer Visualization product line manages, reveals and displays graphical and customized views of relational data, immediately identifying relationships, connections and emerging patterns within the data. Visualization products are available for Java, MFC, ActiveX and .Net.
"When the products are seamlessly bundled, organizations have the benefits of both excellent algorithmic and visual analysis," said Madden. "This combination results in accurate correlations that quickly establish associations and significantly expedite the decision-making process.
"Our products empower organizations and businesses to explore patterns and relationships, and discover information underlying their relational data sources to ultimately gain insights that were previously unclear or unknown."
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.View All Press Releases