DataMontage is a Java class library and set of software applications that displays information-dense arrays of timelines and graphs; interactive displays help analysts review and interpret complex, time-oriented data quickly and consistently
DataMontage Data Visualization Software information-dense interactive displays help analysts review and interpret complex, time-oriented data quickly and consistently
SAN MATEO, Calif., December 14, 2011 - Stottler Henke Associates, Inc. (www.stottlerhenke.com) today announced the immediate availability of an enhanced version of its DataMontage™ software for rapid visual analysis of complex, time-oriented data. DataMontage 3.0 introduces new features that enable analysts to visualize data more flexibly and interactively.
is a Java class library and set of software applications that displays information- dense arrays of timelines and graphs that can be stacked vertically or arranged in rows and columns, so users can see important patterns in large, multivariate datasets that cannot be seen using traditional data displays. DataMontage offers unparalleled control over each display's layout, appearance and interactivity. For example, flexible specification of the color, shape, and size of graph and timeline symbols enable DataMontage displays to encode multiple attributes in high-dimensional data and highlight significant or unexpected data points. Colored lines and regions in graphs help users compare actual data to constant or time-varying reference values and ranges. Powerful zooming, scrolling, graph filtering, and data point highlighting features enable analysts to analyze subsets of the data from multiple analytical perspectives in order to discern significant relationships and trends, interpret their significance, and discover causal relationships quickly and easily.
U.S. Macroeconomic Summary, 1993 to 2005. Red vertial line is Sep 2001
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DataMontage enhances data review, decision support, and real-time monitoring systems for diverse applications in which professionals must rapidly detect temporal patterns spanning many continuous and discrete variables and events in order to interpret complex data and reach time- critical decisions. Applications include patient care, outcomes research, drug safety surveillance, market analysis, engineering analysis, manufacturing production scheduling and process control, system monitoring and problem diagnosis, and the planning, execution monitoring, and after- action review of projects, programs, and missions.