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Spotfire for Academics

Spotfire DecisionSite® is a premier Guided Analytic application for the rich and interactive visualization and analysis of data from a wide variety of research efforts. Scientists from over 200 academic and government institutions use DecisionSite to uncover hidden relationships, test hypotheses, and apply their scientific knowledge and intuition to generate new hypotheses. DecisionSite can be used equally by novices and experts, offering a range of capabilities to support new applications that include guided workflows and links to industry standard statistics packages.

Research conducted at universities and institutes worldwide has been critical for the development of thousands of breakthrough discoveries. The tremendous flood of available data and the multidisciplinary nature of academic research make Spotfire DecisionSite® analytics products ideal for quickly accessing, interpreting and sharing research results with colleagues from different disciplines around the world.

Scientists use DecisionSite analytics across broad areas that also include gene expression analysis, proteomics analysis, and chemical structure and property analysis. Key to the value of DecisionSite is the ability to configure new analyses to meet current and future research projects aligning both data access with objectives of the project.

For academics, Spotfire offers a competitive pricing model and an invaluable platform for meeting their current and future needs for exploration and discovery. Contact one of our sales representatives to get pricing or to get more information.

"While it has been said that one tool cannot do everything, Spotfire DecisionSite comes very close. In our lab, we have found DecisionSite to have the flexibility to work with all of our data sources. When analyzing microarray data, it is necessary to be able to incorporate new methods, technologies and information quickly. For example, the power of using DecisionSite to unify new annotation information from both internal and external sources has been critical to our lab for understanding experimental results."
- Sean Prool, Data Analyst, University of Washington

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