Sophisticated Statistical Software Becomes Accessible with Analytical Tools Statistical software has proven to hold tremendous value for companies seeking a competitive advantage. Decision-makers and researchers in many disciplines rely on this
business intelligence software to maximize quality, speed time to market, reduce defects, optimize operations and allocate resources. But statistical software is difficult for non-experts to use, severely limiting its broad-scale value to the enterprise. In most cases, only a few experts know how to use the applications, and their ability to deliver statistical discoveries and intelligence to every corner of the enterprise is limited. To enable organizations to achieve the potential benefits of statistical software, additional analytical tools may be necessary. Today, enterprises around the world fill that need with software from Spotfire.
Spotfire® Analytic Applications Enhance Statistical Software Spotfire allows experienced and non-experienced users alike to reap the benefits of statistical software. Spotfire provides a self-configuring data environment based on imported information that allows users to visualize and interact with their data. Users can intuitively interact with data to more quickly see trends, interpret outliers and discover unanticipated relationships in statistical data. Users can perform queries at will—no help needed from IT—and get immediate results. That makes Spotfire ideal for front line operational management, where decisions must be made with speed and confidence. Because Spotfire software is built on an open architecture, it can be easily customized for any number of tasks, including
enterprise risk management in financial companies;
life science informatics for pharmaceutical companies;
yield and defect analysis initiatives in production scenarios; and
data mining applications in many enterprises worldwide.
Analytical Guides Offer Assistance in use of Statistical Software Guided Analytics™, a feature unique to Spotfire, enables experienced users to easily develop statistical models for non-experts. With these guides, individuals without advanced knowledge of statistics can still use them to solve problems related to their work. With Guided Analytics, advanced users can record their exploration one step at a time and package the results with annotations, allowing everyone in the organization to benefit from their knowledge. Guided Analytics can also be used to relieve statisticians of more routine activities so they can spend more time on high-value statistical tasks.
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