The latest version of JMP statistical discovery software, which starts shipping today, embraces users of Microsoft Excel and the R open-source statistical programming language. Business analytics leader SAS also announced today the Nov. 16 release of JMP Pro, a new product that adds capabilities for advanced analytics users who need data mining techniques to build robust predictive models. JMP Pro is part of a broad predictive analytics offering from SAS.
Users of JMP 9 can visualise geographic data on maps, explore risk and what-if scenarios using Excel spreadsheets, and predict product quality with a new Degradation platform. JMP 9 also makes it easier for users to make and share add-ins ‚ custom analytic applications ‚ to extend analytics throughout their organisations and the JMP user community. Add-ins enhance the capabilities of JMP and introduce exciting ways to use JMP’s interactive graphics and statistical tools.
‚JMP 9 is a great piece of software! I am a true fan of JMP and especially JMP 9,‚ said Bill Worley, Technology Leader, The Procter & Gamble Co.
‚Because it easily connects to SAS, Excel and R, JMP 9, will quickly become our customers’ analytic hub. JMP Pro is the product our advanced users have been clamouring for, enabling them to take advantage of techniques like bootstrap forests and boosted trees,‚ said Jeff Perkinson, JMP Product Manager.
With JMP 9, organisations can, Integrate JMP and Excel: Analysts can visually and interactively explore what-if scenarios with the JMP Profiler as Excel calculates the model in the background. The simulator built into the Profiler provides instant insight into the key factors influencing risk.
Map geographic data: Users can uncover patterns in geographic data, choosing from built-in maps, importing images from a Web Map Service and even adding custom shapes, such as a store, factory or campus.
Interface with R: R users can now display analytic results as JMP’s interactive graphics and access JMP and SAS Analytics. R programmers can also build user interfaces to deliver their programs to a broader audience.
Apply powerful data mining and modelling techniques: Users can mine and model data with greater accuracy and flexibility using the revamped neural platform in JMP, or move to JMP Pro for such options as cross-validation and automated handling of missing values. Both the Neural and Partition platforms in JMP Pro use the train, validate and test methodology.
Make and share custom add-ins: Users can create JMP add-ins to enhance the capabilities of JMP and share within their organisations or at www.jmp.com/addins.
Leverage other new capabilities: The new Degradation platform enables engineers to analyse product deterioration data over time to help predict product quality and warranty risk. An updated interface for Microsoft Windows makes each window in JMP independent of others so users can flexibly arrange windows. Users can save histograms in the Distribution platform for the Adobe Flash platform to include in presentations and Web pages.
Other key quotes
‚Version 9 is outrageously wonderful,‚ said Palmer Morrel-Samuels, PhD, University of Michigan School of Public Health, and Employee Motivation & Performance Assessment.
‚I am really impressed with the new features added to JMP 9. This is a great improvement and makes JMP more useful for data mining applications,‚ said Michael Conerly, PhD, Head of Department of Information Systems, Statistics, and Management Science, Culverhouse College of Commerce, University of Alabama at Tuscaloosa.
On bootstrap forests in JMP Pro: ‚Another great example of JMP listening to its customers and responding to their requests. This is another great reason why JMP will continue to be a leader in interactive data analysis,‚ said Nelson Lee Afanador, Senior Project Statistician, Centre for Mathematical Sciences, Merck, Sharp & Dohme Corp.
On the R interface: ‚I’m very positive about the new R interface, which lets me consolidate my analytics work in JMP. I have the power of JMP exploratory tools to begin the analysis. Then, I can bring in specialised, non-traditional Bayesian tools from the R environment. Finally, I can verify convergence and summarise results with JMP analysis and graphics without having to document code from multiple platforms. This is an important addition to JMP,‚ said Dave LeBlond, PhD, Principal Research Statistician, Abbott Global Pharmaceutical R&D.
On JMP add-ins: ‚My initial reaction ‚ WOW! This transforms the ability to distribute JSL [JMP Scripting Language] programs and, therefore, the value that JMP will give to users,‚ said David Burnham, Pega Analytics.
A fully functional 30-day trial of JMP 9 is available as a free download from the JMP website.