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The beauty of diversity in analytics

I recently gave a short talk at Predictive Analytics World in DC called “Analytics: The Beauty of Diversity.” Having just met with a wonderful group of customers a few weeks ago on the JMP Customer Advisory Board, I noticed that some of the same themes appeared: diversity of perspectives and how that fuels innovation, the need for multiple paradigms, and the importance of visualization — both data visualization for exploration and analysis, as well as information visualization for sharing results.

Analytics is cross-disciplinary, so it reflects a rich diversity of perspectives — statistics (composed of many subdisciplines itself), measurement theory, econometrics, psychometrics, operations research and many more disciplines. Whole new fields have formed — some from a few decades ago like behavioral economics and behavioral finance to, more recently, network science and econophysics. Network science I had heard of, but econophysics is one I just came across in Everything Is Obvious Once You Know the Answer by Duncan Watts (very enjoyable book).

Back to diversity. The customers on our advisory board have diverse backgrounds and areas of expertise—as we would expect among users of a product that has evolved over more than two decades. While they love JMP, JMP alone didn’t meet all their needs (what product does? And please don’t say spreadsheets!). Two of my favorite quotes from the board meetings: “JMP helps you think in data” and “The learning curve is shockingly fast.” JMP allows them to do a great deal; it also allows them to call out to SAS, R and other tools based on their needs and skills.

Many are still unaware that JMP is a full SAS client, enabling you to do amazing things with the vast and highly scalable data manipulation and analysis capabilities SAS has. Many are also still unaware that JMP allows you to call out to R.

To help get the word out, I’d like to give a plug for an upcoming workshop JMP is sponsoring at Predictive Analytics World in Chicago on June 24: JMP, R, and SAS: The Beauty of Multiple Paradigms. Matt Flynn, who will be conducting this workshop, has given some interesting talks on this topic resulting in some very helpful resources:

At Predictive Analytics World in New York last October, Matt presented Creating More Analytical Bandwidth with R. Following that, Matt gave a talk on Finite Mixtures Using JMP, SAS and R Together at SAS’ Analytics 2011 in Orlando last October. He gave similar talks at The 46th Actuarial Research Conference and more recently at Insurance and Financial SAS User Group (IFSUG). Other useful things he’s contributed include:

  • Multiple Methods in JMP to Interact with R
  • Automating JMP via Scripting tools and MS Windows COM
  • Enabling Powerful Analytics with JMP® Scripting for SAS® and R Users
  • Similar resources can be found on the JMP File Exchange (new files are added all the time, so check back often). You might also want to view these demos:

    • Making JMP Your Analytic Hub
    • JMP and R
    • We hope you will take advantage of these resources to create more analytic bandwidth yourself.

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