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You can note though that in November 2011, we made generally available Spotfire version 4.0. You can tell just by the numbering of this release, this is now 4.5. There's a fair set of improvements here in this release that we're very excited about and I'm eager to walk you through, so why don't we just dive into things. And then, as Brett mentioned, we'll have some time at the end for Q&A. I would also encourage you to submit your questions during the presentation. If you submit them online, I'll do my best to answer the questions in real time as I walk through the different slides or topic areas, so feel free to fire questions over and, where possible, I'll do my best to answer them real time. And what I can't catch in real time, we'll catch at the end of the presentation.So why don't we start off then by looking at version 4.5 through the lens of predictive analytics. We've invested a lot of time and effort in this release to broaden our predictive analytics capabilities. Spotfire's approach towards predictive analytics is quite unique. We really take an ecosystem approach to enable application authors in Spotfire to leverage existing predictive models and statistical investments that they may have made elsewhere. So we want to make it easy for those authors to build very powerful predictive models and statistical features into Spotfire applications that are known for their ease-of-use from the end-user's point of view. So the ultimate goal then of this ecosystem approach is to really enable the broad population of business users who may not have a statistical background to benefit from the applications that the people with statistical training actually have. And by that, those business users can therefore benefit from those predictive analytics that are baked into their applications and make better and more informed decisions faster.
So we've done this historically with S+ and R, and many have appreciated the value of that approach. And what we're really excited to unveil here today is that in 4.5, we've extended our ecosystem now with a new integration for SAS and for MATLAB. So SAS and MATLAB are now integrated with Spotfire, just like R and S+. So in this case, an application author in Spotfire who is already licensed to use SAS and MATLAB separately, so those are separate licenses with Spotfire, that Spotfire application author will continue to develop scripts in those other proprietary systems but they can now embed those proprietary scripts into a Spotfire app, which can then be broadly distributed to a set of business users. So just like we had with our S+ and R integrations, Spotfire version 4.5 is going to now call out also to SAS and to MATLAB, and here we're using our statistical services on server, which is going to manage the activity of the SAS and MATLAB engines. And it will bring back the result sets from those external systems.So from a statistician's point of view, I think this is very exciting and very powerful stuff. You can now leverage your existing SAS and MATLAB investments and make them more broadly available by embedding those scripts into Spotfire. So we actually even in this release provide some sample data functions. These are basically simple tutorials to show how to call SAS or MATLAB from Spotfire. So there's certainly lots of use cases here. But one particular that might be worth calling out would be in the life sciences area, specifically in clinical environments. In clinical, application authors in Spotfire regularly use SAS to extract data and prepare it and then do an initial analysis of that data in SAS. Now with Spotfire 4.5, those same clinicians can essentially use SAS as a data source by pulling data into Spotfire, calling out to SAS and loading existing data preprocessing scripts in SAS and pulling the results back into Spotfire. So again, separate licensing for SAS and MATLAB. But if you have those applications in-house today, you can bring those scripts and embed them into a Spotfire app and then distribute that Spotfire application to consumers who would really benefit from all the decision-making capabilities and insights that would be driven from a stats engine or a MATLAB script, so really excited about this integration here and this broadening of our ecosystem. Read the rest of this transcript for free on seekingalpha.com