I got a chance to catch up with the folks from IBM/Cognos to discuss their (fairly) recent announcement of a formal OEM relationship with SPSS for PASW Statistics (briefly reviewed here). I discussed their original, less formal, partnership previously. IBM Cognos has a long alliance history with SPSS, often working with them to co-sell into accounts. Feedback from IBM customers was that they wanted more and better statistical analysis in the Cognos platform, hypothesis testing, more advanced correlation and regression analysis, classification and scoring tools etc. Essentially customers were demanding advanced analytics to round out the platform.
IBM sees a distinct separation of algorithms between those that are descriptive algorithms and those that are predictive or more data mining-oriented. Descriptive analytics can typically be used against any kind of data to perform statistical analysis while more predictive ones need the person applying the algorithms to understand how the approach taken by the algorithm intersects with the problem domain so they can find a fit.
While there is clearly …
Copyright © 2009 James Taylor. Visit the original article at First Look – IBM and SPSS.
I got a chance to catch up with the folks from IBM/Cognos to discuss their (fairly) recent announcement of a formal OEM relationship with SPSS for PASW Statistics (briefly reviewed here). I discussed their original, less formal, partnership previously. IBM Cognos has a long alliance history with SPSS, often working with them to co-sell into accounts. Feedback from IBM customers was that they wanted more and better statistical analysis in the Cognos platform, hypothesis testing, more advanced correlation and regression analysis, classification and scoring tools etc. Essentially customers were demanding advanced analytics to round out the platform.
IBM sees a distinct separation of algorithms between those that are descriptive algorithms and those that are predictive or more data mining-oriented. Descriptive analytics can typically be used against any kind of data to perform statistical analysis while more predictive ones need the person applying the algorithms to understand how the approach taken by the algorithm intersects with the problem domain so they can find a fit.
While there is clearly demand for both kinds of algorithm in their Cognos customer base they find that easy add-ons to the Cognos platform tend to sell better than “new” interfaces/skill sets. With this in mind the next major release of IBM Cognos BI will focus on bringing descriptive analytics and the associated graphs and statistics into the standard reporting/dashboard environment. This will have the lowest barrier to adoption both because the user interface is familiar and because these algorithms need not be trained or formally analyzed the way data mining algorithms must be.
The new OEM relationship with SPSS for PASW Statistics will allow users to apply the SPSS statistical libraries directly to data already being handled by Cognos. These routines will be applied to the data and displayed in the standard reports and dashboards with no new UI or expertise requirements.
There is a lot to like in BI / Performance Management tools adding more advanced statistical tools. Analytics, it has been said, simplify data to amplify its value and this is a good thing in a world with too many reports and, increasingly, too many gauges on too many dashboards! I remain intrigued by the potential for Cognos, ILOG and SPSS to interoperate more closely to deliver decision management applications but this is a nice step along the path. There is more on how Cognos and SPSS work together on the IBM site.