Not all analytic tasks are born the same. If one is confronted with massive volumes of data that need to be scored on a regular basis, in-database scoring sounds like the logical thing to do. In all likelihood, the data in these cases is already stored in a database and, with in-database scoring, there is no data movement. Data and models reside together hence scores and predictions flow on an accelerated pace.
So, wouldn't it be great if you could now benefit from the flexibility of a standard such as PMML combined with in-database scoring? Zementis is offering just such a solution. It is called the Universal PMML Plug-in™ and it is truly amazing!
Here is why: for starters, it is simple to deploy and maintain. Our Universal PMML Plug-in was designed from the ground up to take advantage of efficient in-database execution, and, as its name suggests, it is PMML-based. PMML, the Predictive Model Markup Language is the standard for representing predictive models currently exported from all major commercial and open-source data mining tools. So, if you build your models in either SAS, IBM/SPSS, or R, you are ready to start benefiting from in-database scoring right away.
Announcing the Universal PMML Plug-in for Sybase IQ
It is our pleasure to announce, together with Sybase, the availability of the Zementis Universal PMML Plug-In for Sybase IQ 15.4 (Press Release: Sybase Does More Big Data Analytics). This solution allows external predictive models created in the PMML standard to be parsed, ingested and executed In-database in Sybase IQ. This unique capability is extremely appealing to most enterprises that leverage multiple data mining tools or seek to deploy their existing predictive models closer to the data for better performance and broader applicability.
The PMML Plug-in seamlessly embeds models within Sybase IQ. In this way, data scoring requires nothing more than adding a simple function call into your SQL statements. You can score data against one model or against multiple models at the same time. There is no need to code connection weights, regression equations or other more complex calculations in SQL or stored procedures. PMML and our Universal Plug-in can easily take care of that.
PMML execution combined with Sybase IQ existing capabilities for text and multimedia analytics provides enterprises with a breadth of available techniques for analyzing big data.
Sybase/Zementis Webinar: PMML - Accelerating the Time to Value for Predictive Analytics in the Big Data Era
In this webinar, Dr. Alex Guazzelli from Zementis and Courtney Claussen from Sybase, discuss predictive analytics in Healthcare - outlining a use case focusing on heart disease prevention. They examine how the Predictive Model Markup Language (PMML) enables data scientists to use a variety of tools to build their predictive models and then easily deploy them in Sybase IQ using the Universal PMML Plug-in. Once in Sybase IQ, models and predictions benefit from existing capabilities for text and multimedia analytics, which provide a breadth of techniques for analyzing big data.
The introductory piece is followed by a demo of the Zementis Universal PMML plug-in (UPPI) for Sybase IQ that allows in-database scoring of predictive models