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Overview
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 this case 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.
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A new day has come! Zementis is now offering UPPI™ (Universal PMML Plug-in), an amazing PMML-based Scoring Engine for in-database scoring |
Amazing! Why?
For starters, it won't break your budget (feel free to contact us for details). Also, it is simple to deploy and maintain. UPPI was designed from the ground up to take advantage of efficient in-database execution. Last but not least, 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
UPPI seamlessly embeds models within your database. 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 regression equations or other more complex calculations in SQL or stored procedures. PMML and UPPI can easily take care of that.
Modeling techniques currently supported are:
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Neural Networks Support Vector Machines Naive Bayes Classifiers Ruleset Models Clustering Models (including Two-Step Clustering) Decision Trees Regression Models (including Cox Regression Models) Scorecards (including reason codes) Association Rules Multiple Models (model composition, chaining, segmentation, and ensemble, including Random Forest Models) |
In addition to all these predictive techniques, UPPI includes the popular Zementis PMML Converter. This means that it accepts PMML models of all versions (2.0, 2.1, 3.0, 3.1, 3.2, 4.0, and 4.1) generated by any of the major commercial and open source mining tools (SAS, IBM SPSS, STATISTICA, MicroStrategy, Microsoft, Oracle, KXEN, Salford Systems, TIBCO Spotfire, R, KNIME, RapidMiner, etc.). It does not get more universal than this!
UPPI for EMC Greenplum Database
UPPI enables execution of standards-based predictive analytics directly within your Greenplum Database. Each individual server (with a dedicated, independent, high-bandwidth channel connection to local disks) houses a separate instance of UPPI that can take full advantage of these local resources. The net result is the ability to leverage the power of standards-based predictive analytics on a massive scale, right where the data resides.
UPPI for Greenplum not only delivers high performance model execution but it does so in an easy and seamless manner. With a couple of simple steps, PMML models are distributed to all segments of the EMC Greenplum installation and are made available for execution. Each model is presented as a separate SQL function that can be used in any query.
For more details about UPPI for Greenplum Database, feel free to: 1) contact us; 2) download our joint WHITE PAPER; or 3) download the UPPI for EMC Greenplum Database Product Data Sheet.
UPPI for IBM Nettezza
With UPPI, IBM Netezza's existing analytic capabilities are vastly expanded, since it allows for predictive solutions built in any PMML-compliant environment to be put to use right way, close to your data, inside the IBM Netezza appliance.
The IBM Netezza data warehouse appliance is infused with advanced analytics which offer the technology necessary to process massive data and to solve complex problems orders of magnitude faster than typical solutions. With IBM Netezza Analytics, parallelized analytics for data pre- and post-processing, scoring and optimization can exploit the IBM Netezza Asymmetric Massively Parallel Processing (AMPP) architecture to deliver blisteringly fast insightful results.
Since UPPI transforms your complex predictive solutions into SQL functions, these can be readily used in any query and generate business decisions and insights where and when you need them.
For more details about UPPI for IBM Netezza, feel free to: 1) contact us; 2) download the IBM Netezza Analytics Data Sheet; or 3) download the UPPI for IBM Netezza Product Data Sheet.
UPPI for SAP Sybase IQ
With Sybase IQ, UPPI offers Sybase users the best combination of open standards and scalability for the application of predictive analytics.
UPPI for Sybase IQ delivers instant and scalable scoring for big data while retaining compatibility with most major data mining tools through the PMML Standard. Through its versatile use of two essential technologies, the Zementis/Sybase partnership:
- Brings the scalability of Sybase IQ to the execution of predictive analytics
- Supports PMML to avoid time-consuming and expensive one-off predictive analytics projects
- Provides cost effective storage and processing of large volumes of highly granular data that predictive applications often require
- Brings together a 100% standards-based approach to analytics that lowers total cost of ownership and increases reuse control and flexibility for orchestrating critical day-to-day business decisions.
For more details about UPPI for Sybase IQ, feel free to: 1) contact us; 2) watch a Zementis/Sybase webinar which contains an introduction and demo to our products; 3) access the SAP Sybase IQ Marketplace; 4) download our joint WHITE PAPER; 5) download the SAP - Big Data Analytics Guide (look for our article in page 48); or 6) download the UPPI for Sybase IQ Product Data Sheet.
UPPI for Teradata & UPPI for Aster
The latest addition to the growing list of UPPI supported platforms combines our Universal PMML Scoring Engine with the Teradata Integrated Data Warehouse as well as the Teradata Aster discovery platform. UPPI for Teradata and UPPI for Aster combine in-database scoring and data warehousing for rapid, on-the-fly predictive analytics on large volumes of data.
UPPI allows businesses to deploy predictive analytic models on any data across the Teradata Unified Data Architecture™. Analysts can quickly integrate a wide range of analytic models generated by leading commercial and open-source data mining tools into both Teradata and Aster databases for optimal scalability and performance.
Teradata provides best in class analytic and BI solutions that are used to create significant business value. By integrating UPPI into Teradata and Aster databases, Zementis enables clients to immediately leverage the power of predictive analytics on existing platform investments.
For more details about UPPI for Teradata and UPPI for Aster, feel free to: 1) contact us; 2) access the Teradata landing page for UPPI and Zementis which lists the benefits of the Teradata/Zementis partnership; or 3) download the UPPI for Teradata and UPPI for Aster Product Data Sheets.
Start accelerating your scoring today with the Universal PMML Plug-in from Zementis!