Real-time and Big Data Scoring for SAP Users
Zementis ADAPA® for real-time scoring and UPPI™ for big data scoring provide additional value to all your predictive assets. The ADAPA Scoring Engine provides you with powerful execution of predictive analytics from within your SAP application. ADAPA for SAP HANA, for example, makes real-time scoring and predictions available for immediate use where and when you need them the most. For in-database scoring, Zementis offers UPPI for SAP Sybase IQ. It delivers instant and scalable scoring for big data while retaining compatibility with most major data mining tools through PMML, the Predictive Model Markup Language.
Immediate Benefits of Using ADAPA or UPPI
Once a model built in any of the SAP tools, e.g. SAP InfiniteInsight, is saved as a PMML file, it can be directly deployed in ADAPA for real-time scoring or in UPPI for scoring in-database or Hadoop. With ADAPA and UPPI, you can:
- Easily add predictive analytics capabilities to your SAP application
- Benefit from using other PMML-compliant model development tools such as R, SAS, or IBM SPSS
- Deploy your models in minutes, not months (no need for recoding models into production)
- Make one or many predictive models operational at once
- Use multiple models to deploy a model ensemble, segmentation, chaining or cascade
With ADAPA for real-time scoring, you can:
- Produce scores in real-time (using Web Services), on-demand, or batch-mode
- Manage models via Web Services or a Web console
- Tap into all the advantages of cloud computing with ADAPA in the Cloud
With UPPI for big data scoring, you can:
- Execute your models in-database, close to where your data resides with UPPI In-database (Greenplum/Pivotal, IBM Netezza, SAP Sybase IQ, Teradata and Teradata Aster)
- Turn your models into UDFs (User-Defined Functions) and write SQL against UDFs
- Execute your models in Hadoop with UPPI for Hive/Hadoop or Datameer
A Common Industry Standard
PMML allows for the de-coupling of two very important modeling phases: development and operational deployment. With PMML, data scientists can focus on data analysis and model building using best-of-breed model development tools, whereas operational deployment and actual use of the model is made extremely easy and simple with ADAPA and UPPI.
For example, if a data scientist develops a Neural Network Model using SAP Business Objects, all she needs to do to effectively deploy her model operationally is to save it as a PMML file and deploy it either in ADAPA for real-time scoring or in UPPI
for big data scoring.
Once deployed, the model is available for all to use. ADAPA makes models available for scoring on-premise through ADAPA On-site or in the cloud through ADAPA in the Cloud. UPPI makes models available for scoring in-database or in Hadoop.
PMML allows for the model development environment to be used just for that, model development. Scoring, in real-time or for batch jobs, is handled by ADAPA or UPPI.
- ADAPA for SAP: In an article posted on the SAP Developer Network, Albrecht Weiss describes how to integrate predictive models into SAP applications. The article provides step-by-step instructions on how to deploy, integrate and execute predictive models based on SAP and ADAPA. It outlines how you can utilize your predictive models inside your SAP application and begin deriving benefits in just a few minutes. To download the white paper, click HERE.
- SAP PMML: This SAP article hails the PMML standard for its ability to cut the time required to operationally deploy predictive models across an organization. What is the key to this capability? Quite simply: with PMML, there is no need for custom code. Once a data scientist builds a model, he or she can simply export it as a PMML file and importit into ADAPA for real-time scoring. Alternatively, he or she can import the model into UPPI for SAP Sybase IQ in-database scoring. To download the white paper, click HERE.
- SAP BigData Guide: Needless to say, big data and analytics are very hot topics these days. Not surprisingly, SAP recently published its “SAP – Big Data Analytics Guide”, in which you will find a Zementis article entitled “Embracing a Standard for Predictive Analytics” (see page 48). Our article explores the use of PMML for the deployment of predictive analytics in the big data era. To download the white paper, click HERE.
To speak with a Zementis representative and get more information about our predictive analytics solutions, please contact us.