Synergies and value proposition between IBM SPSS and Zementis ADAPA

The ADAPA Decision Engine provides additional value to all your predictive assets. It is complimentary to IBM SPSS Modeler and IBM SPSS Statistics, since it extends these modeling environments into the IT operational domain.

ADAPA is compatible with Modeler and Statistics through PMML, the Predictive Model Markup Language, which is the de facto standard to represent predictive models. PMML allows for models to be developed in one application and deployed on another, as long as both are PMML-compliant.

Immediate benefits of using ADAPA

Once a model built in any of the IBM SPSS tools is saved as a PMML file, it can be directly uploaded in ADAPA. With ADAPA, you can:

• Execute your models independently of the IBM SPSS model development tool
• Overcome any speed limitations
• Dramatically lower your infrastructure cost
• Tap into all the advantages of cloud computing with ADAPA on the Cloud (IBM SmartCloud or Amazon EC2)
• Produce scores in real-time (using Web Services or Java API), on-demand, or batch-mode
• Execute your models directly from Excel, by using the ADAPA Add-in for Excel
• Benefit from using other PMML-compliant model development tools such as R, KNIME, or SAS
• Deploy your models in minutes, not months (no need for recoding models into production)
• Manage models via Web Services or a Web console
• Upload one or many models into ADAPA at once
• Use rules to implement model segmentation
• Benefit from the seamless integration of business rules and predictive models

IBM SPSS PMML support

IBM SPSS offers vast support for PMML through IBM SPSS Modeler (formerly known as Clementine) and Statistics. Both systems allow users to export a multitude of models in PMML (for details, click HERE). IBM products such as DB2 Intelligent Miner and ILOG JRules also offer support for PMML.

A common industry standard

PMML allows for the de-coupling of two very important modeling phases: development and operational deployment. With PMML, scientists can focus on data analysis and model building using the best of breed model development tools, whereas operational deployment and actual use of the model is made extremely easy and simple with ADAPA.

For example, if a data mining scientist develops a decision tree model using IBM SPSS Modeler, all he/she needs to do to effectively deploy his/her model operationally is to save it as a PMML file and uploaded it in ADAPA. Once in ADAPA, the decision tree model is available for all to use, directly by business users and applications. It may be used by a business user directly from within Excel to score customers for a marketing campaign.

By doing that, PMML allows for the model development environment to be used just for that, model development. Scoring, real-time or batch-mode from anywhere and at anytime, is handled by ADAPA.