Wednesday, January 26, 2011

Predictive analytics and the power of open standards and cloud computing

Organizations around the globe increasingly recognize the value that predictive analytics offers to their business. The complexity of development, integration, and deployment of predictive models, however, is often considered cost-prohibitive for many projects. In light of mature open source solutions, open standards, and SOA principles we offer an agile model development life cycle that allows us to quickly leverage predictive analytics in operational environments.

Starting with data analysis and model development, you can effectively use the Predictive Model Markup Language (PMML) standard, to move complex decision models from the scientist's desktop into a scalable production environment hosted on the Amazon Elastic Compute Cloud (Amazon EC2).

Expressing Models in PMML

PMML is an XML-based language used to define predictive models. It was specified by the Data Mining Group (DMG), an independent group of leading technology companies including Zementis. By providing a uniform standard to represent such models, PMML allows for the exchange of predictive solutions between different applications and various vendors.

Open source statistical tools such as R can be used to develop data mining models based on historical data. R allows for models to be exported into PMML which can then be imported into an operational decision platform and be ready for production use in a matter of minutes.

On-Demand Predictive Analytics

Amazon EC2 is a reliable, on-demand infrastructure on which we offer the ADAPA Predictive Decisioning Engine based on the Software as a Service (SaaS) paradigm. ADAPA imports models expressed in PMML and executes these in batch mode, or real-time via web-services.

Our service is implemented as a private, dedicated Amazon EC2 instance of ADAPA. Each client has access to his/her own ADAPA instance via HTTP/HTTPS. In this way, models and data for one client never share the same engine with other clients.

Using a SaaS solution to break down traditional barriers that currently slow the adoption of predictive analytics, our strategy translates predictive models into operational assets with minimal deployment costs and leverages the inherent scalability of utility computing.

In summary, ADAPA allows for:
  • Cost-effective and reliable service based on Amazon’s EC2 infrastructure
  • Secure execution of predictive models through dedicated and controlled instances including HTTPS and Web-Services security
  • On-demand computing. Choice of instance type (small, large, extra-large, ...) and launch of multiple instances.
  • Superior time-to-market by providing rapid deployment of predictive models and an agile enterprise decision management environment.
For a practical guide, watch:

Monday, January 24, 2011

Predictions in the Cloud

ADAPA is the first standards-based, real-time predictive decisioning engine available on the market and the first scoring engine accessible on the Amazon Cloud as a service. ADAPA on the Cloud combines the benefits of Software as a Service (SaaS), the scalability of cloud computing and the extensive feature set of ADAPA on Site.

What do you mean by standards-based?

ADAPA executes predictive models represented in PMML (Predictive Model Markup Language). PMML is the standard for representing predictive models currently exported from all major commercial and open-source data mining tools. If you'd like to use ADAPA on the Cloud, but do not want to bother with PMML, contact us. We'll be happy to help you so that you start benefiting from ADAPA right away.




Is ADAPA really fast?


ADAPA is very fast. We recently published a study on the ACM SIGKDD Newsletter in which we show that ADAPA can easily score thousands of transactions per second. In the High-CPU Extra-Large instance, ADAPA can score 300 million transactions per hour. FAST!

What kind of models does it support?

Modeling techniques currently supported are:
  • Neural Networks
  • Association Rules
  • Support Vector Machines
  • Naive Bayes Classifiers
  • Ruleset Models
  • Clustering Models (including Two-Step Clustering)
  • Decision Trees
  • Regression Models (including Cox Regression Models)
  • Scorecards

How about data pre- and post-processing?

ADAPA transforms your raw data into meaningful feature detectors before scoring it. It post-processes the output of your predictive model so that it conforms to your requirements. ADAPA supports all the PMML built-in functions and data manipulations (as well as user defined functions). To learn more about how to represent pre- and post-processing operations in PMML, please take a look at our PMML data manipulation primer or simply contact us.

Can I combine predictive analytics with business rules?


ADAPA provides seamless integration of predictive analytics and rules. Simply put, ADAPA allows data driven insight and expert knowledge to be combined into a single and powerful decision strategy. That is because in addition of a sophisticated predictive analytics engine, ADAPA also incorporates the full functionality of a rules engine.

How do I pay for it? Is it expensive?

Once you sign up for ADAPA on the Cloud through Amazon.com, ADAPA charges show up on your credit card bill. Amazon handles all the billing. You can even use the same account you use to buy books. ADAPA on the Cloud does not cost an arm and a leg. Check out our pricing! And, the best part, you pay only for what you actually use.

Friday, January 14, 2011

Zoey on Model Deployment, PMML, and ADAPA

PMML (Predictive Model Markup Language) is the de facto standard used by all the top analytic vendors (commercial and open-source) to represent data mining models.

When represented in PMML format, a predictive model can be uploaded in ADAPA where it is readily available for execution from anywhere at anytime. ADAPA makes it easy for predictive models to be put to work right away, wherever they are needed, in real-time or batch-mode.

Zementis, the maker of ADAPA, is a company committed to the success of its clients. With PMML and ADAPA, you are on the right track to predictive analytic bliss.

In the video below Zoey takes you in a PMML journey featuring ADAPA and Zementis. Enjoy!

Friday, January 7, 2011

Predictive Analytics with R, PMML, ADAPA, and Excel

PMML (Predictive Model Markup Language) is the standard language used by all the top analytic vendors (commercial and open-source) to represent predictive models. These include IBM/SPSS, SAS, KXEN, TIBCO, STATISICA, R, KNIME, and RapidMiner (for details, see list of PMML-powered tools at DMG.org).

Once a predictive model is exported in PMML format, it can be easily deployed in ADAPA, the predictive decisioning platform from Zementis. ADAPA is PMML-based and is able to upload new and older versions of PMML files and make them available for execution, right away.

Model execution can be performed via the ADAPA Console, Web-services or from within Excel. ADAPA makes predictive models accessible from anywhere at anytime.

See for yourself. Watch our new R to PMML to ADAPA video and learn how to execute your predictive models from within Excel by using ADAPA on the Amazon Cloud.

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