Here is an interview with Ron Ramos, Director , Zementis. Ron Ramos wants to use put predictions for the desktop and servers to the remote  cloud using Zementis ADAPA scoring solution. I have tested the ADAPA solution myself and made some suggestions on tutorials. Zementis is a terrific company with a great product ADAPA and big early mover advantage ( see http://www.decisionstats.com/?s=zementis for the Zementis 5 minute video and earlier interview a few months back with Michael Zeller, a friend, and CEO of Zementis. )

Ajay- Describe your career journey. How would you motivate your children or young people to follow careers in science or at least to pay more attention to science subjects. What advice would you give to young tech entrepreneurs in this recession- the ones chasing dreams on iMobile Applications, cloud computing etc.

Ron- Science and a curious mind go together. I remember when I first met a friend of mine who is a professor of cognitive sciences at the University of California. To me, he represents the quest for scientific knowledge. Not only has he been studying visual space perception, visual control of locomotion, and spatial cognition, but he is also interested in every single aspect of the world around him. I believe that if we are genuinely interested and curious to know how and why things are the way they are, we are a step closer into appreciating and willing to participate in the collective quest for scientific knowledge.

Our current economic troubles are not affecting a single industry. The problem is widespread. So, tech entrepreneurs should not view this recession as target towards technology. It is new technology in clean, renewable fuels which will most probably define what is to come. I am also old enough to know that everything is cyclical and so, this recession will lead us to great progress. iMobile Applications and Cloud Computing are here to stay since these are technologies that just make sense. Cloud Computing benefits from the pay-as-you-go model, which because of its affordability is bound to allow for the widespread use and availability of computing where we have not seen before.

The most interesting and satisfying effect one can have is transformation – do that which changes people’s lives, and your own at the same time.  I like the concept of doing well and doing good at the same time.  My emphasis has always marketing and sales in every business in which I have been involved.  ADAPA provides for delivering on the promise of predictive analytics – decisioning in real-time.

Ajay-  How do you think Cloud Computing will change the modeling deployment market by 2011. SAS Institute is also building a 70 million dollar facility for private clouds. Do you think private clouds with tied in applications would work.

Ron- Model deployment in the cloud is already a reality. By 2011, we project that most models will be deployed in the cloud (private or not). With time though, private clouds will most probably need to embrace the use of open standards such as PMML. I believe open standards such as PMML, which allows for true interoperability, will become widespread among the data mining community; be used in any kind of computing environment; and, be moved from cloud to cloud.

Ajay- I am curious- who is Zementis competition in cloud deployed models. Where is ADAPA deployment NOT suitable for scoring models – what break off point does size of data make people realize that cloud is better than server. Do you think Internal Organization IT Support teams fear cloud vendors would take their power away.

Ron- Zementis is the first and only company to provide a scoring engine on the cloud. Other data mining companies have announced their intention to move to cloud computing environments. The size of the data you need to score is not something that should be taken into account for determining if scoring should be done in the cloud or not. In ADAPA, models can uploaded and managed through an intuitive web console and all virtual machines can be launched or terminated with the click of a mouse. Since ADAPA instances run from $0.99/hour, it can appeal to small and large scoring jobs. For small, the cost is minimal and deployment of models is fast. For large, the cloud offers scalability. Many ADAPA instances can be set to run at the same time.

Cloud computing is changing the way models are deployed, but all organizations still need to manage their data and so IT can concentrate on that. Scoring on the cloud makes the job of IT easier.

Ajay- Which is a case where ADAPA deployment is not suited. Software like from KXEN offers model export into many formats like PMML, SQL, C++ , SAS etc. Do you think Zementis would be benefited if it had such a converter like utility/collection of utilities on its site for the PMML conversion say from SAS code to PMML code etc. Do you think PMML is here to stay for a long time.

Ron- Yes, PMML is here to stay. Version 4.0 is about to be release. So, this is a very mature standard embraced by all leading data mining vendors. I believe the entire community will benefit from having converters to PMML, since it allows for models to be represented by an open and well documented standard. Also, since different tools already import and export PMML, data miners and modelers are the set free to move their models around. True interoperability!

Ajay – Name some specific customer success stories and costs saved.

Ron – As a team, we spent our early development time working on assignments in the mortgage business.  That’s what gave rise to the concept of ADAPA – enabling smart decisions as an integral part of the overall business strategy.  It became obvious to us that we were in fact totally horizontal with application in any industry that had knowledge to be gained from its data.  If only they could put their artful predictive models to work – easily integrated and deployed, able to be invoked directly from the business’ applications using web services, with returned results downloaded for further processing and visualization.  There is no expensive upfront investment in software licenses and hardware; no long-term extended implementation and time-to-production.  The savings are obvious, the ROI pyrotechnic.

Our current users, both enterprise installations and Amazon EC2 subscribers report great results, and for a variety of good reasons we tend to respect their anonymity:

Zementis ADAPA Case Study #1:

Financial Institution Embraces Real-time Decisions.

Decision Management:  A leading financial company wanted to implement an enterprise-wide decision system to automate credit decisions across Retail, Wholesale, and Correspondent business channels. A key requirement for the company’s Enterprise strategy was to select a solution which could execute and manage rules as well as predictive analytic
s on demand and in real-time. With minimal prior automation in place, the challenge was to execute guidelines and pricing for a variety of business scenarios. Complex underwriting and intricate pricing matrices combined present obstacles for employees and customers in correctly assessing available choices from a myriad of financial products. Although embracing a new processing paradigm, the goal for integration of the solution with the existing infrastructure also was to ensure minimal impact to already established processes and to not jeopardize origination volume.

Following a comprehensive market review, the financial institution selected the Zementis ADAPA Enterprise Edition because of its key benefits as a highly scalable decision engine based on open standards. The ADAPA framework, they concluded, ensures real-time execution capabilities for rules and predictive analytics across all products and all business channels.

Working directly with senior business and IT management, Zementis efficiently executed on an iterative deployment strategy which enabled the joint project team to roll out a comprehensive Retail solution in less than three months. Accessed in Retail offices across the country, the ADAPA decision engine assists more than 700 loan officers to determine eligibility of a borrower with the system instantly displaying conditions or exceptions to guidelines as well as precise pricing for each scenario. The Wholesale division exposes the ADAPA decision engine to a large network of several thousand independent brokers who explore scenarios and submit their applications online. While rules were authored in Excel format, a favorite of many business users, predictive models were developed in various analytics tools and deployed in ADAPA via the Predictive Model Markup Language (PMML) standard. Extending its value across the entire enterprise, ADAPA emerged as the central decision hub for vital credit, risk, pricing, and other operational decisions.

Zementis ADAPA Case Study #2:

Delivering Predictive Analytics in the Cloud.

A specialized consulting firm with a focus on predictive analytics needed a cost-effective, agile deployment framework to deliver predictive models to their clients.  The firm specializes in outsourcing the development of predictive models for their clients, using various tools like R, SAS, and SPSS. Supporting open standards, the natural choice was to utilize the Predictive Model Markup Language (PMML) to transfer the models from the scientist’s development environment to a deployment infrastructure.  One key benefit of PMML is to remain development tool agnostic.  The firm selected the Zementis ADAPA Predictive Analytics Edition on the Amazon Elastic Compute Cloud (Amazon EC2) which provides a scalable, reliable deployment platform based on the PMML standard and Service Oriented Architecture (SOA).

With ADAPA, the firm was able to shorten the time-to-market for new models delivered to clients from months to just a few hours.  In addition, ADAPA enables their clients to benefit from a cost-effective SaaS utility-model, whereby the Zementis ADAPA engine is available on-demand at a fraction of the cost of traditional software licenses, eliminating upfront capital expenditures in both hardware and software. The ADAPA Predictive Analytics Edition has given the firm a highly competitive model delivery process and its clients an unprecedented agility in the deployment and integration of predictive analytics in their business processes.

Zementis ADAPA Case Study #3:

Assessing Risk in Real-Time for On-Line Merchant.

An on-line merchant with millions of customers needed to assess risk for submitted transactions before being sent to a credit-card processor.  Following a comprehensive data analysis phase, several models addressing specific data segments were built in a well-know model development platform.  Once model development is complete, models are exported in the PMML (Predictive Model Markup Language) standard. The deployment solution is the ADAPA Enterprise Edition, using its capabilities for data segmentation, data transformation, and model execution. ADAPA was selected as the optimal choice for deployment, not only because PMML-based models can easily be uploaded and are available for execution in seconds, but also because ADAPA Enterprise edition offers the seamless integration of rules and predictive analytics within a single Enterprise Decision Management solution.

ADAPA was deployed on-site and configured to handle high-volume, mission-critical transactions.  The firm not only leveraged the real-time capabilities of ADAPA, but also its integrated reporting framework.  It was very important for the merchant to assess model impact on credit card transactions on a daily basis. Given that ADAPA allows for reports to be uploaded and managed via its web administration console, the reporting team was able to design new reports, schedule them for routine execution, and send the results in PDF format for analysis to the business department with the required agility. During the implementation of the roll-out strategy, the ADAPA web console and its ease of use allowed for effective management of rules and models as well as active monitoring of deployed models and impact of decisions on the business operation.

 

For More on Zementis see here www.zementis.com