Decisionstats Interviews

Here is a list of interviews that I have published- these are specific to analytics and data mining and include only the most recent interviews. If I have missed out any notable recent interview related to analytics and data mining, kindly do let me know. Hat Tip to Karl Rexer, for this suggestion .

Date    Name of Interviewee    Designation and Organization

09-Jun    Karl Rexer                          President, Rexer Analytics
05-Jun    Jim Daves                          CMO, SAS Institute
04-Jun    Paul van Eikeren                 President and CEO, Blue Reference
29-May    David Smith                      Director of Community, REvolution Computing
17-May    Dominic Pouzin                 CEO, Data Applied
11-May    Bruno Delahaye                 VP, KXEN
04-May    Ron Ramos                        Director, Zementis
30-Apr    Oliver Jouve                       VP, SPSS Inc
21-Apr    Fabian Dill                         Co- Founder,
18-Apr    Alicia Mcgreevey                 Head Marketing, Visual Numerics
27-Mar    Francoise Soulie Fogelman    VP, KXEN
17-Mar    Jon Peck                            Principal Software Engineer, SPSS Inc
06-Mar    Anne Milley                        Director of product marketing, SAS Institute
04-Mar    Anne Milley                        Director of product marketing, SAS Institute
03-Feb    Phil Rack                            Creator, Bridge to R,and CEO Minequest
03-Feb    Michael Zeller                     CEO, Zementis
31-Jan    Richard Schultz                   CEO, Revolution Computing
21-Jan    Bob Muenchen                    Author, R for SAS and SPSS Users
13-Jan    Dr Graham Williams           Creator, Rattle GUI for R
05-Jan    Roger Haddad                    CEO, KXEN
26-Sep    June Dershewitz                  VP, Semphonic
04-Sep    Vincent Granville                 Head, Analyticbridge

The URl’s to specific interviews are also in this sheet.

Conferences: KXEN and KDD 09

Here is an announcement regarding one of the foremost conferences on Knowledge Discovery KDD 2009 which is being held in Paris. We have interviewed the joint general chair of the conference, KXEN’s Francoise Soulie Fogelman here at

Indeed given KXEN’s exciting release of their social network analysis software, KSN they are also gold sponsors for the conference. You should view the archives here or read more here

From KXEN’s Press Release-

World’s Best Data Mining Knowledge and Expertise on Show
in Paris at KDD-09

Eminent data mining researchers, academics and practitioners from across the world are honing their presentation skills and charging their laptops in readiness for the industry’s largest and most respected conference, this year being staged for the first time in Europe, in the city of Paris.

The knowledge discovery and data mining 2009 (KDD-09) event will bring together more than 600 specialists, representing the single largest body of expertise in the science and application of data mining technology for industry, government and academia. They will discuss recent discoveries in data mining and share innovative ways of applying the technology in real world business.

Running from the 28th June to 1st July, KDD-09 will feature more than 120 presentations by experts from the US, Europe, Scandinavia and Asia-Pacific. A 20% increase in papers submitted reflects the growing importance of data mining in financially constrained markets. Companies taking part include Orange as a platinum sponsor and Microsoft adCenterLabs and KXEN as gold sponsors. Silver sponsors are Bayesia, Google, HP labs, Pervasive, SAS, Vadis and Yahoo!. Other sponsors include Alberta Center for Machine Learning, Pascal2, Socio Logiciels, Statsoft, Zementis, SFDS, IBM and SIGMOD.

Joint general chair of KDD-09, Francoise Soulie Fogelman, VP Business Development KXEN, says the conference offers a unique chance to see the very latest thinking in data mining. “Some of the best minds from the scientific and business communities will be there, ready and willing to share the results of their cutting edge research and data mining projects with end users. No other industry event offers anything like the depth and breadth of expertise on offer here.”

A particular focus for 2009 will be social network analysis: the discovery and use for competitive advantage of the links between people in social and professional networks. Currently a hot topic among data mining professionals – especially those working in the telecommunications sector – this technique will feature in theoretical and workshop presentations. Details will also be revealed of the world’s first practical applications involving industrial scale volumes of data. Gold sponsor KXEN will present on its booth its recently revealed KSN social network module, helping companies extract valuable new intelligence for better customer acquisition, retention, cross-sell and up-sell campaigns.

Other exhibitors include sponsors as well as Cambridge University Press, Cap Digital, Elsevier, Morgan Claypool Publishers, Oracle, Salford Systems, Springer and Taylor & Francis CRC press.

Also high on the agenda are real-time Web applications for data mining for custom advertising and personalized offers, both seen as crucial to online marketing and sales but both also requiring technologies able to handle very large volumes of data in real time.

Away from science and technology, delegates will also have a chance to sample the best of Paris architecture and hospitality on the evening of 29th June in the main reception room at the exclusive Hotel de Ville – a venue normally reserved for visiting heads of state. A cocktail reception hosted by KXEN will follow presentations, including a welcome from Jean-Louis Missika, the Deputy Mayor of Paris in charge of Innovation, Research and Universities.

There will also be the presentation of awards of the KDD cup by Dr. Isabelle Guyon (ClopiNet). The cup is awarded to the winners of a contest around predicting customer scores from large marketing databases. It, and other prize awards, are being sponsored by the French telecommunications company Orange and Google.

KDD-09 is organized by the data mining special interest group of the Association of Computing Machinery (ACM), the world’s largest educational and scientific computing society. The ACM provides resources that advance computing both as a science and a profession. ACM provides the computing field’s premier digital library and serves its members and the computing profession with leading-edge publications, conferences, and career resources.

More details, program & registration:

About KXEN

KXEN, The Data Mining Automation Company™ delivers next-generation Customer Lifecycle Analytics to enterprises that depend on analytics as a competitive advantage. KXEN’s Data Mining Automation Solution drives significant improvements in customer acquisition, retention, cross-sell and risk applications. Its solution integrates predictive analytics into strategic business processes, allowing customers to drive greater value into their business. Find out more by visiting


Disclaimer- I am a social media consultant to KXEN.

Interview Karl Rexer -Rexer Analytics

Here is an interview with Karl Rexer of Rexer Analytics. His annual survey is considered a benchmark in the data mining and analytics industry. Here Karl talks of his career, his annual survey and his views on the industry direction and trends.

Almost 20% of data miners report that their company/organizations have only minimal analytic capabilities – Karl Rexer


Ajay- Describe your career in science. What advice would you give to young science graduates in this recession? What advice would you give to high school students choosing from science – non science careers?

Karl- My interests in science began as a child. My father has multiple science degrees, and I grew up listening to his descriptions of the cool things he was building, or the cool investigative tools he was using, in his lab. He worked in an industrial setting, so visiting was difficult. But when I could, I loved going in to see the high-temperature furnaces he was designing, the carbon-fiber production processes he was developing, and the electron microscope that allowed him to look at his samples. Both of my parents encouraged me to ask why, and to think critically about both scientific and social issues. It was also the time of the Apollo moon landings, and I was totally absorbed in watching and thinking about them. Together these things motivated me and shaped my world-view.

I have also had the good fortune to work across many diverse areas and with some truly outstanding people. In graduate school I focused on applied statistics and the use of scientific methods in the social sciences. As a grad student and young academic, I applied those skills to researching how our brains process language. But on the side, I pursued a passion for using the scientific method and analytics to address ….well anything I could. We called it “statistical consulting” then, but it often extended to research design and many other parts of the scientific process. Some early projects included assisting people with AIDS outcome studies, psycholinguistic research, and studies of adolescent adjustment.

My first taste of applying these skills outside of an academic environment was with my mentor Len Katz. The US Navy hired us to help assess the new recruits that were entering the submarine school. Early identification of sailors who would excel in this unusual and stressful environment was critical. Perhaps even more important was identifying sailors who would not perform well in that environment. Luckily, the Navy had years of academic and psychological testing on many sailors, and this data proved quite useful in predicting later job performance onboard the submarines. Even though we never got the promised submarine ride, I was hooked on applying measurement, scientific methods, and analytics in non-academic settings.

And that’s basically what I have continued to do – apply those skills and methods in diverse scientific and business settings. I worked for two banks and two consulting firms before founding Rexer Analytics in 2002. Last year we supported 30 clients. I’ve got great staff and they have great quant skills. Importantly, we also don’t hesitate to challenge each other, and we’re continually learning from each other and from each client engagement. We share a love of project diversity, and we seek it out in our engagements. We’ve forecasted sales for medical devices, measured B2B customer loyalty, identified manufacturing problems by analyzing product returns, predicted which customers will close their bank accounts, analyzed millions of tax returns, helped identify the dimensions of business team cohesion that result in better performance, found millions of dollars of B2B and B2C fraud, and helped many companies understand their customers better with segmentations, surveys, and analyses of sales and customer behavior.

The advice I would give to young science grads in this recession is to expand your view of where you can apply your scientific training. This applies to high school students considering science careers too. All science does not happen in universities, labs and other traditional science locations. Think about applying scientific methods everywhere! Sometimes our projects at Rexer Analytics seem far away from what most people would consider “science.” But we’re always asking “what data is available that can be brought to bear on the business issue we’re addressing.” Sometimes the best solution is to go out and collect more data – so we frequently help our clients improve their measurement processes or design surveys to collect the necessary data. I think there are enormous opportunities for science grads to apply their scientific training in the business world. The opportunities are not limited to physics wiz-kids making models for Wall Street trading or computer science students moving to Silicon Valley. One of the best analytic teams I ever worked on was at Fleet Bank in the late 90s. We had an economist, two physicists, a sociologist, a psychologist, an operations research guy, and person with a degree in marketing science. We were all very focused on data, measurement, and analytic methods.

I recommend that all science grads read Tom Davenport’s book Competing on Analytics *. It illustrates, with compelling examples, how businesses can benefit from using science and analytics. Several examples in Tom’s book come from Gary Loveman, CEO of Harrah’s Entertainment. I think that Gary also serves as a great example of how scientific methods can be applied in every industry. Gary has a PhD in economics from MIT, he’s worked at the Federal Reserve Bank, he’s been a professor at Harvard, but more recently he runs the world’s largest casino and gaming company. And he’s famously said many times that there are three ways to get fired at Harrah’s: steal, harass women, or not use a control group. Business leaders across all industries are increasingly wanting data, analytics and scientific decision-making. Science grads have great training that enables them to take on these roles and to demonstrate the success of these methods.

Ajay- One more survey- How does the Rexer survey differentiate itself from other surveys out there?

Karl- The Annual Rexer Analytics Data Miner Survey is the only broad-reaching research that investigates the analytic behaviors, views and preferences of data mining professionals. Each year our sample grows — in 2009 we had over 700 people around the globe complete our survey. Our participants include large numbers of both academic and business people.

Another way our survey is differentiated from other surveys is that each year we ask our participants to provide suggestions on ways to improve the survey. Incorporating participants’ suggestions improves our survey. For example, in 2008 several people suggested adding questions about model deployment and off-shoring. We asked about both of these topics in the 2009 survey.

Ajay -Could you please share some sneak previews of the survey results? What impact is the recession likely to have on IT spending?

Karl- We’re just starting to analyze the 2009 survey data. But, yes, here’s a peek at some of the findings that relate to the impact of the recession:

* Many data miners report that funding for data mining projects can sometimes be a problem.
* However, when asked what will happen in 2009 if the economic downturn continues, many data miners still anticipate that their company/organization will conduct more data mining projects in 2009 than in previous years (41% anticipate more projects in 2009; 27% anticipate fewer projects).
* The vast majority of companies conduct their data mining internally, and very few are sending data mining off-shore.

I don’t have a crystal ball that tells me about the trends in overall corporate spending on IT, Business Intelligence, or Data Mining. It’s my personal experience that many budgets are tight this year, but that key projects are still getting funded. And it is my strong opinion that in the coming years many companies will increase their focus on analytics, and I think that increasingly analytics will be a source of competitive advantage for these companies.

There are other people and other surveys that provide better insight into the trends in IT spending. For example, Gartner’s recent survey of over 1,500 CIOs ( ) suggests that 2009 IT spending is likely to be flat. I’m personally happy to see that in the Gartner survey, Business Intelligence is again CIOs’ top technology priority, and that “increasing the use of information/analytics” is the #5 business priority.

Ajay- I noticed you advise SPSS among others. Describe what an advisory role is for an analytics company and how can small open source companies get renowned advisors?

Karl- We have advised Oracle, SPSS, Hewlett-Packard and several smaller companies. We find that advisory roles vary greatly. The biggest source of variation is what the company wants advice about. Example include:

* assessing opportunity areas for the application of analytics
* strategic data assessments
* analytic strategy
* product strategy
* reviewing software

Both large and small companies that look to apply analytics to their businesses can benefit from analytic advisors. So can open source companies that sell analytic software. Companies can find analytic advisors in several ways. One way is to look around for analytic experts whose advice you trust, and hire them. Networking in your own industry and in the analytic communities can identify potential advisors. Don’t forget to look in both academia and the business world. Many skilled people cross back and forth between these two worlds. Another way for these companies to obtain analytic advice is to look in their business networks and user communities for analytic specialists who share some of the goals of the company – they will be motivated for your company to succeed. Especially if focused topic areas or time-constrained tasks can be identified, outside experts may be willing to donate their time, and they may be flattered that you asked.

Ajay- What made you decide to begin the Rexer Surveys? Describe some results of last year’s surveys and any trends from the last three years that you have seen.

Karl- I’ve been involved on the organizing committees of several data mining workshops and conferences. At these conferences I talk with a lot of data miners and companies involved in data mining. I found that many people were interested in hearing about what other data miners were doing: what algorithms, what types of data, what challenges were being faced, what they liked and disliked about their data mining tools, etc. Since we conduct online surveys for several of our clients, and my network of data miners is pretty large, I realized that we could easily do a survey of data miners, and share the results with the data mining community. In the first year, 314 data miners participated, and it’s just grown from there. In 2009 over 700 people completed the survey. The interest we’ve seen in our research summaries has also been astounding – we’ve had thousands of requests. Overall, this just confirms what we originally thought: people are hungry for information about data mining.

Here is a preview of findings from the initial analyses of the 2009 survey data:

* Each year we’ve seen that the most commonly used algorithms are decision trees, regression, and cluster analysis.
* Consistently, some of the top challenges data miners report are dirty data and explaining data mining to others. Previously, data access issues were also reported as a big challenge, but in 2009 fewer data miners reported facing this challenge.
* The most prevalent concerns with how data mining is being utilized are: insufficient training of some data miners, and resistance to using data mining in contexts where it would be beneficial.
* Data mining is playing an important role in organizations. Half of data miners indicate their results are helping to drive strategic decisions and operational processes.
* But there’s room for data mining to grow – almost 20% of data miners report that their company/organizations have only minimal analytic capabilities.


Karl Rexer, PhD is President of Rexer Analytics, a small Boston-based consulting firm. Rexer Analytics provides analytic and CRM consulting to help clients use their data to make better strategic and tactical decisions. Recent projects include fraud detection, sales forecasting, customer segmentation, loyalty analyses, predictive modeling for cross-sell and attrition, and survey research. Rexer Analytics also conducts an annual survey of data miners and freely distributes research summaries to the data mining community. Karl has been on the organizing committees of several international data mining conferences, including 3 KDD conferences, and BIWA-2008. Karl is on the SPSS Customer Advisory Board and on the Board of Directors of the Oracle Business Intelligence, Warehousing, & Analytics (BIWA) Special Interest Group. Karl and other Rexer Analytics staff are frequent invited speakers at MBA data mining classes and conferences.

To know more do check out the website on


KXEN Case Studies : Financial Sector

Here are the summaries of some excellent success stories that KXEN has achieved working with partners in the financial world over the years.

Fraud Modeling- Disbank (acquired by Fortis) Turkey

1. Dısbank increased the number of identified fraudulent applications by 200% from 7 to 21 per day.

2.More than 50 fraudsters using counterfeit cards at merchant locations or fraudulent applications have been arrested after April 2004 when the fraud modeling system was set.

A large Bank on the U.S. East Coast

1.Response Modeling

Previously it took the modeling group four weeks to build one model with several hundred variables, using traditional modeling tools. KXEN took one hour for the same problem and doubled the lift in the top decile because it included variables that had not been used for this business question before.

2.Data Quality

Building a Cross/Up-sell Model for a direct marketing campaign to high net worth customers, the modelers needed four weeks using 1500 variables. Again it took one hour with KXEN, which uncovered significant problems with some of the top predictive variables. Further investigation proved that these problems were created in the data merge of the mail file and response file, creating several “perfect” predictors. The model was re-run, removing these variables, and immediately put into production.

Le Crédit Lyonnais

1.Around 160 score models now built annually – compared to around 10 previously – for 130 direct marketing campaigns.
2.KXEN software has allowed LCL to drive up response rates, leading to more value-added services for customers.

Finansbank, Turkey

1.Within 4 months of starting the project to combat dormancy using KXEN’s solution, the bank had successfully reactivated half its previously dormant customers as per Kunter Kutluay, Finansbank Director of Marketing and Risk Analytics.

Bank Austria Creditanstalt , Austria

1.Some 4.5 terabytes of data are held in the bank’s operational systems, with a further 2 terabytes archived. Analytical models created in KXEN are automatically fed through the bank’s scoring engine in batches weekly
or monthly depending on the schema.

“But we are looking at a success rate of target customer deals in the area of three to five per cent with KXEN.
Before that, it was one per cent or less. ”
Werner Widhalm, Head of the Customer Knowledge Management Unit.


1.Barclays’ Teradata warehouse holds information on some 14 million active customers, with data
on many different aspects of customer behaviour. Previously, analysts had to manually whittle down several thousand fields of data to a core of only a few hundred to fit the limitations of the modelling process. Now, all of the variables can be fed straight into the predictive model.

Summary– KXEN has achieved tremendous response in all aspects of data modelling in financial sector where time in building, deploying and analyzing model is much more crucial than many other sectors. I would be following this with other case studies on other KXEN successes across multiple domains.

Source –

Disclaimer- I am a social media consultant for KXEN.

Interview Jim Davis SAS Institute

Here is an interview with Jim Davis, SAS Institute SVP and Chief Marketing Officer.

Traditional business intelligence (BI) as we know it is outdated and insufficient-


Jim Davis, SAS Institute..

Ajay -Please describe your career in science to your present position. What advice would you give to young science graduates in this recession? What advice would you give to entrepreneurs in these challenging economic times?
Jim – After earning a degree in computer science from North Carolina State University, I embarked on a career path that ultimately brought me to SAS and my role as senior VP and CMO. Along the way I’ve worked in software development, newspaper and magazine publishing and IT operations. In 1994, I joined SAS, where I worked my way up the ranks from enterprise computing strategist focused on IT issues to program manager for data warehousing to director of product strategy, VP of marketing and now CMO. It’s been an interesting path.

My advice to new graduates embarking on a career is to leave no stone unturned in your search, particularly in this economy, but also consider adding to your skill set. A local example here in the Research Triangle area is at N.C. State University’s Institute for Advanced Analytics, which offers a master’s degree that combines business and analytical skills. These skills are very much in demand. SAS CEO Jim Goodnight helped establish this 10-month degree program where the first 23 graduating all found solid jobs within four months at an average salary of $81,000. Many of this year’s class, facing the worst economy since the Great Depression, have already found jobs. For entrepreneurs today, my advice is simple: make absolutely sure you’re creating a product or service that people want. And especially given the challenging economic environment, resolve to improve your decision making. Regardless of industry or company size, business decisions need to be based on facts, on data, on science. Not on hunches and guesswork. Business analytics can help here.

Ajay – What are some of the biggest challenges that you have faced and tackled as a marketing person for software? What continues to your biggest focus area for this year?

Jim – Among the biggest challenges that the SAS marketing team has worked to overcome is the perception that analytical software – advanced forecasting, optimization and data mining technologies – are way too complex, difficult to use, and only useful to a small band of highly trained statisticians and other quantitative experts, or “quants.” With lots of hard work, we’ve been able to show the marketplace that powerful tools are available in business solutions designed to solve industry issues.

The biggest marketing challenge now is showing the market how SAS offers unique value with its broad and integrated technologies. The industry terminology is confusing with some companies selling Business Intelligence tools that when you scratch the surface are limited to reporting and query operations. Other SAS competitors only provide data integration software, and still others offer analytics. SAS is the only vendor offering an integrated portfolio of these three very important technologies, as well as cross-industry and industry-specific intelligent applications. This combination, which we and others are calling Business Analytics, is a very powerful set of capabilities. Our challenge is to demonstrate the real value of our comprehensive portfolio. We’ll get there but we have some work to do.

Ajay -It is rare to find a major software company that has zero involvement with open source movement (or as I call it with peer-reviewed code). Could you name some of SAS Institute’s contribution to open source? What could be further plans to enhance this position with the global community of scientists?

Jim – SAS does support open source and open standards too. Open standards typically guide open source implementations (e.g., the OASIS work is guiding some of the work in Eclipse Cosmos, some of the JCP standards guide the Tomcat implementation, etc.).

Some examples of SAS’s contributions to open source and open standards include:

Apache Software Foundation – a senior SAS developer has been a committer on multiple releases of the Apache Tomcat project, and has also acted as Release Coordinator.

Eclipse Foundation — SAS developers were among the early adopters of Eclipse. One senior SAS developer wrote a tutorial whitepaper on using Eclipse RCP, and was named “Top Ambassador” in the 2006 Eclipse Community Awards. Another is a committer on the Eclipse Web Tools project. A third proposed and led Eclipse’s Albireo project. SAS is a participant in the Eclipse Cosmos project, with three R&D employees as committers. Finally, SAS’ Rich Main served on the board of directors of the Eclipse Foundation from 2003 to 2006, helping write the Eclipse Bylaws, Development Process, Membership Agreement, Intellectual Property Policy and Public License.

Java Community Process — SAS has been a Java licensee partner since 1997 and has been active in the Java Community Process. SAS has participated in approximately 25 Java Specification Requests spanning both J2SE and J2EE technology. Rich Main of SAS also served on the JCP Executive Committee from 2005 through 2008.

OASIS — A senior SAS developer serves as secretary of the OASIS Solution Deployment Descriptor (SDD) Technical Committee. In total, six SAS employees serve on this committee.

XML for Analysis — SAS co-sponsored XML for Analysis standard with Microsoft and Hyperion.

Others — A small SAS team developed Cobertura, an open source coverage analysis tool for Java. SAS (through our database access team) is one of the top corporate contributors to Firebird, an open source relational database. Another developer contributes to Slide WebDav. We’ve had people work on HtmlUnit (another testing framework) and FreeBSD.

In addition, there are dozens if not hundreds of contributed bug reports, fixes/patches from SAS developers using open source software. SAS will continue to expand our work with and contribute to open-source tools and communities.

For example, we know a number of our customers use R as well as SAS. So we decided to make it easier for them to access R by making it available in the SAS environment. Our first interface to R, which enables users to integrate R functionality with IML or SAS programs, will be in an upcoming version of SAS/IML Studio later this summer. We’re also working on an R interface that can be surfaced in the SAS server or via other SAS clients.

Ajay – What is business intelligence, and business analytics as per you? SAS is the first IT vendor that comes in the non sponsored link when I search for “business intelligence’ in Google. How well do you think the SAS Business Intelligence Platform rates across platforms from SAP, Oracle , IBM and Microsoft.

Jim – Traditional business intelligence (BI) as we know it is outdated and insufficient.

The term BI has been stretched and widened to encapsulate a lot of different techniques, tools and technologies since it was first coined decades ago. Essentially, BI has always been about information delivery, be it in static rows and columns, graphical representations of information, or the modern and hyper-interactive dashboard with dials and widgets.

BI technologies have also evolved to include intuitive ad-hoc query and analysis with the ability to drill down into the details within context. All of these capabilities are great for reacting to business problems after they have occurred. But businesses face diverse and complex problems, global competition grows exponentially, and increasingly restrictive regulations are just around the corner. They need to anticipate and manage change, drive sustainable growth and track performance.

Now they also have to operate in the midst of a ruinous global credit and liquidity crisis. Reactionary decision making is just not working. Now more than ever, progressive organizations are looking to leverage the power of analytics, specifically business analytics. Why? Real business value comes from capitalizing on all available information assets and selecting the best outcome based on every possible scenario.

Proactive evidence-based decisions – not just information delivery – should drive informed decisions. That is business analytics and that is what SAS provides its customers.

Businesses require robust data integration, data quality, data and text mining, predictive modeling, forecasting and optimization technologies to anticipate what might happen, avoid undesired outcomes and course correct.

These capabilities need to be in synch and integrated from the ground up rather than cobbled together through acquisitions. More importantly, they cannot be part of a monolithic platform that requires 2-3 years before any real value is derived.

They must be part of an agile framework that enables an organization to address its most critical business issues now and then add new functionality over time. A business analytics framework — like the one SAS provides — enables strategic business decisions that optimize performance across an organization.

Ajay – For 4 decades SAS Institute created, nurtured and sustained the SAS language, often paying from its pocket for conferences, papers. Till today SAS Language code on your website is free and accessible to all without a registration unlike other software companies. What do you have to say about third party SAS language compilers like “Carolina” and “WPS”

Jim – There is no doubt that much of the power and flexibility behind our framework for business analytics is derived from our SAS language. At its core, the Base SAS language offers an easy-to-learn syntax and hundreds of language elements, pre-built SAS procedures and re-usable functions. Our focus on listening and adapting to customer’s changing needs has helped us, over the years, to sustain and continuously improve the SAS language and the SAS products that leverage it.

Competition comes in many forms and it pushes us to innovate and keep delivering value for our customers. Language compilers or code interpreters like Carolina and WPS are no exception.

One thing that sets SAS apart from other vendors is that we care so deeply about the quality of results.Our Technical Support, Education and consulting services organizations really do partner with customers to help them achieve the best results.

As Anne Milley, SAS’ director of technology product marketing, told DecisionStats this March, customers have varied and specific requirements for their analytics infrastructure. Desired attributes include speed, quality, support, backward and forward compatibility, and others. Certain customers only care about one or two of these attributes, other customers care about more. With our broad and deep analytics portfolio, SAS can uniquely provide the analytics infrastructure that meets a customer’s specific requirements, whether for one or many key attributes. Because of this, an overwhelming majority vote with their pocketbooks to select or retain SAS.

For example, as Anne noted, for some customers with tight batch-processing windows, speed trumps everything. In tests conducted by Merrill Consultants, an MXG program running on WPS runs significantly longer, consumes more CPU time and requires more memory than the same MXG program hosted on its native SAS platform.

At SAS, we provide a complete environment for analytics — from data collection, manipulation, exploration and analysis to the deployment of results. One example of our continuous innovation, and where we are devoting R&D and sales resources, is the SAS In-Database Processing Initiative. Through in-database analytics, customers can move computational tasks (e.g., SAS code, SQL) to execute inside a database. This streamlines the analytic data preparation, model development and scoring processes. Customers needing to leverage their investments in mixed workload relational database platforms will benefit from this SAS initiative. It will help them accelerate their business processes and drive decisions with greater confidence and efficiency.

Ajay – Are you going to move closer for an acquisition? Or be acquired? Which among the existing BI vendors are you most comfortable with in synergy of products and philosophy?

Jim –SAS is in an enviable position as the largest independent provider of business intelligence (BI) software, and the leader in the rapidly emerging field of business analytics, which combines BI with data integration and advanced analytics. We have no plans, nor have had any talks regarding SAS being acquired.

As for SAS acquiring another company, we continuously look for technologies complementary to our wide and deep lineup of business analytics solutions, many of which are targeted at the specific needs of industries ranging from banking, insurance and pharma to healthcare, telecom, manufacturing and government.

Last year, SAS made two acquisitions, IDeaS Revenue Optimization, the premier provider of advanced revenue-management and optimization software for the hospitality industry, and Teragram, a leader in natural language processing and advanced linguistic technology. IDeaS delivers to SAS and our hotel and hospitality customers software sold as a service that meets a critical need in this industry. Teragram’s exciting technology has enhanced SAS’ own robust text mining offerings.

Ajay – Jim Goodnight is a legend in philanthropy, inventions, and as a business leader (obviously he has a fine team supporting him). Who will be the next Jim         Goodnight ?

Jim – I think Jim Goodnight best addressed the question of succession plans at SAS best a few years ago when he noted that the business world often places undue emphasis on the CEO and forgets about the CTO, CMO, CFO and other senior leaders who play a key role in any company’s success. SAS has a very strong executive management team that runs a two billion-dollar software company very effectively. If a “next Jim Goodnight” is needed in the future, SAS will be ready and will continue to provide our customers with the business analytics software they need.


Jim Davis, Senior Vice President and Chief Marketing Officer for SAS, is responsible for providing strategic direction for SAS products, solutions and services and presenting the SAS brand worldwide. He helped develop the Information Evolution Model and co-authored “Information Revolution: Using the information Evolution Model to Grow your Business.” By outlining how information is managed and used as a corporate asset, the model enables organizations to evaluate their management of information objectively, providing a framework for making improvements necessary to compete in today’s global arena.

s285_sas100k_130w SAS ( is the leader in business analytics software and services, and the largest independent vendor in the business intelligence market. Through innovative solutions delivered within an integrated framework, SAS helps customers at more than 45,000 sites improve performance and deliver value by making better decisions faster. Since 1976 SAS has been giving customers around the world The Power to Know®.

Interview Paul van Eikeren Inference for R

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Interview Paul van Eikeren Inference for R

Here is an interview with Paul van Eikeren, President and CEO of Blue Reference, Inc. Paul heads up a startup company addressing the need of information workers to have easier-cheaper-faster access to high-end data mining, analysis and reporting capabilities from software like R, S-plus, MATLAB, SAS, SPSS, python and ruby. His recent product Inference for R has been causing waves within the analytical fraternity across both R users and SAS users, especially given the fact that it is quite well designed, has a great GUI, and is priced rather reasonably.

A few weeks ago, rumour had it the SAS Institute was reportedly buying out the Inference for R product ( Note the merger and acquisition question below)

Rather curious to know about this company, I happened to met Ben Hincliffe at the site which with 5000 members has the largest number of data analytics and many business intelligence members as well). Ben who recently authored a guest post for Sandro at Data Mining Blog then put across my request to interview with Paul, the CEO for Blue Reference. Existing products for Blue Reference include additional analytical packages like Inference for Matlab etc.

Paul is an extremely seasoned person with years in the analytical fraternity and with a Phd from MIT. Here is Paul’s vision on his company and analytics product development.

Ajay: Describe your career journeys. What advice would you give to today’s young people of following careers in science.

Paul: I have been blessed with extremely productive and diversified career journey. After receiving undergraduate and graduate degrees in chemistry, I taught chemistry and carried out research as a college professor for 14 years. During the next 12 years I spend heading R&D teams at three different startup companies focused on the application of novel processing technology for use in drug discovery and development. And using that wealth of acquired experience, I have had the good fortune to successfully co-found and develop with my son Josh, two startup companies (IntelliChem and Blue Reference) directed at the use of informatics to drive more efficient and effective Research, Development, Manufacturing and Operations.

In my journey I have had the opportunity to counsel many young people regarding their career choices. I have offered two principal pieces of advice: one, for the right person, science represents an outstanding opportunity for a productive and satisfying career; and two, a science education provides an outstanding stepping stone to careers in other fields. A study disclosed in a recent Wall Street Journal article (Sarah E. Needleman, “Doing the Math to Find the Good Jobs, 26 January 2009) revealed that mathematicians land the top spot in the new rankings of the best occupations. Science-linked occupations took 7 out of the top 20 spots.

These ratings suggest that the problem solving and innovation aspects of scientific occupations are much less stressful than other occupations, which leads to high job satisfaction. But does one have to be a genius to have a successful career in science? An interesting read on this subject is the book by Robert Weisberg (Creativity: Beyond the Myth of the Genius) in which he dispels the myth of the genius being the results of a genetic gift. Weisberg argues, convincingly, that a genius exhibits three elements: (1) a basic intellectual capacity; (2) a high level of motivation/determination, which enables the genius to remain focused; and (3) immersion in their chosen field, typically represented by over 10,000 hours of study/practice/experience. It turns out that the latter element is the principal differentiator, and fortunately, it is something one has control over.

Ajay: Describe the journey that Blue Reference has made leading to its current product line, including Inference for R.

Paul: The Inference product suite represents a natural extension beyond the Electronic Laboratory Notebook (ELN) product we developed at our previous company, IntelliChem. ELNs are used by scientists and technicians to document research, experiments and procedures performed in a laboratory. The ELN is a fully electronic replacement of the paper notebook. IntelliChem (sold to Symyx in 2004) was a leader in deployment of ELNs at global pharmaceutical companies.

After seeing the successful adoption of ELNs in the laboratory, we saw an opportunity to improve upon the utility of ELN documents and the data contained therein. Essentially, we developed Inference to be a platform for enabling MS Office documents with powerful, flexible, and transparent analytic capabilities – what we call “dynamic documents” or “document mashups”. Executable code from high-level scripting languages like R, MATLAB, and .NET, is combined with data and explanatory text in the document canvas to transform it from a static record into an analytic application.

The pharmaceutical industry, in cooperation with the FDA, has begun to look at ways to implement quality by design (QbD) practices as an alternative to quality by end-testing. QbD comprises a systematic application of predictive analytics to the drug R&D process such that development timelines and costs are reduced while drug safety and efficacy is improved.

Statistical modeling and analysis plays a key role in QbD as a tool for identifying critical quality attributes and confining their variability to a specified design space. Dynamic documents fit nicely into this paradigm, and we’re currently using Inference as a platform to develop an enterprise solution for QbD. You can visit for more information about our QbD product.

Along the way, we recognized the need for Inference outside of the pharmaceutical industry. The Inference for R, Inference for MATLAB, and Inference for.NET versions are meant to serve users of these technical computing languages who have analysis, publishing, reporting, collaboration, and reproducible research needs that are best served by a document centric environment. By using Microsoft Word, Excel and PowerPoint as the “front end,” we can serve the the 500 million users that use Microsoft Office as their principal desktop productive application.

Ajay: What is the pricing strategy for Inference for Matlab and Inference for R – and how do you see the current recession as an opportunity for analytical products.

Paul: Our strategy is to reach out to the market Microsoft Office users that would benefit from easy access to datamining and predictive analytics capabilities within their principal desktop productivity tool. Accordingly, we have offered the Inference product at the low price of $199 for a single user/one year subscription. Additionally, because it is implemented on top of an existing installation of Microsoft Office, the cost of training, support and maintenance are expected to be minimal.




Ajay: Your product seems to follow a nice fit where both open source as well as proprietary packages from Microsoft( .Net) are working together to give the customer a nice solution. Do you believe it is possible that big companies and big open source communities can work together to create some software rather than just be at loggerheads.

Paul: Absolutely. We’re seeing momentum build for open source analytic solutions as the economy impacts companies, both small and large. We saw this take place in the back office with implementation of Linux and Apache Web servers, and now we’re starting to see it in the front office. Smart IT teams are looking for creative ways to stretch their resources, forcing them to look beyond established, but expensive, software products.

We’ve encountered concrete evidence of this in the financial industry. Fresh on the heels of the credit crisis, investment banks and hedge funds have begun to realize that their risk models and supporting software infrastructure are inadequate. In response, quantitative finance and risk analysts are increasingly turning to the open source R statistical computing environment for improved predictive analytics.

R has a core group of devotees in academia that drive innovation, making it a comprehensive venue for development of leading-edge data analysis methods. In order to leverage these tools, banks need a way

for R to play nicely with their existing personnel and IT infrastructure. This is where Inference for R produces real value. It transforms MS Office into platform for the development, distribution, and maintenance of R based quantitative tools – enabling production level predictive analytics.

Commercial distributions of R address issues of scalability and support, which might otherwise be subjects of concern. For example, REvolution Computing distributes an optimized, validated and supported distribution of R, providing peace of mind to corporate IT. REvolution also offers Enterprise R, a distribution of R for 64-bit, high performance computing.

Ajay: Please name any successful customer testimonials for Inference for R.

Paul: We have been working with the director of quantitative analytics at a large international bank. He reported that he has successfully distributed R applications to his team of research analysts and portfolio managers based on Inference in Excel. Use of this strategy eliminated the need to code complex models in Visual Basic for applications, which is time consuming and error prone.

Ajay: Also are there any issues with licensing and IP for mixing open source code and proprietary code.

Paul- The licensing issues with open source R pertain to distributing R. There are no licensing restrictions in using R. Accordingly, we do not distribute R. Rather, our customers install R separately and Inference recognizes the installation.

Ajay: So R is free and I can get Open Office for free. What are the five specific uses where Inference for R can score an edge over this and make me pay for the solution.

Paul: R is free, and many R enthusiasts would argue that all you need for R is a Linux operating system like Ubuntu, a text editor such as Emacs, and R’s command line interface. For some highly-skilled R users this is sufficient; for the new and average R user this is a nightmare.

Many people think that the largest fraction of the cost of implementing new software is the cost of the license. In actuality, and especially in the corporate world, it is the cost of training, user support, software maintenance, and the costs of switching the user base to the new software. Free open source software does not help here. Hence there is a strong ROI argument to be made to build new software application on top of existing systems that have worked well.

Additionally, successful implementation of open source software like R requires a baseline of integration with existing systems. The fact is that Microsoft operating systems dominate the business world, as does Microsoft Office. If one is serious about using R to address the analytic needs of big business, tight integration with these systems is imperative.

Ajay: Any plans for a web hosted SaaS version for Inference for R soon?

Paul: The natural progression of Inference for R to SaaS will coincide with the next release of Office (Office 2010 or Office 14), which we expect to be largely SaaS enabled.

Ajay: Name some alliances and close partners working with Blue Reference

– and what we can expect from you in terms of product launches in 2009.

Paul: We have created a product development consortium in partnership involving ‘top ten’ global pharmaceutical companies The consortium is guiding the development of an enterprise solution for Quality by Design (QbD), using Inference for R as the platform.

We are working with several consulting firms specializing in IT solutions for specialized markets like risk management and predictive analytics.

We are also working with several technology partners who have complementary products and where integration of their products with Inference provides clear and significant value to customers.

Ajay: Any truth to the rumors of an acquisition by a BIG analytics company?

Paul: Our business strategy is centered on growth through partnerships with others. Acquisition is one means to execute that strategy.

Ajay: How do you see this particular product (for R) shaping up down the years.

Paul: R’s success can be attributed, in large part, to the support of its loyal open source community. Its enthusiastic use in academia bodes very well for its growth as a cutting-edge analytics tool. It is just a matter of time before commercial analytic solutions powered by R become de rigueur. We’re happy to be at the tip of the spear.

Ajay: Any Asia plans for Blue Reference or are you still happy with the Oregon location. How do you plan to interact with graduate schools and academia for your products.

Paul: Although we don’t have a major private university in our backyard, Oregon State University has opened a campus here. And, we’ve been in dialogue with the global Academic community from day one. Over 100 academic institutions around the world use Inference through our academic licensing program. Inference is a great tool for preparing dynamic lessons and publishing reproducible research.

Our Central Oregon location is home to a growing high-tech sector that we’ve been a part of for decades. We’ve had success building large and profitable companies here. Bend attracts Silicon Valley types who come here for vacation and don’t want to leave – they just can’t seem to resist the quality of life and bountiful recreational opportunities that this area offers. It’s a good mix of work and play.


Paul van Eikeren is President and CEO of Blue Reference, Inc. He is responsible for guiding the strategic direction of the company through novel products and services development, partnerships and alliances in the realm of application of informatics to faster-cheaper-better research, development, manufacturing and operations. Van Eikeren is a successful serial entrepreneur, which includes the co-founding of IntelliChem with his son Josh and its ultimate sale to Symyx Technologies. He has headed up R&D at several startup companies focused on drug discovery and development including Sepracor Inc., Argonaut Technologies, Inc, and Bend Research, Inc. He served as Professor of Chemistry and Biochemistry at Harvey Mudd College of Science and Engineering. He is author/co-author and inventor/co-inventor in over 50 scientific articles and patents directed at the application of chemical, biochemical and computational technologies. Van Eikeren holds a BA degree in Chemistry from Columbia University and a PhD in Chemistry from MIT.bluereference-logo

Ajay- To know more I recommend checking out the free evaluation at especially if you need to rev up your MS office Installation with greater graphics and analytics juice.

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