Category: Interviews

Interview Alison Bolen SAS.com

My biggest editing soapbox right now is to encourage brevity. We’re so used to writing white papers, brochures and magazine articles that the concept of throwing down 200 words on a topic from your day is a very foreign exercise. –

 

Alison Bolen  Editor-in-Chief sascom

Here is an interview with Alison Bolen the editor-in-chief of SAScom , online magazaine of the SAS Institute. Alison talks of the challenges in maintaining several of the topmost expertise blogs on SAS ,Business Analytics and Business Intelligence.

Ajay- Describe your career in the technology writing and publishing area. What advice would you give to young Web publishers and content producers just entering the job market in this recession? Describe your journey within SAS.

Alison- I started at SAS in 1999 as a summer student working as a contributing editor for SAS Communications magazine. Before the end of the year, I came on full time and soon transitioned to writing and editing for the Web. At that time, we were just developing the strategy for the customer support site and e-newsletters. As the first editor for the SAS Tech Report, I led marketing efforts that brought in 15,000 opt-in subscribers within six months. A year later, I switched to writing and editing customer success stories, which I enjoyed doing until I took on the role of Editor-in-Chief for sascom® magazine in 2006. We started our blogging program in 2007, and I’ve been actively involved in coaching SAS bloggers for the past two years.

Outside of SAS, I’ve written for Southwest Hydrology Magazine, the Arizona Daily Star and other regional papers. My bachelor’s degree is in magazine journalism and my master’s degree is in technical and business communications.

If you’re just beginning your career as a writer, start a blog and stick with it. There’s no better way to get daily writing practice, learn the basics of search engine optimization and start to understand what works online.

Ajay www.SAS.com/Blogs has many, many blogs by experts, RSS feeds and even covers the annual SAS conference with video content. In terms of social media adaptation, what prompts you to stay ahead of the competition in ensuring marketing and technical communications for brand awareness?

What do you think are the basics of setting up a social media presence for a company, regardless of size?

Alison- Social media excites me because you can cut through the clutter and be real. Our new business forecasting blog by Michael Gilliland is a good example. Teaching people how to forecast better is his top priority, not selling software. Our overarching goal for the blogging program is similar: to share and develop expertise.

We’re big advocates of aligning your social media presence with existing marketing goals. We have a few grass-roots teams interested in social media, and we have a director-level Marketing 2.0 Council that our Social Media Manager Dave Thomas leads to determine broad guidelines and strategies. But the overarching concept is to look at the goals of your individual marketing campaigns first, and then determine which social media channels might help you reach those goals.

Most of all, take off your marketing hat when you enter the blog, network or forum. Social media consists of individuals, for the most part, and not companies, so be sure to offer value as a colleague and build relationships.

Ajay- I noticed that SAS.com/ Blogs are almost ad free – even of SAS products – apart from a simple banner of the company. Was this a deliberate decision, and if so, why?

Alison- Yes, most of the SAS blogs were intentionally created to help establish the individual blogger’s expertise – not to promote SAS products or services. One positive side effect is that SAS – by extension – builds credibility as well. But we really do see the blogs as a place to discuss concepts and ideas more than products and tools.

Ajay- What distinguishes good writers on blogs from bad writers on blogs? How about some tips for technical blog writing and especially editing (since many writers need editors more than they realize)?

Alison- The best blog writers know how to simplify and explain even the most mundane, everyday processes. This is true of personal and technical blog writing. If you can look at your life or your work and see what piece of it others would find interesting or want to know more about – and then know how to describe that sliver of yourself clearly – you have what it takes to be a good blogger. Chris Hemedinger does this well on The SAS Dummy blog.

My biggest editing soapbox right now is to encourage brevity. We’re so used to writing white papers, brochures and magazine articles at SAS that the concept of throwing down 200 words on a random topic from your day is a very foreign exercise. You have to learn how to edit your day – not just your writing – to find those topics and distill those thoughts into quick snippets that keep readers interested. And don’t forget it’s okay to have fun!

Ajay- I balance one blog, small consulting assignments and being a stay-at-home dad for an 18-month old. How easy is it for you to balance being editor of sascom, given the huge content your sites create, and three kids? Does working for SAS and its employee-friendly reputation help you do so?

Alison- I couldn’t balance work and kids without a whole lot of help from friends and family, that’s for sure. And the employee-friendly benefits help too. The biggest benefit is the cultural mindset, though, not any individual policy. My boss and my boss’ boss are both working mothers, and they’re balancing the same types of schedules. There’s an understanding about finding a healthy work-life balance that permeates SAS from top to bottom.

Ajay- As a social media consultant it is a weekly struggle for me to convince companies to discontinue registration for normal content (but keep it for special events), use a lot more video tutorials and share content freely across the Web. Above all, convincing busy senior managers to start writing a blog or an article is an exercise in diplomacy itself. How do you convince senior managers to devote time to content creation?

Alison- In a lot of areas, the content is already being created for analyst presentations, press interviews and consulting briefs. It’s really a matter of understanding how to take those existing materials and re-present them in a more personal voice. Not everyone can – or should – do it. You have to decide if you have the voice for it and whether or not it will bring you value beyond what you’re getting through your existing channels.

Ajay- Any plans to visit India and have a SAS India blogathon?

Alison- Alas, not this year.

Maybe I will visit Cary,NC then 🙂


Bio:
Alison Bolen is the Editor of sascom magazine and the sascom voices blog, where SAS experts publish their thoughts on popular and emerging business and technology trends worldwide. Since starting at SAS in 1999, Alison has edited print publications, Web sites, e-newsletters, customer success stories and blogs.

Alison holds a bachelor’s degree in magazine journalism from Ohio University and a master’s degree in technical writing from North Carolina State University.

1) Describe your career in the technology writing and publishing area. What advice would you give to young Web publishers and content producers just entering the job market in this recession? Describe your journey within SAS.

I started at SAS in 1999 as a summer student working as a contributing editor for SAS Communications magazine. Before the end of the year, I came on full time and soon transitioned to writing and editing for the Web. At that time, we were just developing the strategy for the customer support site and e-newsletters. As the first editor for the SAS Tech Report, I led marketing efforts that brought in 15,000 opt-in subscribers within six months. A year later, I switched to writing and editing customer success stories, which I enjoyed doing until I took on the role of Editor-in-Chief for sascom® magazine in 2006. We started our blogging program in 2007, and I’ve been actively involved in coaching SAS bloggers for the past two years.

Outside of SAS, I’ve written for Southwest Hydrology Magazine, the Arizona Daily Star and other regional papers. My bachelor’s degree is in magazine journalism and my master’s degree is in technical and business communications.

If you’re just beginning your career as a writer, start a blog and stick with it. There’s no better way to get daily writing practice, learn the basics of search engine optimization and start to understand what works online.
2) SAS.com/Blogs has many, many blogs by experts, RSS feeds and even covers the annual SAS conference with video content. In terms of social media adaptation, what prompts you to stay ahead of the competition in ensuring marketing and technical communications for brand awareness?

What do you think are the basics of setting up a social media presence for a company, regardless of size?

Social media excites me because you can cut through the clutter and be real. Our new business forecasting blog by Michael Gilliland is a good example. Teaching people how to forecast better is his top priority, not selling software. Our overarching goal for the blogging program is similar: to share and develop expertise.

We’re big advocates of aligning your social media presence with existing marketing goals. We have a few grass-roots teams interested in social media, and we have a director-level Marketing 2.0 Council that our Social Media Manager Dave Thomas leads to determine broad guidelines and strategies. But the overarching concept is to look at the goals of your individual marketing campaigns first, and then determine which social media channels might help you reach those goals.

Most of all, take off your marketing hat when you enter the blog, network or forum. Social media consists of individuals, for the most part, and not companies, so be sure to offer value as a colleague and build relationships.


3) I noticed that SAS.com/ Blogs are almost ad free – even of SAS products – apart from a simple banner of the company. Was this a deliberate decision, and if so, why?

Yes, most of the SAS blogs were intentionally created to help establish the individual blogger’s expertise – not to promote SAS products or services. One positive side effect is that SAS – by extension – builds credibility as well. But we really do see the blogs as a place to discuss concepts and ideas more than products and tools.
4) What distinguishes good writers on blogs from bad writers on blogs? How about some tips for technical blog writing and especially editing (since many writers need editors more than they realize)?

The best blog writers know how to simplify and explain even the most mundane, everyday processes. This is true of personal and technical blog writing. If you can look at your life or your work and see what piece of it others would find interesting or want to know more about – and then know how to describe that sliver of yourself clearly – you have what it takes to be a good blogger. Chris Hemedinger does this well on The SAS Dummy blog.

My biggest editing soapbox right now is to encourage brevity. We’re so used to writing white papers, brochures and magazine articles at SAS that the concept of throwing down 200 words on a random topic from your day is a very foreign exercise. You have to learn how to edit your day – not just your writing – to find those topics and distill those thoughts into quick snippets that keep readers interested. And don’t forget it’s okay to have fun!
5) I balance one blog, small consulting assignments and being a stay-at-home dad for an 18-month old. How easy is it for you to balance being editor of sascom, given the huge content your sites create, and three kids? Does working for SAS and its employee-friendly reputation help you do so?

I couldn’t balance work and kids without a whole lot of help from friends and family, that’s for sure. And the employee-friendly benefits help too. The biggest benefit is the cultural mindset, though, not any individual policy. My boss and my boss’ boss are both working mothers, and they’re balancing the same types of schedules. There’s an understanding about finding a healthy work-life balance that permeates SAS from top to bottom.

6) As a social media consultant it is a weekly struggle for me to convince companies to discontinue registration for normal content (but keep it for special events), use a lot more video tutorials and share content freely across the Web. Above all, convincing busy senior managers to start writing a blog or an article is an exercise in diplomacy itself. How do you convince senior managers to devote time to content creation?

In a lot of areas, the content is already being created for analyst presentations, press interviews and consulting briefs. It’s really a matter of understanding how to take those existing materials and re-present them in a more personal voice. Not everyone can – or should – do it. You have to decide if you have the voice for it and whether or not it will bring you value beyond what you’re getting through your existing channels.

7) Any plans to visit India and have a SAS India blogathon?

Alas, not this year.

Interview Karim Chine BIOCEP (Cloud Computing with R)

Here is an interview with Karim Chine of http://www.biocep.net/

Working with an R or Scilab on clusters/grids/clouds becomes as simple as working with them locally-

Karim Chine, Biocep.

Ajay- Please describe your career in the field of science. What advice would you give to young science graduates in this recession.

Karim- My original background is in theoretical Physics, I did my Master’s thesis at the Ecole Normale’s Statistical Physics Laboratory where I worked on phase separation in two-dimensional additive mixtures with Dr Werner Krauth. I came to computer science after graduating from the Ecole Polytechnique and I spent two years at TELECOM ParisTech studying software architecture and distributed systems design. I worked then for the IBM Paris Laboratory (VisualAge Pacbase applications’ generator), Schlumberger (Over the Air Platform and Web platform for smartcards personalization services), Air France (SSO deployment) and ILOG (OPL-CPLEX-ODM Development System). This gave me the intense exposure to real world large-scale software design. I crossed the borders of cultural, technical and organizational domains several times and I worked with a broad palette of technologies with some of the best and most innovative engineers. I moved to Cambridge in 2006 and I worked for the European Bioinformatics Institute. It’s where I started dealing with the integration of R into various types of applications. I left the EBI in November 2007. I was looking for an institutional support to help me in bringing into reality a vision that was becoming clearer and clearer about a universal platform for scientific and statistical computing. I failed in getting that support and I have been working on BIOCEP full time for most of the last 18 months without being funded. Few days of consultancy given here and there allowed me to keep going. I spent several weeks at Imperial College, at the National Center for e-Social Sciences and at Berkeley’s department of statistics during that period. Those visits were extremely useful in refining the use cases of my platform. I am still looking for a partner to back the project. You asked me to give advice. The unique advice I would give is to be creative and to try again and again to do what you really want to do. Crisises come and go, they will always do and extreme situations are part of life. I believe hard work and sincerity can prevail anything.

Ajay- Describe BIOCEP’s scope and ambition.

What are the current operational analytics that can be done by users having data.

Karim- My first ambition with BIOCEP is to deliver a universal platform for scientific and statistical computing and to create an open, federative and collaborative environment for the production, sharing and reuse of all the artifacts of computing. My second ambition is to enhance dramatically the accessibility of mathematical and statistical computing, to make HPC a commonplace and to put new analytical, numerical and processing capabilities in the hands of everyone (open science).

The Open source software Conquest has gone very far. Environments like R or Scilab, technologies like Java, Operating Systems like Linux-Ubuntu, and tools like OpenOffice are being used by millions of people. Very little doubt remains about the OSS’s final victory in some domains. The cloud is already a reality and it will take computing to a whole new realm. What is currently missing is the software that, by making the Cloud’s usage seamless, will create new ecosystems and will provide rooms for creativity, innovation and knowledge discovery of an unprecedented scale.

BIOCEP is one more building block into this. BIOCEP is built on top of R and Scilab and anything that you can do within those environments is accessible through BIOCEP. Here is what you have uniquely with this new R/Scilab-based e-platform:

– High productivity via the most advanced cross-platform workbench available for the R environment.

– Advanced Graphics: with BIOCEP, a graphic transducer allows the rendering on client side of graphics produced on server side and enables advanced capabilities like zooming/unzooming/scrolling for R graphics. a client side mouse tracker allows to display dynamically information related to the graphics and depending on coordinates. Several virtual R Devices showing different data can be coupled in zooming/scrolling and this helps comparing visually complex graphics.

– Extensibility with plug-ins: new views (IDE-like views, analytical interfaces…) can be created very easily either programmatically or via drag-and-drop GUI designers.

– Extensibility with server-side extensions: any java code can be packaged and used on server side. The code can interact seamlessly with R and Scilab or provide generic bridges to other software. For example, I provide an extension that allows you to use openoffice as a universal converter between various files formats on server side.

– Seamless High Performance Computing: working with an R or Scilab on clusters/grids/clouds becomes as simple as working with them locally. Distributed computing becomes seamless, creating a large number R and Scilab remote engines and using them to solve large scale problems becomes easier than ever. From the R console the user can create logical links to existing R engines or to newly created ones and use those logical links to pilot the remote workers from within his R session. R functions enable using the logical links to import/export variables from the R session to the different workers and vice versa. R commands/scripts can be executed by the R workers synchronously or asynchronously. Many logical R links can be aggregated into one logical cluster variable that can be used to pilot the R workers in a coordinated way. A cluster.apply function allows the usage of the logical cluster to apply a function to a big data structure by slicing it and sending elementary execution commands to the workers. The workers apply the user’s function to the slices in parallel. The elementary results are aggregated to compose the final result that becomes available within the R session.

– Collaboration: your R/scilab server running in the cloud can be accessed simultaneously by you and your collaborators. Everything gets broadcasted including Graphics. A spreadsheet enables to view and edit data collaboratively. Anyone can write plug-ins to take advantage of the collaborative capabilities of the frameworks. If your IP address is public, you can provide a URL to anyone and get him connect to your locally running R.

– Powerful frameworks for Java developers: BIOCEP provides Frameworks and tools to use R as if it was an Object Oriented Java Toolkit or a Web Toolkit for R-based dynamic application.

– Webservices for C#, Perl, Python users/developers: Most of the capabilities of BIOCEP including piloting of R/Scilab engines on the cloud for distributed computing or for building scalable analytical web application are accessible from most of the programming languages thanks to the SOAP front-end.

– RESTful API: simple URLs can perform computing using R/Scilab engines and return the result as an XML or as graphics in any format. This works like google charts and has all the power of R since the graphic is described with an R script provided as a parameter of the URL. The same API can be exposed on demand by the workbench. This allow for example to integrate a Cloud-R with Excel or OpenOffice. The workbench works as a bridge between the cloud and those applications.

– Advanced Pooling framework for distributed resources: useful for deploying pools of R/scilab engines on multi nodes systems and get them used simultaneously by several distributed client processes in a scalable/optimal way. A supervision GUI is provided for a user friendly management of the pools/nodes/engines.

– Simultaneous use of R and Scilab: Using java scripting, data can be transferred from R to Scilab and vice versa.

Ajay- Could you tell us about a successful BIOCEP installation and what it led to? Can BIOCEP be used by the rest of the R community for other packages? What would be an ideal BIOCEP user /customer for whom cloud based analytics makes more sense ?

Karim- BIOCEP is still in pre-beta stage. However it is a robust and polished pre-Beta that several organizations are already using. Janssen Pharmaceutica is using it to create and deliver statistical applications for drug discovery that use R engines running on their backend servers. The platform is foreseen there as the way to go for an ultimate optimization of some of their data analysis pipelines. Janssen’s head of statistics said to be very much interested in the capabilities given by BIOCEP to statisticians to create their own analytical User Interfaces and deliver them with their models without needing specific software development skills. Shell is creating BIOCEP-based applications prototypes to explore the feasibility and advantages of migrating some of Shell’s applications to the Cloud. One group from Shell Global Solutions is planning to use BIOCEP for running scilab in the cloud for Corrosion simulation modeling. Dr Ivo Dinov’s team at UCLA is studying the migration of some the SOCR applications to the BIOCEP platform as plug-ins and extensions. Dr Ivo Dinov also applied for an important grant for building DISCb (Distributed Infrastructure for Statistical Computing in Biomedicine). If the grant application is successful, BIOCEP will be the backbone at software architecture level of that new infrastructure. In cooperation with the Institute of Biostatistics, Leibniz University of Hannover, Bernd Bischl and Kornelius Rohmeyer have developed a framework to user friendly R-GUIs of different complexity. The toolkit uses BIOCEP as an R-backend since release 2.0. Several small projects have been implemented using this framework and some are in production such as an application for education in biostatistics at the University of Hannover. Also the ESNATS project is planning to use the BIOCEP frameworks. Some development is being done at the EBI to customize the workbench and use it to give to the end user the possibility to run R and Bioconductor on the EBI’s LSF cluster.

I’ve been in touch with Phil Butcher, Sanger’s head of IT and he is considering the deployment of BIOCEP on Sanger’s systems simultaneously with Eucalyptus. The same type of deployment has been discussed with the director of OMII-UK, Neil Chue Hong. BIOCEP’s deployment is probably going to follow the deployment of the Eucalyptus System on NGS. Tena Sakai deployed BIOCEP at the Ernest Gallo Clinic and Research Centre and he is currently exploring the usage of the R on the Cloud via BIOCEP (Eucalyptus / AWS). The platform has been deployed by a small consultancy company specializing in R on several London-based investment banks’ systems. I have had a go ahead form Nancy Wilkins Diher (Director for Science Gateways, SDSC) for deploying on TeraGrid, a deployment on EGEE has been discussed with Dr Steven Newhouse (EGEE Technical Director). Both deployments are in standby at the moment.

Quest Diagnostics is planning to use BIOCEP extensively. Sudeep Talati (University of Manchester) is doing his Master’s project on BIOCEP. He is supervised by Professor Andy Brass and he is exploring the use of a BIOCEP-based infrastructure to deliver microarray analysis workflows in a simple and intuitive way to biologists with and without the Cloud. In Manchester, Robin Pinning (e-Science team leader, Research Computing Services) has the deployment of BIOCEP on Manchester’s research cluster on his agenda…

As I have said, anything that you can do with R including installing, loading and using any R package is accessible through BIOCEP. The platform aims to be universal and to become a tool for productivity and collaboration used by everyone dealing with computing/analytics with or without the cloud.

The Cloud whether it is public or private will be generalized and everyone will become a cloud user in one way or another

Ajay- What motivated you to build BIOCEP and mash cloud computing and R. What scope do you see for cloud computing in developing countries in Asia and Africa?

Karim– When I was at the EBI, I worked on the integration of R within scalable web applications. I explored and tested the available frameworks and tools and all of them were too low level or too simple to answer the problem. I decided to build new frameworks. I had the opportunity to be able to stand on the shoulders of giants.

Simon Urbanek’s packages already bridged the C-API of R with Java reliably. Martin Morgan’s RWebsevices package defined class mappings between R types, including S4 classes, and java.

Progressively R became usable as a Java object oriented toolkit, then as a Java Server. Then I built a pooling framework for distributed resources that made it possible for multiple clients to use multiple R engines optimally.

I started building a GUI to validate the server’s increasingly sophisticated API. That GUI became progressively the workbench.

When I was at Imperial, I worked with the National Grid Service team at the Oxford e-Research Centre to deploy my platform on Oxford’s core cluster. That deployment led to many changes in the architecture to meet all the security requirements.

It was obvious that the next step was to make BIOCEP available on Amazon’s Cloud. Academic Grids are for researchers and the cloud is for everyone. Making the platform work seamlessly on EC2 took few months. With the cloud came the focus on collaborative features (collaborative views, graphics, spreadsheets…).

I can only talk about the example of a country I know, Tunisia, and I guess some of this applies to Asian Countries. Even if the broadband is everywhere today and is becoming accessible and affordable by a majority of Tunisians, I am not sure that the adoption of the cloud would happen soon.

Simple considerations like the obligation to pay for the compute cycles in dollars (and not in dinars) are a barrier for adoption. Spending foreign currencies is subject to several restrictions in general for companies and for individuals; few Tunisians have credit cards that can be used to pay Amazon. Companies would prefer to buy and administer their own machines because the cost of operation and maintenance is lower in Tunisia than it is in Europe/US.

Even if the cloud would help in giving Tunisian researchers access to affordable Computing cycles on demand, it seems that most of them have learned to live without HPC resources and that their research is more theoretical and less computational than it could be. Others are collaborating with research groups in Europe (France) and they are using those European groups’ infrastructures.

Ajay- How would BIOCEP address the problem of data hygiene, data security and privacy. Is encrypted and compressed data transfers supported or planned?

Karim- With BIOCEP, a computational engine is exposed as a distributed component via a single mono-directional HTTP port. When you run such an engine on an EC2 instance you have two options:

  • 1/ totally sandbox the machine (via the security group) and leave only the SSH port open.
  • Private Key authentication is required to access the machine. In this case you use an SSH Tunnel (created with a tool like Putty for example) which allows you to see the engine as if it was running on your local machine on a port of your choice, the one specified for creating the Tunnel.
  • When you start the Virtual Workbench and connect in Http mode to your local host via the specified port, you are effectively connecting to the EC2-R engine. 100% of the information exchanged between your workbench and the engine, including your data, is ciphered thanks to the SSH tunnel.
  • The virtual workbench embeds JSCH and can create the Tunnel for you automatically. This mode doesn’t allow collaboration since it requires the private key to let the workbench talk to the EC2 R/Scilab engine.
  • 2/ tell the EC2 machine at startup (via the “user data”) to require specific credentials from the user. When the machine starts running, the user needs to provide those credentials to get a session ID and to be able to pilot a virtual EC2 R/Scilab engine. This mode enables collaboration. The client (workbench/scripts) connects to the EC2 machine instance via HTTP (will be HTTPS in a near future).

Ajay- Suppose I have 20 gb per month of data and my organization decided to cut back on the number of annual expensive software. How can the current version of BIOCEP help me do the following?

Karim– Ways BIOCEP can help you right now.

1) Data aggregation and Reporting in terms of spreadsheet, presentation and graphs

  • BIOCEP provides a highly programmable server side spreadsheet.
  • It can be used interactively as a view of the workbench and simple clicks allow the transfer of data form cells to R variables and vice versa. It can be created and populated from R (console / scripts).
  • Any R function can be used within dynamically computed cells. The evaluation of those dynamic cells is done on server side and can use high performance computing functions. Macros allow adding reactivity to the spreadsheets.
  • A macro allows the user to execute any R code in response to a value change of an R variable or of the content of a range within a spreadsheet. Variables docking macros allow the mirroring of R variables of any type (vectors, matrixes, data frames..) with ranges within the spreadsheet in Read/Write mode

. Several ready-to-use User Interface components can be created and docked anywhere within the spreadsheet. Those components include

  • an R Graphics viewer (PDF viewer) showing Graphics produced by a user-defined R script and reactive on user-defined variables and cell ranges changes,
  • customizable sliders mirroring R variables,
  • Buttons executing user-defined R code when pressed,
  • Combo boxes mirroring factor variables ..

The spreadsheet-based analytical user interface can pilot an R running at any location (local R, Grid R, Cloud R…). It can be created in minutes just by pointing, clicking and copy/pasting.

Cells content+macros+reactive docked components can be saved in a zip file and become a Workbench plug-ins. Like all BIOCEP plug-ins, the spreadsheet-based GUI can be delivered to the end user via a simple URL. It can use a cloud-R or a local R created transparently on the user’s machine.

2) Build time series models, regression models

BIOCEP’s workbench is extensible and I am hoping that contributors will soon start writing plug-ins or converting available GUIs to BIOCEP plug-ins in order to make the creation of those models as easy as possible.

Biography-

Karim Chine
Karim chine graduated from the French Ecole Polytechnique and TELECOM ParisTech. He worked at Ecole Normale Supérieure-LPS (phase separation in two-dimensional additive mixture), IBM (VisualAge Pacbase), Schlumberger (Over the Air Platform and Web platform for smartcards personalization services), Air France (SSO deployment), ILOG (OPL-CPLEX-ODM Development System), European Bioinformatics Institute (Expression Profiler, Biocep) and Imperial College London-Internet Center (Biocep). He contributed to open source software (AdaBroker) and he is the author of the Biocep platform. He currently works on the seamless integration of the new platform within utility computing infrastructures (Amazon EC2), its deployment on Grids (NGS) and its usage as a tool for education and he tries to build collaborations with academic and industrial partners.

You can view his resume here http://www.biocep.net/scan/CV_Karim_Chine_June_2009.pdf

Interview Gary Cokins SAS Institute

Here is an interview with Gary Cokins , a well respected veteran of the Business Intelligence industry working with the SAS Institute. Gary has just launched his sixth book (wow!) and the gentlemen he is , he agreed to answer these questions en route to his constant traveling.Gary is the expert on performance measurement so we decided to quiz him a bit on this.

CIO’s need to shift their mindset from a technical one to a managerial one.- Gary Cokins, SAS Institute

Gary_Cokins_SAS_05

Ajay -Gary, please describe your career journey from a freshman in college to your position today. What are the key items of advice that you would give to high school students to encourage taking science careers in this recession?

COKINS: I have been very fortunate. After receiving my MBA in 1974 from the Northwestern University Kellogg Graduate School of Management, I worked in industry for ten years. I had the luck of being a financial controller at Fortune 100 corporation division and then becoming operations manager at the same location. I then had to “eat the financial data I was serving,” and it was a true wake-up call – much of the information was at best useless and at worst misleading. Later with Deloitte I was trained on the theory of constraints (TOC) methodology which indicted cost accounting as “enemy number one of productivity.” I learned about the shortcomings with how accountants make assumptions.

In 1988, when Professor Kaplan struck an exclusive relationship with KPMG Peat Marwick, I was recruited to KPMG with about three others with similar operational backgrounds as I to implement activity based cost management (ABC/M) systems but with using an ABC/M modeling software tool. I learned from experience. Four years later, my mentor Bob Bonsack, who had moved on from Deloitte to Electronic Data Systems (EDS) recruited me to head EDS’ cost management consulting. With about fifteen consultants, I was exposed to over a hundred implementations of cost systems. It was there that I experimented with creating a two day “ABC/M rapid prototyping” method that was radically different from the multi-month approach. By starting with a quick vision of what their ABC/M system would look like, companies could iteratively re-model to the level of detail, granularity, and accuracy needed to support analysis and decisions. It did not initially require a huge system, which was why some ABC/M system implementations got into trouble. My major self-realization is that costing is accomplished by modeling cost consumption relationships – an insight that continues to evade many accountants.

When I began to see the application of strategy maps and the balanced scorecard, more light bulbs went off in my brain. I then began truly seeing the organization as a “system” where all the performance improvement methodologies and core processes are inter-connected. I realized that the technologies are no longer the impediment because they are proven. The obstacle is the organization’s thinking – and the mindset of senior management who is presumably doing the leading.

My advice to high school students take your studies more seriously than you even imagine, and spend less time text-messaging everyone you know and focus on the more meaningful relationships. They will eventually be your friends rather than just acquaintances. And take math courses!

Ajay- So what exactly do you do at SAS? And name some interesting anecdotes that led to a lot of value as well as fun for both your company and clients. How does Gary spend his daily day at SAS Institute?

COKINS: My primary role with SAS is to create and deliver thought leadership content about Performance Management leveraging business analytics. I present webinars and write articles, blogs, presentations and also books. For the last four years I have averaged visiting roughly 40 international cities where SAS offices are located to present seminars and meet SAS customers to educate them on the concepts and benefits from Performance Management methodologies.

Recent examples of having fun and providing value to organizations involved providing expert advice to the International Monetary Fund (IMF) in Washington DC and the European Patent Office (EPO) in Brussels. The IMF is at the beginning of implementing an activity based cost management (ABC/M) system whereas the EPO is completing their ABC/M system design. Both organizations were seeking tips for success and pitfalls to avoid. One of my major recommendations was to not under-estimate the natural resistance to change of managers and employees. That is, they need to focus much more on getting their buy-in than worrying if the system is perfect. The value to them is realizing that Performance Management methodologies are much more social than technical.

Regarding my daily activities, when I am not traveling, I am mainly reading articles written by other experts or journalists and then translating my relevant takeaways into content that I can educate others with. I also respond to questions and requests both internally within SAS and externally from customers, management consultants, and university faculty.

Ajay- When you were a young employee, what was the toughest challenge that you faced? What was your worst mistake and how did you overcome it? What lessons did you learn from it?

COKINS: In my first few years in business following my university graduation, my toughest challenge was persuading my supervisors, usually older men than I, to accept my new ideas. I have always been a creative thinker, almost a dreamer; and I was not accustomed to the resistance that managers have to innovations, particularly those suggested by young inexperienced employees fresh from their university schooling.

My worst mistake was developing a computer program that automatically suggested treasury cash balance transfers to optimize the corporate cash management system of my first employer, a large Fortune 100 corporation. My computer program was basically replacing the decisions made by the corporate cash manager and part of his job. I overcame this disappointment by learning what needs the corporate cash manager did have and developing a different computer program that solved his needs. With its success, he eventually accepted the first computer program.

My lesson was one should first understand what people may want rather than trying to impose on them what you think they need without involving them.

Ajay- Looking back on your distinguished career, what project are you proud of the most? What project would you do over again if given the chance?

COKINS: In 1973 I became a financial controller of a large division of another Fortune 100 manufacturer. I created a rolling financial planning and forecast software program, using pre-spreadsheet software from a mainframe (years before personal computers and Excel). The program modeled product line sales forecasts by month and integrated both the income statement and balance sheet. It became a valuable tool for the executive team to suggest and immediately see varying sales levels as a “what if” scenario builder to calculate the different profit and working capital results. The executive team marveled at how analytical software, in contrast to our transactional ERP-like system, could make sense of the complexity of our operations with thousands of products and customers.

Regarding a project that fell short of expectations, I actually did get a chance to do it over again. As a consultant with Deloitte, I lead a project designing and implementing an activity based cost management (ABC/M) system using the client’s general ledger accounting software. It took many months, and when finished it was too complex for the client to fully understand. Several years later with a similar project I applied a rapid prototyping with iterative re-modeling approach that involved the company’s managers from the first day. (I mentioned this approach in my reply to the first question.) We completed the ABC/M system in just a few weeks, and everyone understood it and also how to interpret the information for analysis and decisions. I have since been a proponent of this type of rapid learning and system design approach.

Ajay- What do people do for fun at SAS Institute do when not creating or selling algorithms? How is SAS reaching out to other members of the analytics community in terms of basic science and development?

COKINS: SAS employees are inspired by our CEO, Dr. Jim Goodnight, who founded SAS roughly 35 years ago. Dr. Goodnight loves solving problems of all flavors. For fun, but also part of our jobs, SAS employees search for problems that only computer software can solve.

SAS’ offerings evolve by listening to our customers, who are typically scientists, researchers, and business analysts. Drug development and marketing analysts are examples. Our customers are our “community.” We motivate them, with formal methods of collecting input from them, to share with us enhancements to our future versions of our software.

Ajay- Describe your new book on Performance Management from the point of a beginner. Assume that I am a college student who does not know why I should read it. Then assume that I am a CIO and have little time to read it. What is in it for a CIO?

COKINS: This is my sixth book I have written. My first four books were about activity based cost management (ABC/M) and the last two about Performance Management. What is different about this second book is it immediately clarifies the confusion and ambiguity about what Performance Management is and is not. It is also written in a humorous and simplified way with lots of analogies and metaphors, such as all of the Performance Management methodologies integrated together like gears in an automobile engine and with a GPS for predictive navigation and dashboards for feedback. Beginners perceive each methodology, such as a balanced scorecard or customer relationship management system, are stand-alone tools. There is synergy when they are integrated.

cokins3

CIOs have similar needs. They need to shift their mindset from a technical one to a managerial one. Just a few chapters from this book can help CIOs see the broad picture of how all of their organizations processes fit together, and how they can be aligned to efficiently execute the ever-adjusting strategy that the executives continuously formulate with operations.


Biography and Contact Information

Gary Cokins, CPIM

(gary.cokins@sas.com; phone 919 531 2012)

http://blogs.sas.com/cokins

Gary Cokins is a global product marketing manager involved with performance management solutions with SAS, a leading provider of performance management and business analytics software headquartered in Cary, North Carolina. Gary is an internationally recognized expert, speaker, and author in advanced cost management and performance improvement systems. Gary received a BS degree with honors in Industrial Engineering/Operations Research from Cornell University in 1971. He received his MBA from Northwestern University’s Kellogg School of Management in 1974.

Gary began his career as a strategic planner FMC’s Link-Belt Division and then served as Financial Controller and Operations Manager. In 1981 Gary began his management consulting career first with Deloitte Consulting. Next with KPMG Peat Marwick, Gary was trained on ABC by Harvard Business School Professors Robert S. Kaplan and Robin Cooper. More recently, Gary headed the National Cost Management Consulting Services for Electronic Data Systems (EDS)/ A.T. Kearney.

Gary was the lead author of the acclaimed An ABC Manager’s Primer (ISBN 0-86641-220-4) sponsored by the Institute of Management Accountants (IMA). Gary’s second book, Activity Based Cost Management: Making it Work (ISBN 0-7863-0740-4), was judged by the Harvard Business School Press as “read this book first.” A reviewer for Gary’s third book, Activity Based Cost Management: An Executive’s Guide (ISBN 0-471-44328-X) said, Gary has the gift to take the concept that many view as complex and reduce it to its simplest terms.” This book was ranked number one in sales volume of 151 similar books on BarnesandNoble.com. Gary has also written Activity Based Cost Management in Government (ISBN 1-056726-110-8). His latest books are Performance Management: Finding the Missing Pieces to Close the Intelligence Gap (ISBN 0-471-57690-5) and Performance Management: Integrating Strategy Execution, Methodologies, Risk, and Analytics (ISBN 978-0-470-44998-1).

Mr. Cokins participates and serves on committees including: CAM-I, the Supply Chain Council, the International Federation of Accountants (IFAC), and the Institute of Management Accountants. Mr. Cokins is a member of Journal of Cost Management Editorial Advisory Board. Cokins can be reached at gary.cokins@sas.com . His blog is at http//:blogs.sas.com/cokins

and his latest book can also be previewed at http://www.sas.com/apps/pubscat/bookdetails.jsp?catid=1&pc=62401

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, Knime.com
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.

http://spreadsheets.google.com/pub?key=rWTqcMe9mqwHeFv1e4GS_yg&single=true&gid=0&range=a1%3Ae24&output=html

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

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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 (http://www.gartner.com/it/page.jsp?id=855612 ) 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.

Bio-

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 www.rexeranalytics.com

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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-

davis_jim

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.

Biography-

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 (www.sas.com) 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 http://www.analyticbridge.com 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.
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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 http://www.InferenceForQbD.com 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.

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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.

Biography

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 http://inferenceforr.com/ especially if you need to rev up your MS office Installation with greater graphics and analytics juice.