Here is an interview with Kai Chew, Founder of Cloudstat. CloudStat is developing a cloud-based statistical platform to help researchers who want to make sense of data to do statistical analysis collaboratively with its high performance computing infrastructure.

Describe the startup story for setting up CloudStat

In 2010, Kai Chew, as an actuarial student, found that R Language is the best statistical tools available, offering a breadth and depth in statistical computing beyond what is available in commercial closed source products, and is the lingua franca in statistics. However, R, remains, primarily, a programming language for the highly skilled statistician, and out of the reach of many, especially his actuarial course mates. Kai was inspired to leverage R Language to create a online statistical platform so that the students and researchers can do high performance data analysis collaboratively in easier way. As a platform, developers can create statistical modules to allow anyone who don’t have programming knowledge to make sense of data. Finally, the researchers (even SMEs) can apply high performance computing in data analysis immediately (within a minute) while save time and save cost.

In the end of 2010, Kai worked on the business plan and built the prototype. In July, Kai hired a programmer in assisting to develop the CloudStat system.  In August, CloudStat.me Sdn Bhd was incorporated and the web cloudst.at was beta testing in November 2011. In December, CloudStat moved into Plug and Play Malaysia as temporarily office in Cyberjaya, Malaysia.

What advantages does CloudStat give over a plain vanilla Amazon EC2 instance?

The real difference is between IaaS and PaaS. If you were interested in an IaaS cloud, we would have definitely considered AWS, it’s flexible, can setup applications other than R, given that you have time and knowledge. However, the real win for us was getting access to an R environment that no management needed, so that we are spending our time and money focused on solving the statistical problem instead of creating and managing our various environments. It didn’t make sense to gamble on AWS technology and learning curve.

With CloudStat, you get everything pre-installed and pre-configured. Everything works out of the box, you will need no more administration and you have not to deal with any security keys. Furthermore, we provide a very powerful and user friendly web interface for analyzing, developing and collaborating in the cloud. The Security is our top priority. We meet high security standards by providing secure encryption for data transmission and storage. In the default configuration you will not get this level of security at Amazon Web services.

Why CloudStat chooses R ahead of others, like python and FORTRAN?

R’s language is more powerful than SAS or SPSS. R developers write most of their analytic methods using the R language. R is the lingua franca for statistics.

What are the incentives that Universities and Government give to tech startups in Malaysia?

Since the entrepreneurship environment is still not so strong in Malaysia, they do have a lot of funds and grants but managed by inexperienced managers and with many unnecessary processes which will cause the willingness of entrepreneurs to apply for them. So, until now, CloudStat is still maintaining as a bootstrapping company. Fortunately, CloudStat currently was sponsored a place in MSC Commercialization Center and given consultation and support by Mr. Jamie, Business Development Manager of Plug and Play Malaysia.

What are the exciting new features that you plan to roll out for CloudStat ?

CloudStat is now providing a statistical platform that allows students and researchers to do data analysis collaboratively with R Language in the cloud at anywhere, anytime across multiple platforms. There is no more download, installation, upgrade or maintenance needed. You can exchange data analysis experience immediately with the experts all around the world with CloudStat.

We are in the way to provide interactive R Language learning, statistical modules creator and last but not least, improving our High Performance Computing infrastructures.