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Skytree Brings Machine Learning to Life in the Enterprise

As part of IT Specialist's series of profiles on innovative startup firms in the information technology market, we are pleased to introduce Skytree. Skytree is a startup that focuses on Machine Learning to help enterprises and other organizations to exploit the massive amounts of data they are now accumulating with the aim of making more accurate decisions for their businesses going forward. There are quite a few companies using "Big Data" technology to assist organizations manage the explosion of data, but Skytree through its Machine Learning technology is taking a particularly interesting approach to the Big Data challenge. Joining us today is Skytree's Co-founder and CEO Martin Hack.

IT Specialist:  Thank you for making the time to speak with us Martin. To start with, can you provide our readers and overview of the background of Skytree's founders, and the inspiration for launching Skytree?

Martin: The two co-founders of Skytree are Alex Gray and myself. I have been involved in the technology industry for 20 years, in a variety of roles from marketing to business development and sales, engineering and product management. I previously worked for Sun Microsystems, SonicWALL and GreenBorder - GreenBorder was actually acquired by Google and became part of the underlying technology for the Google Chrome Browser.

My cofounder Alex Gray is our CTO and has a background in Applied Mathematics and Computer Science. Alex has been involved in Machine Learning going back to 1993 at NASA's Jet Propulsion Laboratory in its Machine Learning Systems Group. Alex has won numerous awards for his contributions to Machine learning, and he currently sits on the National Academy of Sciences Committee on the Analysis of Massive Data.

Alex and I have known each other for 14 years, and we started Skytree because we began to see more and more organizations looking to take the data sets they have and use them to improve their future decision-making. We saw a huge market for this requirement, and decided to begin working together. Skytree was initially in stealth mode as we developed the algorithms for the product, built the team and began to introduce our technology to customers. Once we felt ready to go, we came out of stealth mode in February 2012 and it's been an 18-month sprint since then.

IT Specialist: Martin, could you explain at a high level what "Machine Learning" is? At a minimum, I would guess that Machine Learning and Skytree's solution involves the creation of complex algorithms for data exploitation - what is the difference though between using traditional Business Intelligence (BI) tools versus what can be done with Machine Learning?

Martin: Machine Learning involves the creation of algorithms that allow for the analysis of massive data sets that traditional BI tools cannot handle. It is in a sense accurate to think of it as Artificial Intelligence. The algorithms literally allow for "learning", in the sense that the more data that is analyzed over time the "smarter" and more accurate the algorithms become. I suppose you could think of the concept as being almost akin to the Japanese concept of Kaizen in manufacturing where the process is not just static, but actually continuously improves over time. In that sense, Machine Learning can be thought of almost as an iterative process of improvement in data analysis since outputs become more and more accurate over time as the algorithms "learn" from the data - a virtuous circle if you will.

Another critical point about Machine Learning to understand is that it its real value is to actually provide organizations with concrete information to enable them to make better decisions going forward.  This concept of being able to more accurately predict the future is really the key point to remember; all the Big Data analysis in the world is useless to a company if all it does is analyze what has occurred in the past; businesses want to make better future decisions, and that's what Skytree helps them do. For those interested in learning more, we have a good overview of the Skytree products and services on our website.

IT Specialist: I think most readers will be familiar with Hadoop and the use of this open source OS to analyze large data sets. Can you explain what is the relationship between Hadoop and Machine Learning? What does Machine Learning do that Hadoop does not? 

Martin: Hadoop could be classified as data management. It's ideal for better organizing and assembling data, essentially transforming it into something that is organized and structured, so essentially Hadoop is a giant repository for large data sets. Machine Learning, however, takes the next step and analyzes this newly structured data to make predictions about what will happen in the future. In fact, Skytree's Machine Learning algorithms can actually sit on top of a Hadoop data set and turn that data into actionable intelligence by predicting possible future trends.

IT Specialist:  What are the factors that could help an enterprise IT or data analytics professional determine if Machine Learning could indeed assist him or her to solve a Big Data issue? Or to put it another way, what is the bottom line value proposition to the senior management of an enterprise or another organization to invest in a Big Data solution from Skytree and how would investing in Skytree's solution help them solve an issue in a way that might impact their bottom line?

Martin: Machine Learning is ideal for a highly data driven organization that wants to be able to more accurately predict future trends. For example, Machine Learning is ideal for financial institutions. Large banks and trading firms are inundated with data, and Skytree's solution can take that data and make more accurate predictions about what will happen in a financial market going forward. Or, to take another vertical market, eCommerce companies can use Machine Learning to more accurately predict the future buying patterns of their customers and then direct their inventory manage and sales focus accordingly. Feel free to browse our site where you can find an overview of some Skytree customers.

IT Specialist: There have been some reports in the media about an emerging shortage of data scientists that may prevent many organizations from fully exploiting Big Data. In that context, how easy is Skytree's solution to actually implement and operate for enterprise IT analysts who may not be data scientists? 

Martin: Once you set up Skytree's product on top of your data sets if you will, the product is very easy to use. An enterprise IT Professional or data analyst can use Skytree's solution with ease once it's been installed. The product operates behind the scenes. To borrow a term from cloud computing, Skytree's solution is "abstracted" from the user of our technology - all of the magic operates in the background once it's connected to the underlying data sources.

IT Specialist: One thing that caught my eye on your website and that I found absolutely fascinating was that you have a number of customers in astronomy who are actually using Skytree to actually better understand and catalogue the vast reaches of space. I gather one of your customers is actually using Skytree to actually search for signs of extraterrestrial intelligence?! Could you elaborate a little bit more on how your astronomy and space exploration customers are using Skytree's Machine Learning technology?

Martin: That brings up a very good point about the origins of Machine Learning. One of the original Big Data problems was in the realm of astrophysics. In fact, as I think I mentioned, our CTO Alex originally began implementing Machine Learning for NASA.  Canadian Advanced Network for Astronomical Research (CANFAR) at the Canadian Astronomy Data Centre is currently using Skytree to better map out the universe. There are literally millions of stars and other objects out there, and they use Skytree to better map out an actual map of the universe more accurately and with less guesswork. Likewise, we are assisting scientists at the SETI Research Center (SETI stands for Signs of Extraterrestrial Intelligence) to search for signs of other life in the universe. SETI has terabytes of data streaming into their computers in real time. Their ultimate goal is to find the one signal that stands out above the noise. SETI chose Skytree Machine Learning to help get through more of their data efficiently and to determine which data to analyze.

IT Specialist: For organizations who may want to learn more about how Skytree can help them, what is the best way to engage with you?

Martin: We are very flexible in this. Feel free to call our Offices at 408416-5600, or e-mail is at and we'll respond immediately. Our method for interacting with potential customers is to take a consultative approach as Big Data and Machine Learning may be a fairly new topic for them, and we first want to understand an organization's needs and requirements to ensure that there is a match with our capabilities and value proposition. For those who would like to learn more, I encourage you to visit the Skytree YouTube channel where we have a number of videos about our technology and customer applications.

IT Specialist: I know Skytree recently raised a big $18 million Series A round from a number of partners. What was it about Skytree that made your investors want to partner with you?

Martin: We were very pleased with the amount of money we were able to raise, and in fact our Series A round was actually substantially oversubscribed. We have a diverse group of investors, including U.S Venture Partners; Javelin Venture Partners; Osage University Partners; and UPS Corporation. I think a big part of our success raising money was that we possess what I like to refer to as the "Three T's" that investors look for: The right Team; The right Timing; and the right Technology. On top of that, we already had a number of customers when we went to raise capital, thereby proving out the demand for our technology. Overall, we were very pleased with how everything went.

IT Specialist: Thanks so much for your time Martin. What Skytree is doing sounds really fascinating, and I suspect you will have a great deal of success going forward.

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