Thought Leaders in Big Data: Eldad Farkash, CTO of Sisense (Part 1)

An end of the year view into what’s happening in the Big Data ecosystem with Eldad Farkash, a veteran of the Business Intelligence world.

Sramana Mitra: Let’s start with introducing our audience to yourself as well as to Sisense.

Eldad Farkash: I’m the CTO and Founder of Sisense. Sisense is a Big Data analytics company that bridges the gap between complex models and Big Data clusters with simple business users’ unique needs. The company itself is around 130 people. We have raised around $50 million. We have offices in Tel Aviv and New York. Our R&D team operates from Tel Aviv and sales and management operates in New York. We have 700 customers ranging from huge Internet web companies to government agencies and startups.

Sramana Mitra: What about target customer? Specifically, how do you segment the market and where are you focusing?

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Thought Leaders in Big Data: Frank Bien, CEO of Looker (Part 5)

Frank Bien: Let’s go back to the HotelTonight example. There’s no way the data would have understood that there was a correlation between these two data metrics that they had identified. Those were two different business teams that independently built these views of their business. Then one them says, “ Let’s put this together and see what happens.” You see that time and time again. What we really believe is that the trick is going to curate this over really large data sets so that business people can actually get value out of it.

Sramana Mitra: So you’re saying that we’re in the domain of data analyst and data scientist. My interpretation also is it’s going to remain a bad domain for another several years. I think eventually we will see actions being taken in software without the data scientists needing to intervene. >>>

Thought Leaders in Big Data: Frank Bien, CEO of Looker (Part 4)

Sramana Mitra: Let’s look at your big picture. Bring it up to industry level and tell me more about what trends you are seeing from your vantage point in the Big Data world.

Frank Bien: My entry into data has only been during this Big Data trend – right after 9/11 when Web 2.0 was happening. In 2003, I was working in big column stores. My view is coming from that side. What I say might be surprising. We’ve stored lots of data but there’s been very little value. Organizations have spent millions of dollars, and collectively billions of dollars, in storing just a massive set of information and data. The value at the other side has been really elusive. I think the big trend moving forward is to finally crack into this data and move it beyond data science experiments into the hands of business people who can make better decisions. We believe in Looker that involves the data team. >>>

Thought Leaders in Big Data: Frank Bien, CEO of Looker (Part 3)

Frank Bien: They saw, of course, that people who were booking hotels were also referring customers because they had a great service. What they also saw was that people who are not using the service were referring the most number of customers. In a lot of organizations, when they see something like that, the thinking goes to fraud. In HotelTonight’s case, since they had Looker, they could drill in. In our environment, you constantly have this ability to drill-in to data.

They were able to infer that the people who were referring customers were flight attendants or bartenders. >>>

Thought Leaders in Big Data: Frank Bien, CEO of Looker (Part 2)

Frank Bien: We’ve found that organizations have now stored lots of data, but trying to layer on the traditional BI tools hasn’t really worked. I think as we look across our customers, that’s a constant theme.

A great customer story would be one of our earlier customers like HotelTonight who are doing same day hotel bookings. They’re really disrupting the hotel booking industry in a big way. The way they have to do that is oriented towards data—understanding how customers are traveling and where inventory will be required. In a place like HotelTonight, getting departmental views was not good enough. What they had to do was have information across the entire organization and that information had to be very reliable.

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Thought Leaders in Big Data: Frank Bien, CEO of Looker (Part 1)

How far are we from software making decisions based on Big Data rather than human data scientists having to make those decisions? Let’s see what Frank Bien, CEO of Looker, has to say.

Sramana Mitra: Let’s start by introducing Looker and yourself. Tell us what you do. What’s the company all about?

Frank Bien: I’m the CEO of Looker. Looker is a new kind of data analytics and business intelligence solution that really provides end users a new level of exploration capabilities on top of very large and complex sets of data.

Sramana Mitra: What kinds of customers are you going after?
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Thought Leaders in Cloud Computing: Chris Sullens, CEO of Marathon Data Systems (Part 3)

Sramana Mitra: What trends are you seeing in your marketplace? Is the market penetrated at this point or is a lot of your customer base still on legacy systems?

Chris Sullens: There’s a lot of white space because of the new entrants and the capabilities of these small guys to now consume the technology. At the high-end, there is pretty high penetration where you have legacy solutions. The small companies have been doing things with white boards and spreadsheets and finding a good dispatcher who has it all in the head and leaning on that particular person to be their solution.

From that standpoint, there’s a lot of white space which is also the case from the field service side. More and more people are finding solutions for the market, but I would say that over half of our customers come to us with no system at all.

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Thought Leaders in Cloud Computing: Chris Sullens, CEO of Marathon Data Systems (Part 2)

Chris Sullens: From a solution standpoint, we have a proprietary route optimization algorithm that we have developed. It does two main things. One, from a longer range planning perspective, it can put the schedules in any given constraint. For example, a certain technician needs to do a specific job because of whatever constraints. We feed all that from an operating system into our algorithm. The algorithm then computes the most optimal way to organize that work to minimize downtime and maximize productivity for those set of assets.

What we see is upwards of 40% improvement in capacity. That has a big impact on businesses. If you can grow your company without having to go through the process of buying another vehicle or training another employee, it is definitely positive. It makes it quicker and a lot more efficient. That’s one side of it.

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