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.
Frank Bien: We see this interconnection. We have data represented in Looker. Looker provides this transformation of data. This is what inventory looks like. This is how lifetime value of a customer should be represented. Right now, some of that data is consumed in the UI but more and more of that data is also consumed in other applications. Looker is definitely an application service for analytics. You see things like dynamic pricing engine powered by the data that’s being represented. We’re seeing a lot of that today.
Sramana Mitra: Exactly. That’s exactly where I’m going with this. Is there anything else you want to add?
Frank Bien: The other thing that we see is there’s been this real revelation in data infrastructure and how to store data and how to access data faster. The tool set has been much more about evolution. We have a tool set in the BI ecosystem that’s evolving where the underlying data infrastructure has completely had a revolution. I think what’s going to be required in what we’re trying to do is to bring the tool layer up to where the infrastructure has gone. As we and others do that, that’s where we will finally unlock the value of data.
Sramana Mitra: Great! Thanks for your time.