 Live from Seattle, Washington, it's The Cube at Tableau Conference 2014. Brought to you by headline sponsor, Tableau. Here are your hosts, John Furrier and Jeff Kelly. Okay, welcome back when we're here at Live in Seattle, Washington for Tableau's user conference, Data 14. This is The Cube, our program where we go out to the events, extract the signal from the noise. I'm John Furrier, the founder of SiliconANG. I'm Jeff Kelly, big data analyst at Wikibon.org. Next guest is Vish Aghashe, global product lead for big data technologies at Google. Welcome to The Cube. Thank you. Google obviously is a big data company. I mean, the large scale, this is so impressive. I mean, just what an amazing success story. I was joking earlier in The Cube that, you know, Apple and Google are going to invent everything that was ever seen on Star Trek. You know, the eye-watches came out. Just the innovation is just fantastic. You guys have such a large scale and all that data. I mean, searching the web starts it, now you're doing a bunch of other stuff. So how do you manage the global big data lead? I mean, you're leading a big effort. So break that down for us real quick. Awesome. So at Google, as you know, Google has been investing a lot of money and energy in innovating technologies because, you know, if you ever use Google search engine, you can start typing whatever you want to find out and within a quarter of a second, we'll give you answers. We'll give you answers which are organized, which kind of addresses what you're searching for. This does not happen overnight. There is a great deal of innovation, both at the hardware level as well as software level, which has gone into making this happen. What we have been doing is that many of those innovations we are bringing to market in a commercial marketplace for our customers, our partners to use so that they can also start taking advantage of some of the innovations which we have done. That is what Google Cloud Platform is and that's how we are bringing our innovations to the marketplace. And so prior to that though, you guys were very active with open source so you obviously would open source a lot of stuff as well prior to that too. Yeah, Google is active in open source as well. Now the commercialization is a big part of it because the cloud, right? So the cloud's a big driver. What's the update there? At Google I.O., we saw some impressive benchmarks. I mean, the numbers are off the chart. I think MapR did a benchmark with you guys. That was pretty impressive. Shreve is over there and John Schroeder. I mean, I think it was like seven seconds to stand up and run this amazing benchmark that would have taken like it's seven years or some ridiculous number or some cost. You guys haven't been really touting the cloud a lot. I mean, you have, but I mean, not like in a big way, it's out there. It's almost like it's a stealth strategy, but it's not stealth. So share with us what the cloud business looks like. Is it consumers and enterprise? Is it both? Google made several announcements at Google I.O. around big data topic, big data technologies. When you look at Google Cloud, we offer services and products in multiple layers of the cake, so to speak, as a service cake. We have infrastructure services. We have platform as a service. We also have software as a services. Today we are here to talk to customers about big data technologies. BigQuery happens to be one of the key product service within that area and that's basically software as a service. So when you think about Google Cloud, Google Cloud offers in all three layers of a as a service model, infrastructure, platform, as well as software as a service. And there are numerous options, numerous services which addresses certain workloads, certain use cases for different customers. When it comes to big data, we talked at Google I.O. about Dataflow. We talked about PubSub. We talked about other innovations which are coming out. So when you look at all the services and aggregate with Google Cloud, you are able to address many diverse use cases, many diverse workloads, if you will, in this big data world, so to speak. I want to back up a little bit to kind of the genesis of your outward facing big data tools you're making available to customers. So obviously Google really started this whole big data trend with MapReduce and releasing those papers in 2004. But I believe, correct me if I'm wrong on the data, I think it was 2010, 2011 you started to actually package these and offer them to the outside world. What was that, how did that decision come about? That hey look, we've been doing this pioneering work internally, using it to serve our consumer customers with the search engine and all the other products we offer. Why the decision to actually get into the, essentially the enterprise tools, enterprise software, enterprise big data business? It's a great question. As you mentioned, Google has been pretty open about sharing a lot of innovations which we do. 2004 we published the MapReduce paper. There was a paper written about Dramal Technology which is the underpinning for a lot of big data technologies which are out there including BigQuery. And we have been publishing a lot of that. What happened was a lot of customers of ours realized the whole value of big data and they wanted to kind of start using some of the solutions, some of the strategies which Google was using to solve similar problems. In order to get started with big data, the biggest challenge is upfront investments which organizations have to do. It's a new topic, even if you kind of get away from the hype of big data, getting data driven, there's a great deal of investment which one has to make. So they were looking for an option where they can get started with technologies which can scale as their businesses scale, technologies which are easy to use, and technologies which are very cost effective. So a lot of customers have started asking Google, what does it take for you guys to share what you are doing with us? We are your loyal customers, we have been using your technologies and you're doing some great work. And that was the point where Google decided some of these innovations we are doing, we can start exposing those progressively to our customer base so that they can also take advantage of the innovations Google is doing. One aspect which I want to highlight, a lot of time industry tends to talk about software innovations which are done. When you think about Google Cloud Platform, it's really a combination of what we are able to do at a hardware or at a lower level, as well as at a software level, it combined together kind of gives what we call Google scale to the business problems and challenges which customers have. Well yes, it's absolutely the combination of the hardware and the software. Without the hardware innovation, you wouldn't be able to scale the way you do and that's part of the value proposition of the cloud. Is that you're able to extract away the complexity and offer that elastic scale capability. Talk a little bit about just the big data business relative to the cloud generally. So when we talk to, we cover the big data market pretty closely, we talk to all the Hadoop players out there and the majority of their customers are on-premise. And interesting, one of the leading companies there, Cloudera, their name has cloud in the name, but 95 plus percent of their customers are on-premise. What's it going to take for a lot of those deployments, not necessarily Cloudera, but just not even just necessarily Hadoop, but a lot of the big data deployments to move to the cloud. I think we're going there long term but there seems to be some barriers in the short term. What's it going to take to start to see that migration take shape? So there are a few trends which we are noticing in the industry as a whole. Industry as a whole have realized that there's a significant value in driving businesses being data driven. And that's where the whole hub of around big data is happening. There are, if you dig deeper into that, there are two, three characteristics within that trend in terms of how organizations need to execute. Number one, they really need to time to value. They really need to be able to kind of get to the value faster. Number two, there's a great deal of experimentation or iterative nature in terms of what they are trying to do with data is happening. And by its nature, a lot of times when you do start doing experimentation and when you start doing iterative, a lot of times you may not have upfront realization of ROI. It takes several experiments, it takes several iterations before you actually start seeing ROI. And if you start looking at all these characteristics and if you want to achieve decent ROI and provide a timely fashioned decision making to the organization, you need agile environment, you need environment where you can make use of your existing investments, such as people, technology. And that means that a lot of organizations are gearing towards kind of using familiar technologies where they don't have to worry about scalability at a very cost effectively. And more and more organizations start realizing that more and more organization start looking at the cloud because cloud tends to offer everything which is required scale, cost effectiveness in many of the technologies which such as BigQuery and other technologies which we are evolving make use of existing standards, SQL, Lesbos API so that you don't have to really rip and replace current investments whether it is in people or technology you can just kind of have this fit into your ecosystem while kind of starting to explore big data. Vish, I want to get your perspective on the business intelligence market and maybe comment on the data warehousing space. Obviously, Tableau is interesting in that they're disrupting that market of the old guard, how they handle the metadata and interconnecting the databases and kind of creating this horizontal overlay, if you will, and focusing just on the visualization. Not just visually, but the analytics behind that. They're very focused. How is that changing BI? Because a lot of the success that we're seeing from people that are users coming on theCUBE are sharing their stories is it's liberating at one level and two, it's giving them a career advancement. So there's a huge shift in the customer base. It's an aspirant of item and this kind of new born in the cloud concept. What's your take on that? What cloud does in cloud is the engine. Mobile is the interface. People are, you know, it's mobile and web. You've got the cloud under the hood and all this goodness on top. How is that going to disrupt? And what do you see the future for these BI guys out there? It's a great question. And going back to what I just said, big data or data driven industry is really changing the way businesses are thinking about business models, how businesses are making money and how they're disrupting. Key tenets supporting that is agility, the speed with which you are able to respond, empowering line of business functions rather than kind of line of business not having any control over the data. And it's a lot of it is self-serve. The situation is such that environment is changing really fast. You don't get years to respond to either opportunities or threat. That means business should be ready agile to really understand what the opportunity lies ahead of them or what are the threats. How do you help them fast? Like no lag, as fast as possible. Really fast. So you, as a business, as a line of business, you need to be able to focus on what your expertise is in. And in most cases, their expertise is in managing their business, not necessarily managing their IT systems as an example. So what solutions like Tableau is doing is they're really providing self-serve capability to the business analyst. What cloud and other technologies they're providing, especially cloud technologies, is self-serve from a backend perspective. LoB people, people in marketing organization now without having to worry about systems and architectures, et cetera, can get their data, upload their data, do the analysis, answer that question of the day or question of the hour, and kind of help the business. Push that data to the compute. That there you go. That's spinning up resources, provisioning on the fly without calling IT. Exactly. In the lot of cloud, I mean if you see. That's not shadow IT, that's no IT. No, I mean if you look at Google Cloud and a lot of other cloud products as well, we're focused on user experience and we do expect that line of business people, people with not a deeper technical knowledge and expertise should be able to take advantage of the services provided. And we see that time in and time again with BigQuery where CMOs organization, sales organization can adopt this technology for doing business analytics. So I got to ask the Tableau question. So why are you here, Google? Why don't you just make it? Why don't you just make Tableau? So Tableau is one of our data visualization slash BI partner. We provide, as I mentioned, big data technologies. So you're partnering with Tableau. We are partnering with Tableau. We provide big data technologies so that customers can adopt big data very cost effectively as well as very efficiently. Tableau helps us provide visualization to that data. Data visualization, storytelling, creates value. It helps us, helps customer bring the value out of data and the insight they're trying to get. So we're getting a little hook here but I want to get to Amazon question because we had the Amazon web services guy here earlier and he's just rolled out here a Amazon test drive risk-free for Tableau customers that were really about Redshift. Do you guys have an answer to that? Is it, how does a Tableau customer plug into Google? Is there a push button risk-free way to put the toe in the water? So a lot of Google Cloud services have what we call free tier. That means customer can log into Google Cloud console, start using services and there is a free tier. For example, BigQuery, you can query up to a terabyte of data for free without incurring a charge. So there are free tiers and these are well-published and documented. Also, all the visitors which are coming to see us at Tableau conference will get a certain coupon code to try Google Cloud products for free. And so that's going to, you are giving that out. We are giving that out. That is correct. Not all attendees. People who are inquiring and coming to our office. Okay, so right now there's a free tier which is the freemium model which is great. That's cloud friendly. How do they do that? Is there URL or just go to Google? So they can go to cloud.google.com and they can start trying any of the products and each of the products will have a free tier published. For example, in case of BigQuery, they can, if they have Gmail user access, they can look at the public data sets, query and get the experience. They can query up to a terabyte of data per month for free. So there are free tiers across the board. Vish, great to have you on theCUBE. I love talking with Google folks. Super smart, you guys doing great. Big fan, obviously living in Palo Alto. Google's been a great success story in Silicon Valley and around the world. Obviously it is what it is. Thank you so much for having me. And if I may, folks, if you're out there, you want to try big data very cost effectively, do give it a try to BigQuery. Do give it a try to Google Cloud. It's there. We'll love to help you out in the process. You got to say it is quite easy. I'm starting right now myself. So let's put our CrowdChat product on Google and see how it does compared to Amazon. We'll do a bake-off and we'll call you with the results. Oh, thank you. We'll kick the tires. Google has huge engine. I'm excited to hear more. And I always tell people, watch out for Google. The sleeping giant cloud can be very big. So thanks for coming on. Big data lead here inside theCUBE, talking about Google's global big data initiatives and technologies. We'll be right back with our next guest after this short break. We're live in Seattle. This is theCUBE. We'll be right back. Thank you.