 Does this look good? Oh, we're live here, live in New York City. Right, we are, the countdown went really fast on me and I wasn't paying attention. So, okay, this is siliconangle.com's flagship, covers the queue of Strata. We're here live for a big data week in New York City, and all the big data action here. I'm Joe, my co-host Dave Vellante, wikibun.org. And Bruno, you're welcome to the queue for the first time. Well, thank you very much for having me, John. So, great to have you in. We've chatted in the past. You were at Microsoft when you did your famous viral video when you were leaving Microsoft. Yes. How many hits did that end up getting? We ended up getting about a million views over the entire program. As you know, the last video wasn't the only video I did. I did videos with Malcolm Gladwell and Guy Cowasecki were focused on broadening the big data world. In less than a year's time, you got those results. All right, so explain to the folks what your current situation was, where you were at Microsoft real quick and then you have the new company and we'll get into some of the cool things you're working on, including the tattoos. Sure. I was at Microsoft for about seven years. Before that, I worked at Business Objects and Apple and a few other companies here in Silicon Valley. I moved to Seattle to start the business intelligence business. So I was there a part of the BI team and we took it from zero dollars to a billion dollar business, including big data and so forth. That was a lot of fun. It was a great company to work for. And then I just recently, now about six months ago, moved back to the Silicon Valley to work for a company called Sysense. We are the big data analytics company and we focused on helping companies of all sizes deal with big data issues on a very simple hardware. So what was your, you had a marketing angle. I thought it was pretty clever. What was it, the smallest? Yes. Big data company. What was it? That's correct. Explain that. So essentially here, when you think about big data, the first mistake I think we make in this space is that we identify big data with a dupe and we also identify big data with big companies and big bucks and big boxes and so forth. So everything's big. And as it turns out, from what we see. Big data meet big iron. That's Larry Ellison's philosophy. Exactly. So it works for Larry, I think. And we actually have an office right across from, or I'm trying to get a hold of him if he listens to this. If he wants to pass over the lease when we go bigger, we'll take over his building. But in the real world, what happens is that companies of all sizes have big data issues. And so what we announced at this event is what we called the smallest big data analytics solution, which we crunched about a terabyte of data on an eight giga machine, which as you know, mathematically is impossible. And we showed that using our technology, you can do such things. Great, so tell us about the tattoos. We'll get into some of the industry stuff. So yesterday, two days ago, you've been wearing it. Do you still have it on now? I still have the tattoos. I don't know if you want to zoom in on them, but. No, no, I wouldn't. I will give you, actually guys, I'll give you one here. You can have this one and maybe you can have this one and the team behind there can have the third one. You guys know that I'm committed to, it's hard to read backwards, but I'll tell you what they say. You know, I'm committed to the data world, so I decided with the team that it would be a great giveaway to tattoo people. And people have been tattooing themselves across the show. This one here I have here says, go ahead and make my data. I went as far as shaving my arm to make sure that it looked really good. This other one here says, I eat data for breakfast and I have one in my neck that says I size sense data, or I heart, or I love data. Okay, so do you definitely have the Big Data Branding Award here at Strata, congratulations. Also did a Nick Knight's talk on Monday on Big Data for Small People, which was an analogy for Big Data for Everyone. Most companies focus on the Fortune 5, we focus on the Fortune 5 million. Bruno, I love your passion, that's one thing that I like about you and like to get attention and the passion is clear, but you also work for a really good company that's really relevant. Let's talk about that right now because I had a chance to meet the founders from Israel at the office when you first came in there, it was great to see them. But explain to what they're doing because you guys have a really clever product that solves a problem. Explain the product and what you guys are doing. So the product is essentially an end-to-end solution, it starts with the data store, it's an in-memory data store and we have, it's a columnar data store and we have in-memory technology that is using the combination of RAM and Drive and what we call CPU-Ware to maximize the capacity on your machine. And so in addition to the data store and the capacity we have that we call the ElastiCube, we also have what we call automatic ETL which basically solves the issue of getting data into a simple environment for what you might call normal people so they can start work with the data. And on top of that we have visualization, Hadock tools that are integrated inside the environment so people can quickly start with their disparate data, grow with it and then build great visualization on top of it. We think that data sources don't have to become apparent to the end user, most people want to be able to work with data regardless what it is. It could be Hadock based data, it could be SQL Server, it could be a file, it could be a cloud or an on-premise application so really focus on hiding your complexity for the end user so they can get to their data faster and provide great analytical solutions. That's the idea. So no external ETL. No, no, essentially it's funny, I was doing demos throughout the week and I showed that there's no scripting. Most of the data integration happens by clicking in the mouse, I just press the plus button and I can add Salesforce.com data, I can add data through Hive, I can add data from the spreadsheet or any database that you know. So really that's what we're focusing on and that's what we call automatic ETL. We detect the data and the metadata and we'll bring all that inside the nice environment where you can start doing mashup which is very complicated. Most business analysts today spend a lot of time, too much time, preparing their data and for us as an industry, if we want to evolve, we got to get rid of that, remove the bottlenecks there. So Bruno, you started the conversation by sort of debunking some of the myths that you see that big data equals Hadoop that only the big guys are really in a position to do this. Well, two of the big guys that are talking about in memory now are SAP and Oracle. Yes. And they got a big customer base. Are you going after those customers? How do you communicate to those CIOs and practitioners and why size sense? So we're not going after a head-to-head against an SAP HANA or any of the Oracle big box solutions. In fact, you know most of the people that can afford solutions like that either have a lot of time, a lot of money and big teams. Yeah, a lot of people, right. And it turns out that's probably maybe 500 companies. While these guys focus on the Fortune 500, we focus on the Fortune 5 million. That might include them, right? Some customers of ours are big companies, Target and Merck and Caterpillar and Philips. So we definitely have a great value proposition for them. What is this value proposition is very simple. First of all, when you work with size sense, you don't really have to think about the technicality or the infrastructure required in order to scale. Most of the companies we work with have what we call a complex data problem. What the complex data problem is is two factors. Either it's data that grows at a pace where you can provide infrastructure fast enough. You're an online business and you're turning on behavior analytics on your website and all of a sudden your traffic explodes by 50%. Well, so what's the solution of the other guys? Well, you buy more racks, more memory or maybe you hire more people. In our system, because we optimize the way the data works on any machine, any server, you don't really have to worry about that. The second problem we solve that is a characteristic of a complex data problem is multi-data sources. There is nobody out there that is satisfied by just looking at data from Salesforce.com only. Most marketers want to know what's happening in Google Analytics, Google AdWords, Salesforce and maybe Zendesk. They want to have a 360 view of their data and today the industry is fairly immature in providing end-to-end solution for that and we focus on those scenarios. So with our solution in three clicks you'll get Google Analytics, Salesforce.com data and Zendesk and we have a dashboard you can download and know if the leads that you're bringing inside your company are bringing any business and they're costing you the right amount of money. And so you can install on-premise or in the cloud, correct? That's correct. Do you have customers asking you for paid-by-the-drink approaches to these types of analytics? Do you see that coming? Paid-by-the-drink meaning paid-by-the-amount-of-data that they're using? Yeah, yeah, yeah. Sure, or the amount of activity around your software. Yeah, and so this is a very good question because in fact our business model is the entire opposite of that and you're right that the competition, you've got other companies in the space that are in memory, public leading companies and these companies make it actually very hard for people to bring in more data and they do charge-by-the-drink very much like what you're saying. For us when you buy size-sense the principle is that you can add an unlimited amount of data. We actually want you to add more data so we give you all the connectors out of the box for free and as we add more connectors that just comes with the product. Okay, excellent. Well Bruno, listen, thanks very much for stopping by theCUBE. It's great to see you today and last night. Good hanging with you. Great to see you, dynamic personality. Love your work. Love what you did at Microsoft. Love what you're doing at the startup. Congratulations, great to see you. This is theCUBE. We have all kinds of signal here inside theCUBE and a lot of fun as well. Bruno doing some serious work, having fun doing it. That's what this ecosystem's all about. Thanks for coming. This is theCUBE. Thanks for your short break.