 Live from the Sands Convention Center, Las Vegas, Nevada. Extracting the signal from the noise. It's theCUBE, covering AWS re-invent 2015. Now your host, John Furrier. Okay, welcome back everyone. We are live here in Las Vegas for Amazon re-invent. Amazon Web Search, AWS fourth year, our third year broadcasting live. Three days of wall-to-wall coverage. We're in day two, we've got a whole half a day and then all day tomorrow, big news. Day one of the keynotes, a lot of great stuff. This is theCUBE, Silicon Angles flagship program, where we go out to the events and extract the signal from the noise. Talking to the executive, we're going to have Andy Jassy on shortly, but talking to the people in the trenches, talking to the thought leaders, talking to the entrepreneurs, that's what we do. We collect the dots to allow you to connect them. Our next two guests is Jeremy Winters, Lead Data Warehousing Architect for full 360 and his colleague, Michael Bowen, Lead Data Architect, same company. Welcome to theCUBE guys. Thank you. Good to be here. Put my glasses back on for the boys. There you go. So, the big news today was not really a surprise for the folks inside the industry. Business intelligence has to be different. It's got to be faster. We've been seeing technologies advance all the way from ingest to prepare to spark in memory. All the technologies are all pointing to one direction. Faster analytics, better insights, better decisions, better outcomes. That's a sea chain because the old way of doing it was big, bloated software, send out reports, fenced out data and some silo. So Amazon really now is going to the next step, putting an actual product in the ground to reduce the costs down to significant levels but provide real value. This is your business wheelhouse. One, what's your take of the announcement? And then why so long? Why did it take Amazon this long to do this? Well, we're happy to hear that freedom and it was really cool for me. I've been around this business for about 20 years to hear them saying the slice and dice kind of stuff that I've been saying for 15 years. So it's kind of a big, I told you so, for the enterprise on-prem people that we kind of left five years ago when I jumped ship and I said the cloud is the future. So now it's kind of vitalizing that message that we've had for a while. What made you jump ship to go to the cloud? Was it obvious? You just said, okay, it's the new economics, the new platform. Is the cloud, some might say, wasn't fully baked then? Was it more of you saw it early? Did you have some use cases baked out or what was the impetus? We saw it early. We were one of the first partners full 360 about seven years ago to put S-Base in the cloud. We were the first ones to put Amazon, excuse me, Vertica in the cloud. And we had worked in enterprise environments where IT is kind of, I'm an IBM shop, you got to do it this way. Or I'm a Hewlett Packard shop or a Sun shop. And we couldn't keep our tools and migrate them along with us. So we'd find things that would work well on Unix environments and they didn't have Unix environments. So we saw in order to expand what we wanted to do, we have to have control of the whole environment. And AWS gave us that. So now we have VPCs with complete control over the whole end-to-end process. Jeremy, I love your shirt, fast data. That's really all about the data. There's no one characteristics. Before we get to that, I want to ask you to explain what you guys do, what's your company, how you guys fit into the ecosystem, and your relationship with Amazon. Because obviously, saw it early, that's good. You're two years ahead of everybody else basically. Now everyone's going to Amazon. What do you guys do and what do you guys do for customers? So we're a systems integrator. So we typically help customers get their data into the cloud, get their business intelligence setup, get their ETL setup. And our relationship to Amazon is, again, as partners. So we're not competing with them though. Sometimes they come out with a product and we're like, whoa, we have to rethink the way we're doing stuff. But at the same time, we've been able to roll with it. And that's part of our philosophy is to continuously change and expand as the technology changes. So we stay current, instead of staying locked into an old way of doing things, we're all about, what is the new way of doing things? How do we stay current with it? When we first started reporting on the ecosystem at Amazon, Dave Vellante and I would say, man, Amazon's going to rule the world. We're like, we saw it early. We're like, this thing is a tsunami, it's going to take the beach out and it's not going to stop until someone puts a seawall up. The question is who is going to be that vendor? We're still speculating on who that might be. We don't know. But the ecosystem was always kind of a question mark because they're running so hard on the product advancements. It was kind of like a hard thing to dissect. We had to compete there, had to partner. Will they eat us? Will they identify us and do what we're doing? Do they roll it into the product line? So the question is, is there a secret handshake in Amazon? Is there a way that you guys saw early in the ecosystem being successful? And how is the ecosystem going today? Because obviously it's a packed house here, a lot of players, but still people worry about that, you know, shit, am I in their path? Or, you know, yeah, because they're just rolling stuff out like it's nobody's business. Well, we're data folks and we concentrate on our customers' needs. So we would have customers, some of them are already in the clouds, like some of our gaming customers, and they would tell us different things and our enterprise told us things. But we found that we needed to change data warehouting methodology because now we had, we're kind of vendor agnostic in terms of databases. We are here with our partners VoltDB. We work with Redshift. We work with DynamoDB. And we said, how do we make all these things into a coherent place? So the idea was kind of, how do we do DevOps in data warehousing? How do we integrate multiple technologies? How do we handle the security needs of our customers? And so we knew there was a lot of stuff that wasn't product base, but process and methodology base. And guiding customers who were kind of gingerly getting into the cloud with confidence. All right, so let's break down some of the announcements. What do you guys think of the Fireball, I mean, Snowball, Firehose, QuickSight, Spice, these are things that they're adding in. Streaming of data, you talk about fast data, I love this shirt, what they're really referring to is, it's going to come trickling in slow off internet of things or it's going to be really fast targeted data that's been either worked on in the past. What is the dynamic in today's announcement? What is the real meat on the bone? Meat of the bone in today's announcement. For you guys? Well, for us, it's really opportunities. I mean, again, we're rolling with the technology, so we're not trying to stick with the way of doing stuff. We're trying to, or really going with it. So as these things come up, we're just trying to find customers that want to do it. And because we're, you know, we say data centric as in technology agnostic, we understand data regardless of what tool you're going to move it around with. So we want to find the people with the data that want us to help them use these new tools to move their data around to ingest it and to view it. Well, I mean, that's exactly what probably the customers will like too. They want to be data centric, but they also have multi-vendor environments. So, you know, there's some things that they're looking at too. So, I mean, Amazon, obviously they're their agenda. But the customer, they're going to do what's in Amazon, they're going to do some hybrid cloud. So there's going to be some engineering going on, certainly at the architectural level, right? Yes, okay. I got to lay out some architecture. What is the critical threshold issue for the customer? Is it the tooling? Is it the systems management? What do you guys see for customers that to get them over that point of, okay, I get this now, I'm operationally sound with cloud, I got my on-prem, and that's not going to go away. Most cases, 90% of the cases, there'll be some on-prem. Hybrid will dominate. We see hybrid all over the place now. So, this is the engineering conversation, but to look at down the road, where's the straight and narrow? Is it the tooling? What do you guys see? One of the things that Amazon came to us, and they said, well, we know that on-prem scales, what happens when you have a 50-node database? And this was even actually before the Redshift came on. And they asked us, and we showed that we could do stuff in the cloud that people outside on-prem hadn't been bold enough to do. So, Amazon trusts us enough in terms of our expertise with scaling databases, so that we could advance. Also, it's interesting when our customers have confidence in us, and they start talking our language. They said, can you get that stuff in our VPC? Well, we have this data over here. Can you get that in our VPC? That's fun. And we say, yeah, we have a really comprehensive methodology for data management that includes fast data, pulling data from microservices in real-time, and all the way to business. So, what do you think about the ingest tool? They have the data porting tool, they have a lot of migration, one's free. The schema thing was a freebie. I love that one. That seemed like a great tool. Another tool they were previewing, I think that was what was called, it was the data micros, firehose. They also had the data, I moved data in faster. So, there used to be the criticize of Amazon, was it's the Roche Motel. Data goes in, but you can't check out, right? So now, they're saying freedom. Is it really free? What's the, I mean, is it freedom? And what's the price of freedom? It's into the day, nothing's free. I mean, talk about our ability to do transparency. People look for the data supply chain, and with the traditional vendors, you know, you kind of like, well, this is in our proprietary box, and end users, when you're doing BI, you're responsible for the whole data supply chain. And then we open that up with stuff like config, and CloudWatch, and customers can see where their data lives at all times through the stack. And that's the transparency level that they've never had before. And also just in general with dealing with data, you know, one of my philosophies is you want, he says transparency, but it really, to me it means you should be focusing on the data, not on the things around it, and your data should be kind of self-evident in the story that it's trying to tell. So, regardless of what tools you're using to pulling your data, collect it, and house it, assuming the data's structured correctly, you can someday decide, you know what, this 200 petabytes of data is going to be, we want to shift off-site in these new snowball containers, because we're going to use it somewhere else. And that's not a problem, because our data still makes sense. As- Yeah, the data's the value. Exactly. Also the data having access to other parts of data, seeing what's coming in from other parts of the data flow. So, if we were to set a data, you want to see through the APIs of other systems. That seemed to me a big, the streaming stuff was pretty significant. I mean, I think that's solid. Let me ask you guys a different question then. So, let's talk about business intelligence, also known as BI. What is the biggest change happening right now in BI? Is it the, finally people are like crossing over to the fact that is a better way? Is it just the clock is running out on the old way? He calls them brands of yesteryear on stage, since he's targeting, he's talking about the old guys, the big data warehouses and the BI tools. So, what's the biggest change that's happening in BI? I would have to say, time to market. So, BI projects used to be very monolithic, take a long time. But now, when we say fast data, we don't just mean fast ingestion. That's part of it, is time to market. Here's your data. How quickly can we start making sense of it and start looking at it? Making it useful immediately. Making it useful, and as soon as you put data in Amazon S3, you dump 100 terabytes in Amazon S3, you can spin up an EMR cluster with Hive and start querying it right away. To me, that's fast data. That's having the ability to start thinking about the information as soon as you have it and at various steps along the way. And letting the BI reporting and stuff is much more interactive with that process instead of let's plan it out, do a bunch of work and then look at it. It's really, here's the data, let's start looking at it and let it grow. You know, it's interesting. It seemed like two years ago when the Kinesis was announced. I think it was two years ago, I don't remember, but Redshift too, Kinesis and Redshift, very interesting closed loop concepts. What you're basically referring to is I want to get the data and close out what I'm working on, not have to wait. The time is huge issue. Is those products getting traction in your customer base? Do you see Kinesis and Redshift? Obviously you know the hot seller. And if so, what value propositions and what use cases do you see them? We talked about this with one of our customers just yesterday, we brought some with us here. And they were talking about the accountability of the system that they bought, that they would probably like to replace Redshift. And Redshift gives you the auditability of who's querying what. And so we can use API calls and say, how useful is this system actually being used in your organization? And you can count that ROI. Generally if you buy a big data appliance, the whole IT organization uses it and nobody's quite clear what piece is using what. Redshift gives you that accountability right there. Yeah, I mean, I love that. What other observations do you guys have here at the show? What do you guys see going on? What's the big vibe here? The folks that aren't here, what's it like? I love that Amazon is pointed toward the enterprise. Because when you said big data, even just last year, people weren't sure if you were talking about e-commerce, if they were talking about data mining, if you were talking about IoT. And so now they're focused on the enterprise and getting more enterprise players. Now that people are being more confident, they're says, yeah, this is the stuff that we know that we've been talking about. And data warehousing is going to change with this and Amazon is part of it. So there was a lot of fun before, but it's becoming clearer that Amazon is serious about this business. The fog is lifting on there, enterprise. And they can do it, yeah, yeah. So it's making our messaging a little bit easier because people understand the cloud is real. Jeremy, thoughts on the show? Folks that aren't here? I'm just seeing kind of off a tanger that just really, I see a lot of focus on data clearly in the announcements, the fact that business intelligence is front and center in the main keynote. Business intelligence, 15 years ago, when I tried to explain to people, what do I do for a living? They're like- You get kicked out of the overflow room. Right, whereas now it really is a very central fundamental thing, which again, the idea is people are what makes data meaningful and the layers between the person and the data and the time to make that happen. It's a lot of emotional aspects too. There's a lot of storytelling that people talk about that. But to me, the thing that I get excited about that is that it really is so relevant because the value of the data is extremely untapped right now. And tapping the data is huge. Look at the spark stuff in memory. You're seeing the underlying technologies actually advancing, I mean, the puck is coming right to where BI is right now. And that's going to be not a geek conversation. It's going to be data, quant jocks, business people kind of partying together. You know, it's going to be interesting. It's the data itself. I mean, we have aviation customers and so when a plane got lost, we said, hey, we actually take engine data and we know when engine data is doing this and that. And so we're just like thinking about all the future things that can happen when we can get data real-time. Guys, Jeremy and Michael, thanks for coming on theCUBE. Really appreciate. Full 360, check them out. These guys are big time on the data bandwagon. Of course, the data bus, the data river, the data lake, which I don't like, data ocean, is more like it because it's fast, a lot of currents, dynamic, tsunamis, lake. You know, I'm not a big fan of the lake. Fast data, I'm a big fan of that. You're watching theCUBE. Go to SiliconANGLE.TV. Check out our guests of the week. Every Wednesday we do women in tech Wednesday. And check out guests of the week, a podcast every week dedicated to our guests of the week where they're bringing the signal. Of course, we're bringing the data. We're data-driven, sharing the data with you. We'll be right back after this short break.