 Welcome to Las Vegas, I'm Jeff Kelly with wikibon.org. You're watching theCUBE, SiliconANGLE's premier live broadcast. We go out to the technology events, and as John Furrier likes to say, extract the signal from the noise. So being here at the AWS show, we're going to talk to a lot of AWS customers, hear a lot about what they're doing, in this case around analytics, data warehousing, and data integration. So for this segment, I'm joined by two customers, Daniel Heacock, Senior Business Systems Analyst with ETICS, and Adam Haynes, who's a data architect with federated sample. Welcome guys, thanks for joining us on theCUBE. Thanks. Your first time, so promise we'll make this as painless as possible. So you guys have a couple things in common, we were talking beforehand, some of the workflows are similar, you're using Amazon Web Services Redshift platform for data warehousing, you're using attunity for some of the data integration to bring that in from your operational, transactional databases, and using a BI tool on top to kind of tease out some of the insights from that data. But why don't we get started, Daniel? We'll start with you, can you just tell us a little bit about ETICS, kind of what you guys do, and then we'll just kind of get into the use cases and talk a little bit about how you guys came to use AWS, and attunity, and some of the other technologies you're using. Sure, yeah, so a company I work for is ETICS. We are a primary market ticketing company in the entertainment industry. We provide box office solutions to venues and venue owners, all types of events, casinos, fairs, festivals, pretty much you name it, we sell some tickets in that industry. We provide a software solution that enables those menu owners to engage their customers and sell tickets. So could kind of a competitor do something like Ticketmaster, the behemoth in the industry, in your channel? Definitely, so Ticketmaster would be the behemoth in the industry, and we consider ourselves a smaller, sexier version that is more friendly to the customers. Customer friendly, more agile, absolutely. So Adam, tell us a little bit about Federated Sample. Sure, Federated Sample is a technology company in the market research industry, and what we aim to do is add an exchange layer between buyers and sellers. So we facilitate the transaction between when a buyer or a company like Coke would say, hey, we need to do a survey. We will negotiate pricing and route our respondents to their survey. Try to make that a more seamless process so they don't have to go out and find survey respondents. They're qualified and absolutely got it. So let's talk a little bit about, let's start with AWS. So obviously we're here to reinvent a big show. 9,000 people here. So you guys, you know, talk about agile, talk about cloud enabling kind of innovation. Adam, let's start with you. What kind of brought you to AWS? Are you using Redshift? And I think you mentioned you're all in the cloud. Right. Just give us your impressions of the show and AWS and what that's meant for your business. Right, show's been great so far. We were originally on-premise entirely, a data center out in California, and it just didn't meet our rapid growth. We're a smaller company startup, so we couldn't handle the growth, so we needed something more elastic, more agile. So we ended up moving our entire infrastructure into Amazon web services. So then we found that we had a need to actually perform analytics on that data, and that's when we started the transition to Redshift. And so the idea being you're moving data from your transactional system, which is also on AWS, into Redshift, so you're using attunity for that. Their cloud beam solution, talk a little bit about that and how that is differentiated from some of the other integration methods you could have chose. Right, so we started with a more conventional integration method, a homegrown solution to move our data from our production SQL server into Redshift, and it worked, but it was not optimal, didn't have all the bells and whistles, and it was prone to bad management being, like not many people can configure it and know how to use it. So then we saw cloud beam from attunity, and they offered a native solution using SQL server replication that could tie into our native SQL server and then push that data directly into cloud beam at a very fast rate. So moving that data from the SQL server, is it essentially a real-time replication so that that's moving that data into Redshift so that your analysts can actually, when they're doing their either reporting or doing some real ad hoc kind of queries, they can be confident they've got the most up-to-date data from your SQL server transactional system. Right, yeah, nearly real-time, and just to put in perspective, the reports that we were running on our other system were taking 10, 15 minutes to run, and in Redshift we're running those same reports in minutes, one, two minutes. Right, and if you're running those reports quickly, the people sometimes forget when you're talking about real-time or interactive queries and reporting, it's somewhat only as good as the data timeliness that you've got, the timeliness of the data that you've got in that database, because if you're trying to make some real-time decisions and you've got a lag of, depending on the workload and your use case, even 15 minutes to an hour back to really impact your ability to make those decisions. So Adam, talk a little bit about your use case. Is it a similar cloud, all-cloud architecture? Are you moving from, I'm sorry, Daniel, moving from on-premise to Redshift? So we are actually working with an on-premise data center, it's an Oracle database, and so basically we ran into two limitations. One, regarding to our current reporting infrastructure, and then two, kind of our business intelligence capabilities. And so as an analyst, I've been kind of tasked with creating internal feedback loops within our organization as far as delivering certain types of KPIs and metrics to inform our different teams, our operations teams, our marketing teams. So that has been one of the kind of BI elements that we've been able to achieve because of the replication and the Redshift. And then the other is actually making our reporting more, I guess, comprehensive. We're able to run, now that we're using Redshift, we're able to run reports that we were previously not able to do to run on-premise transactional database. So really we just are kind of embracing the power of Redshift and it's enabling us in a lot of different types of ways. Yeah, I mean we're hearing a lot about Redshift at this show, it's the, Amazon says the fastest growing service AWS has had from a revenue perspective. And it's, you know, six, seven year history. So clearly there's a lot of power in that platform and it removes a lot of the concerns around having to manage that infrastructure, obviously. But the performance, you know, that's something I think when people have their own data centers, their own databases, tuning those for the type of performance you're looking for is going to be a challenge. Was that one of the drivers to kind of your move to Redshift? Oh, for sure. The performance, I'm trying to think of a good example of a metric to compare, but it basically enabled us to develop a product or to develop products that would not have been possible otherwise. There were certain, I guess, the ability to crunch data, like you said, in a specific timeframe is very important for reporting purposes. And if you're not able to meet a certain timeframe, then a certain type of report is just not going to be useful, so it's opening the door for new types of products within our organization. Well, let's dig into that a little bit, the different data types we're talking about. So you've got, at E-Tix you're talking about customer transactions, you're talking about profiles of different types of customers. Tell us about some of the data sources that you're moving from your transactional system, which I think is an Oracle database, to Redshift, and then what are some of those types of analytic workloads, what kind of insights are you looking for? Sure, so we're in the business of selling tickets, and so one of our main concerns, or I guess I should say we're in the business of helping our customers sell tickets, and so we're always trying to figure out ways to improve their marketing efforts, and so marketing segmentation is one of the huge ones. Appending data from large data services in order to get customer demographic information is something that is easy to do in Redshift, and so we're able to use that information, transaction information, customer information to, I guess, better engage our fans, so. And likewise, Adam, could you maybe walk us through kind of a use case, maybe types of data you're looking at that you're moving into Redshift with Attunity, and then what kind of analytics are you doing on top of that, what kind of insights are you gathering? Right, so our data's a little bit different than ticketing, but what we ultimately capture is a respondent's answers to questions, so we try to find the value in a particular set of answers, so we can determine the quality of the supply that's sent from suppliers, so if they say that a person meets a certain demographic that we can actually verify that that person meets that demographic, and then we can actually help them improve their supply that they push down to that respondent to it, everybody makes more money because the completion rates go up, so overall just business analysis on that type of information so that we can help our customers and help ourselves. So I wonder if we could talk a little bit about kind of the BI layer on top as well, I think you're both using Jaspersoft, but beyond that, one of the topics we've been covering on theCUBE and on Wikibon is this whole analytics for all movement, and we've been hearing about self-service business intelligence for 20 plus years from some of the more incumbent vendors like BusinessObjects and Cognos and others, but really, if you look at a typical enterprise, business intelligence usage or adoption rate kind of stalls out by 18%, 20%. Talk about how you've seen this kind of industry evolve a little bit, maybe talk about Jaspersoft specifically, but what are some of the things that you think are going to have to happen or some of the types of tools that are needed to really make business intelligence more consumable for analysts and more just business users, people who are not necessarily trained in statistics or data scientists? Adam, why don't we start with you? Yeah, so one of the things that we're doing is with our Jaspersoft, we're trying to figure out certain, we have APIs and we have traditional client server applications, which ones our customers want to use the most is we're trying to push everybody towards an API oriented, so we're trying to put that data into Redshift with Jaspersoft and kind of flip that data and look at it year to date or over a period of time to see where all of our money's coming from, where all of our revenue's getting driven from, and our business users are now empowered with Jaspersoft to do that themselves. They don't rely on us to pull data from them, they can just tie right into Jaspersoft, grab the data they need for whatever period of time they want and look at it in a nice, pretty chart. Is that a similar experience you're having at E-Tex? Definitely, and I think one of the things I should emphasize about our use of Jaspersoft and basically really any BI tool you choose to use in the Amazon platform is just the ability to launch it almost immediately and be able to play with data within five, 10 minutes of trying to launch it, so. Yeah. It's amazing how quickly things can come from just a thought into action, so. Well that's a good point, because I mean you think about not just business intelligence, but the whole data warehousing world, it was the traditional method is you, the business user or business unit goes to IT, they say here are some of the requirements, some of the metrics we want in these reports. IT then kind of goes away and builds it, comes back six months later, 12 months later, here you go, here's the report, and next thing you know, the business doesn't even remember what they asked for, this isn't necessarily going to serve our needs anymore, and you've just essentially, it's not a particularly useful model, and Amazon really helps you kind of shorten that time frame significantly, it sounds like, between what you can do with Redshift and some of the other database products and whatever BI tool you choose to use, is that kind of how you see this evolving? Oh definitely, and the options are, I guess the kind of plug and play workflow is pretty amazing, and it's given us the flexibility in our organization to be able to say, well we can use this tool for now, and there's a chance we may decide there's something different in the future that we want to use and plug in in its place, and we're confident that that product will be there whenever the need is there. Right, well that's the other thing, you can start to use a tool, and if it doesn't meet your need, you can stop using it and move to another tool. So I think that puts vendors like Jasper Stop and others, put some on their toes, they've got to continually innovate and make their product useful, otherwise they know that their AWS customers can simply press a button, stop using it, press another button, stop, start using another tool. So I think it's good in that sense. But kind of, when you talk about cloud, and especially around data, you get questions around privacy, about data ownership, who owns the data? If it's in Amazon's cloud, it's your data, but it's in their data centers. How do you feel about that, Adam? Is there any concerns around either privacy or data ownership when it comes to using the cloud? I mean, you guys are all in in the cloud, so. Right, yeah, so we've isolated a lot of our data into virtual private clouds, so with that segment of the network, we feel much more comfortable putting our data in a public space, because we do feel like it's secure enough for our type of data. That was one of the major concerns up front, but after talking with Amazon and going through the whole process of migrating to, we kind of feel way more comfortable with that. Can you expand on that a little, so you've got a private instance, essentially in Amazon's cloud? Right, so we have a private subnet, so it's a segmented piece of their network that's just for us. So we're not, you can't access this publicly only within our VPN client or within our infrastructure itself. So we're segmented, we're away from everybody else. Interesting, so they offer that kind of type of service when there's more privacy concerns and security concerns. Definitely. And of course, a lot depends on the type of data. I mean, how sensitive that data is. If it's personally identifiable data, obviously it's going to be more sensitive than if it's just general market data that anyone could potentially access. Daniel, talk about your concerns around that or did you have concerns? And is that more of a governance people process question than a technology question, I think? Well, it's definitely a technology question, to a certain extent. I mean, as a transaction based business, we are obviously very concerned with security and our CTO is very adamant about that. And so that was one of the first issues that we addressed whenever we decided to go this route. And obviously AWS has taken all the precautions. We have a very similar setup to what Adam is describing as far as our security. We are very much confident that it is a very robust solution. So, looking forward, how do you see your use of both the cloud and kind of analytics evolving? You know, one of the things we've been covering a lot is the, as use cases get more complex, you kind of, you've got to orchestrate more data flows. You've got to move data from more places. You mentioned, you know, you're using Attunity to do some of that replication from your transactional database and some Redshift. You know, what are some of the other potential data integration challenges you see yourselves facing as you kind of potentially get more complex deployments. You've got more data. Maybe you start using more services on Amazon. How do you look to tackle some of those data integration challenges? Let me start. That's a good question. One of the things we're trying to do inside of, you know, our organization is, I guess bring data from all the different sources that we have together. We have, you know, we use Salesforce for our sales team. We collect information from MailChimp from our digital marketing agency that we'd like to tile that information together. And so that's something we're working on. Attunity has been a great help there and their product development as far as their capabilities of bringing in information from other sources is growing. So that's, you know, we're confident that the demand is there and that the product will develop as we move forward. Well, I mean, it's interesting that we've got, you know, you two gentlemen up here, one with a kind of an on-premise to cloud deployment and one all in the cloud. So clearly, Attunity can kind of gap both those, the on-premise and cloud role, but also works in the cloud environment. Adam, why don't we, if you could talk a little bit about how you see this kind of evolving as you get more complex, maybe bring in more systems. Are you looking to bring in more data sources? Maybe even third-party data sources, outside data sources. How do you look at this evolving? Right. Presently, we do have a Mongo database, so we have other sources that we're doing now. There's talks of even trying to stick that in DynamoDB, which is a red Amazon offering, and that ties directly into Redshift, so we could load that data directly into that, using that key pair or however we want to use that type of data mark. But one of the things that we're trying to work out right now is just distribution and being agile, elasticity, we're trying to work those issues with our growing database. So our database grows rather large each month, so working on scalability is our primary focus, but other data sources, so we're looking at other database technologies that we can leverage in addition to SQL Server to help distribute that load. So we've got time just for one more question. I always like to ask when we get customers and users on if you can give some advice to other practitioners who are watching. So I mean, if you can give one piece of advice to somebody who might be in your position, they're looking, maybe they've got a non-premise data warehouse, or maybe they're just trying to figure out a way to make better use of their data. I mean, what would that be the one thing? Would it be a technology piece of advice? Maybe look to something like Redshift or in solutions like Atunity, but maybe it would be more of a cultural question around the use of data and that mindset of making data-driven decisions. What would that kind of one piece of advice be? If I could put you on the spot. Okay, I would say don't try to do it yourself when the experts have done it for you. I couldn't put it any more simpler than that. Very succinct, but very powerful. For me, my biggest takeaway would be just Redshift. I was kind of apprehensive to use it at first, because I was so used to other technologies, but we can do so much with Redshift now at half the cost. So, use what works. Pretty compelling, all right, fantastic. Well, Adam Haynes, Daniel Higock, thank you so much for joining us on theCUBE. Appreciate it. We'll be right back with our next guest. We're live here at AWS Reinvent in Las Vegas. You're watching theCUBE.