hi everybody we are live at AWS reinvents in Las Vegas I'm Jeff Kelly with Wikibon org you're watching the cube silicon angles premiere live broadcast we go out to the technology events and as John foyer likes to say extract the signal from the noise so being here at the AWS show we were talk we're going to talk to a lot of AWS customers here a lot about what they're doing in 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 a tix and Adam Cain's who's a data architect with federated sample welcome guys thanks for joining us on the cube Thanks your first time so we'll promise we'll make this as painless as possible so so you guys have a couple things in common we were talking beforehand some of the workflows are similar you work your 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 for 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 tell us a little bit about etix kind of what you guys do and then we'll just kind of get into the use cases and talk to use AWS and the tuner need some of the other technologies you use it sure yeah so the company I work for is etix we are a primary market ticketing company in the entertainment industry we provide a box office solutions to venues and venue owners all types of events casinos fairs festivals pretty much you name and we sell some tickets in that industry we we provide a software solution that enables those menu owners to engage their customers and sell tickets so could kind of a competitor to something like ticketmaster the behemoth in the industry and you're definitely so Ticketmaster would be the behemoth in the industry and we are we consider ourselves a smaller sexier version that more friendly to the customer customer friendly more agile absolutely so Adam tell us a little bit about better a sample sure federated sample is a technology company in the market research industry and 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 surveys try to make that a more seamless process so they don't have to go out and find your very respond right everything online and right right absolutely got it so 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 and I'm gonna start with you what kind of brought you to AWS are you using red shift and I think you mentioned you're all in the cloud right just give us your impressions of the show in AWS and what that's meant your business right shows been great so far as to we were originally on-premise entirely at 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 need 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 you know redshift and so the idea being you're moving data from your transactional system which is also on AWS into redshift so using attunity for that they're clapping solution talk a little bit about that and and you know how that is differentiate from some of the other integration methods you could have chosen right so we started with a more conventional integration method a homegrown solution to move our data from our production sequel 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 could configure it know how to use it so then we saw cloud being from attunity and they offered a native solution using secret survey replication that could tie into our native sequel server and then push that data directly into cloud being at a very fast rate so moving that data from from the sequel server it is essentially a real-time replication so that yes that's moving that data into redshifts of the year analysts can actually write when they're doing there the 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 secret service right actual system right yeah nearly real-time and just to put in perspective the reports that we were running on our other system we're taking you know 10 15 minutes to run in redshift we're running those same reports in minutes 1 12 minutes right and if you're running those reports so quickly you know the people sometimes forget when you're talking about you know real time or interactive queries and reporting it's somewhat only as good as the data timeliness that you've got that you by Dave the timeless of the data you've got in that database because right trying to make some real-time decisions you've got a lag of depending on the workload and your use case even 15 minutes to an hour back might really impact you're ready to make those decisions so Adam talk a little bit about your use case is it is a similar cloud cloud architecture are you moving from upside Daniel moving from on-premise to so you're actually working with an on-premise data center it's an Oracle database and so we've basically we we ran into two limitations one regarding to our current reporting infrastructure and then to 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 you know inform our our different teams or operations teams our marketing teams so that has been one of the kind of BI lms that we've been able to achieve because of the replication and the redshift and then the 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 be able to do to run on our on-premise transactional database so really we just are kind of embracing the power of redshift and it's enabling us and a lot of different types of ways yeah i mean we're hearing a lot about red shift at the show it's the amazon says the fastest-growing service AWS has had from a revenue perspective and it's six seven year history so clearly there's a lot of power in that platform it removes a lot of the concerns around having to manage that infrastructure obviously but the performance you know that's that's something I think when people are have their own data centers their own databases tuning those for the type of performance you're looking for is can be a challenge is that one of the drivers to kind of your move to redshift oh for sure the performance i I'm trying to think of a good example of a metric to compare but it's 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 time frame is very important for reporting purposes and if you're not able to meet a certain time frame then 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 a tea tix you're talking about customer transactions your custom are you 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 to red shift and then you know what are some of those types of analytic workloads what kind of insights are you looking for sure so you know we're in the business of selling tickets and so one of our you know main concerns or I guess you 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 as you know easy to do in red shift and so we're able to use that information transaction information customer information I guess better engage our fans and likewise Adam could you maybe walk us through kind of a use case maybe your types of data you're looking at right that you're moving into red ship with attunity and then you know what kind of analytics are you doing on top of that what kind of insights are you gathering right so are our date is a little bit different than then ticketing but what we ultimately capture is is a respondent 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 reads 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 and 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 you know beyond that you know one of the topics we've been covering on the cube another 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 business objects and cognos that others but really I mean if you look at a typical enterprise business intelligence usage or adoption rate kind of stalls out by eighteen percent twenty percent 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 have to happen or some of the types of tools that are needed to really make business intelligence more consumable for analysts and more business use people who are not necessarily trained in statistics aren't data scientists Adam we start yes so one of the things that we're doing is with our jaspersoft we're trying to figure out you know certain we have a pis and we have traditional you know client server applications which ones our customers want to use the most because we're trying to push everybody towards an API oriented so we're trying to put that data into redshift with Jasper soft 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 others are rather than 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 they could 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 as a similar experience you're having any text definitely and I think one of the things I should emphasize about our use of Jasper's off 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 5-10 minutes of trying to launch it yeah it's pretty amazing what 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 bitten telligence but the whole datawarehousing world it was you know the traditional method is you you know the business user a business unit goes to IT they say here are some of the requirements of the metrics we want on these reports IT then gun it 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 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 their other database products and whatever bi to used to use is that kind of how you see this evolving oh definitely and the options I guess the the kind of plug and play workflow is is pretty pretty amazing and it's a 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 there's a chance we may decide there's something different in the future that we want to use and plugin in its place we're confident that that product will be there whenever the you know whenever the need is there right well that's the other thing you can you can start to use a tool and if it doesn't meet your need you can stop using it move to another tool so I think that puts you know vendors like jaspersoft than others puts them on their toes they've got to continually innovate and make their product useful otherwise you know they know that you know there were AWS customers can simply press the button stop using it press another button stop start using another tool so I think it's good in that sense but kind of you know 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 is your data but you know it's on there 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 so that was one of the major concerns up front but you know after talking with Amazon and going through the whole process of migrating to we kind of feel way more comfortable with that if you expand on that a little so you've got a private instance essentially in amazon's rep right so we have a private subnet so it's a segmented piece of their network that's just for us okay 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 that everybody else interesting so they offer that kind of type of service when there's more privacy concern as a security concern definitely and of course a lot depends on the type of data i mean how sensitive that data is if it you know but personally identifiable data obviously is going to be more sensitive than if it's just a general market data that anyone could potentially access daniel is we'll talk about your concerns around that or did you have concerns definitely a more of a governance people process question than a technology question I think well I definitely a technology question to a certain extent I mean as a as a transaction based business we were obviously very concerned with security and our CTO is very adamant about that and so that was one of the first first issues that we address whenever we decided to go this route and I'm obviously AWS has has taken all the precautions we have a very similar set up 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 case to get more complex your kind of you've got to orchestrate more data flows you've got to move data for more places you mentioned you're using attunity to do some of that replication from your transactional database and some red shift you know what are some of the other potential data integration challenges you see fate you see yourselves facing as you kind of potentially get more complex deployments we've got more data maybe you start using more services on Amazon how do you look to tackle some of those eight 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 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 they're you know they're their product development as far as their capabilities of bringing in information from other sources is growing so that's a you know we're confident that the demand is there and that the product will develop as we 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 a on premise to cloud deployment and one all in the cloud so I'm clearly tuning you can kind of gap both those right on premise and cloud roll but also work in the cloud environment Adam when 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 are you how do you look at this evolve right President Lee 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 dynamo DB which is a reg 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 data Mart but one of the things that we're trying to work out right now is just distribution and you know being agile you know elasticity which I work those issues with our growing database so so our database grows rather large each month so working on scalability is our primary focus but other data sources so we look into other database technologies that we can leverage in addition to sequel server to help distribute that load you so we've got time just for one more question I wonder I always like to ask when we get customers and users on if you can give some advice to other practitioners for watching so I mean if you can give one piece of advice to somebody who might be in your position they're looking at maybe they've got an on-premise data warehouse or maybe they're just trying to figure out a way to to get make better use of their data I mean what would the we the one thing would it be a technology piece of advice maybe you know looked at something like red shift or and solutions like attunity but maybe it would be more of a you know cultural question around the use of data and I'm I instead of making data-driven decisions but with that kind of one piece of ice big 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 I couldn't put it any more simpler than that very succinct but very powerful but for me my biggest takeaway would be just redshift I was kind of apprehensive to use it at first I was so used to other technologies but we can do so much with redshift now add you know half the cost so your good works pretty compelling all right fantastic well Adam pains Daniel heacock thank you so much for joining us on the cube appreciate it we'll be right back with 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