>> Live, from Orlando, Florida. It's theCUBE! Covering Enterprise Connect 2019. Brought to you by Five9. >> Welcome back to Orlando at Enterprise Connect 2019, I'm Lisa Martin with Stu Miniman. It may sound like we're at a party, this is the buzz of the event, this is day one, and we have had a great day so far of talking with lots of guests. We're welcoming back to theCUBE an alumni, Jim Lundy, see applause for you, Jim, CEO of Aragon Research, welcome back to theCUBE. >> Thank you, great to be here. [Lisa] - That was cute, by the way, so I hope we get some credit for that. >> Yeah, yeah, very cute. >> So Jim, you have been coming to Enterprise Connect since before it was even branded Enterprise Connect, back when it was VoiceCon. Tell us a little bit about your observations about the evolution, not only of the events, but also of all the collaboration and communication tools that consumers now are expecting and demanding of businesses. >> So, I think my first event was called VoiceCon in '07, and then it was all about phones. There was no software here. There was no video. There was no messaging. There was certainly no AI. And there were a lot of the players were not here, they were not in business then. So, if you actually look at some of the bigger players here today, they did not exist in 2007. So you look at the advent of Cloud, that's powered a whole new generation of services and opportunities, and it's great for buyers because there's so much more choice. So, VoiceCon almost died and they rebranded it but they've had to expand their focus. There's still a lot of voice focused stuff, but as you can see it's really shifted, we think it's shifting to communications and collaboration, we think contact center, particularly Cloud, is hot. We've got through overall Tam for communication, collaboration, contact center, by 2024, about 120 billion dollars, which makes it bigger than Enterprise secured. >> Yeah, we just had a great type-in with Blair Pleasant, and said, I'm a new channel, absolutely is where it is, but voice is still the number one preferred channel, when you talk about context center, there's lots of ways you can get in touch, but when something's wrong, I want to pick up my device and talk to a human eventually, so yeah, Cloud, and AI, and everything else, but there's still people in this center of everything going on here. >> Well, I think one of the things for contact center in particular you mentioned is the power of Cloud. So you look at some of the players here like we're in the Five9 booth, they've grown because of their Cloud focus, and Cloud is a lot of what's powering everybody here. And buyers want flexibility, so I think that's one of the big things that's changed, is there's still a lot of On Premise, and hybrid Cloud, but the power and the demand for 'I want to deploy something fast, and maybe I'm not even that big of a shop,' Cloud gives me that flexibility. >> When I look at the market as a whole, there's all those arguments about it's private Cloud, public Cloud, hybrid Cloud, multi Cloud, but if we think of Cloud as an operational model, and not a place, I want speed, I want to be able to update to my latest thing, whether that's for security or the cool new feature, and if I'm not Cloud, or Cloud-like, then I probably install something and what I do now and what I do a few years from now looks pretty close to what I did when I installed it. No? Does that resonate in this phase? >> Yeah, yeah. I think there's a couple things, also there's the operational nature of do I want to be in the server update business? Some people do, because of the nature of their business, but a lot of people don't. So then I can focus on the client experience, providing better journeys, and I think that's up the game. I think there's an awful lot of competition in this market because, really because of Cloud, but On Premise or private Cloud is not a bad word, and like I said, I think the bigger play is to be able to do a combination of things and meet the needs of the customer. The only thing I would say about the show is there's a lot of feature wars at this show and needs to be maybe a little more focused on what the customer needs versus hey, my box is better than your box. >> On that front, in terms of focusing on the customer experience, we talk a lot about that, there's a lot of the messaging and branding around the shows you were just pointing out, but something that is always interesting is where does a company balance the customer experience with the agent experience, because the customer experience is directly related to the agents being in power. >> Oh, totally! Well, you got to really do both and do both well. If the agent can't do their job, then the customer is not going to have a good experience. I do think that overall, there's been a pretty good focus on the agent, because that's where it kind of all started, and if you really look at contact center, it's really a heavy-duty application. You've got to be able to do all those things to service the inbound calls or inbound messages, and you're right, there is a lot of focus on the customer, because in some cases there is so much focus on the agent, well, we took the calls even though a lot of the calls, 10% might've gone to voicemail? Sometimes? Well, we serviced it, so. Little unknown fact is that in a lot of enterprises, marketing and the contact center group never talk. Interesting opportunity. >> Yeah, Jim, it's interesting, you talked about in tech we often get to that feature battle. Battle by power point or by product stack and oh, I've got 147 features and they only have 125 features, when you look at most customers they only know how to use three of the features they've got on there. So what differentiates from a customer standpoint, how do they choose, how do they make sure that they get something that is going to help their overall customer experience, and help their products and their marketing? >> Well, a couple things. First of all, you're right, they don't care as much about 'I've got this feature, you don't', they want to know can the provider take care of me if I buy from them? Are they reputable? Do other people, are they happy with the service? We do a lot of vender evaluations, we call them Aragon research globes and we usually spend six months working on understanding where the vender is this year, and we talk to references and things like that. So I think that sometimes when you, they read a report and they get some insight, they still want to talk to somebody versus just reading a peer review on somebody's consumer website, and really get that insight, so I think that's one lens and I think the other lens is that the smarter players are doing those things where they can provide really high touch support, I'd probably say Five9's pretty good at that, because contact center is really, really complicated, you just don't turn them on sometimes, there's things you have to do to make them work, and I think overall in this space, there are some products you can buy, maybe not contact center where you can spin them up and turn them, configure phones and go, I've actually deployed some of them, and there's some that would be such a nightmare, like who in the world would ever buy this product? So, I think it really varies a gambit and again, sometimes that doesn't always come out with an online review and again, sometimes the buyer, still buyer beware, in a lot of cases, some of the things you read online are not true. >> One of the things we were chatting with a number of the Five9 executs about today is that they have a five billion recorded customer conversations, tremendous potential there to really glean actionable insights about retaining that customer, increasing their CLV, but there's also the concern of data privacy and security in sharing, when you're talking with customers that might have this massive pull of data from which they can really expand their business and become competitive, where is the security and the privacy concerns there? >> It's a good question. There's a lot of focus on GDPR in Europe, there's a lot of focus in California on that, even though there's not been talked about in California. The rest of the US is kind of behind a little bit what Europe has done, but here's the thing. They've got ways to mass sensitive data in a recording like credit card data, that's pretty standard stuff, the big thing is data residency. I want my data in a certain country, Canadians do not want their data resident in the United States, Europeans don't either. Germans don't want their data resident in Belgium, so there's a big sensitivity in Europe about that, and even in fact, Microsoft's even gotten in trouble in Germany over that last year, because they eliminated a relationship with Doy to Telecom, sometimes you can kind of go overboard on that, but however, what I would say though is, some of the big Cloud companies have done this, brought this problem onto themselves, where they have not respected data privacy, there's even a bill now on facial recognition, because of some of the things that have gone on like IBM disclosed, they're doing something, so it is still an issue, it's always going to be an issue, I do think that there needs to be more protect, but here's the question. Who owns your data? Who owns your face, or my face? I don't think that because I upload a photo that I should give my rights away. I think we're going to catch up on that, I do think for the B-to-B though, a lot of these companies, first of all, they are certified, they have Cloud certifications, they definitely do certain things relative to privacy, and so they have to pass a lot of tests that are certified by an auditor, so I think there's a lot of things that most of the B-to-B buyers are not going to have to worry about with a lot of the people here, it's more of the personal side of things, the personal Cloud, Facebook, but usually not the kind of stuff you're dealing with here. >> So, Jim, when I look at the overall contact center market, the Cloud portion of that is still relatively small, if I saw right somewhere, 10, 15%, but it's been growing at a steady clip, where are we in their adoption, is there a plateau that it will hit that, is it take a third of a market, half the market, what do you see happening? >> I would say, we're on a journey and you're right, there is still a small part, which means the large address will market, not that much different than unified communications where it's mainly On Premise, going Cloud. We've got contact center going about 24 billion, and we think a lot of that will be eventually converted to a Cloud, except for maybe the ultra, ultra large call centers, and I think just like email migration 10 years, I've covered that, 10 years ago it was all On Premise. Today it's the opposite. It's like 90-10. So I think that eventually is going to start to happen. >> It's interesting, a lot of that was Microsoft really turned the lever, Microsoft on email, and Microsoft is like, we're going sass, you are going sass if you use Office, you are going Office 365. So I'm curious, is there a lever like that from a licensing standpoint or from a vender standpoint, that would push contact center? >> If you look at the contact center market, we've got it, growth rates around 9% overall, but then you've got people like Five9 that are growing 31%, alright? So if you starting looking at that, why is a Cloud company growing that much when the overall market, well because there's demand. They want the flexibility of Cloud, they don't want to run the servers and upgrade the servers, and I think that they've learned lessons from that, and you're right, Microsoft did do that, but Google forced them to do that. So I think that, are fast growing companies like Five9 forcing some of the bigger players to go more Cloud? And I can say absolutely yes, that a lot of the bigger players are looking over their shoulders saying, and they bought Cloud contact center players so they can keep up with some of the young startups, and Five9's not young, but they would still be considered young in the relative terms of this event. >> I'm curious, Jim, when you're talking with venders and the Aragon research that you do, companies of different sizes, whether they're born in the Cloud or they're legacy companies, where does cultural transformation come into this conversation about evolving a contact center such that an agent is empowered with the right content to deliver it through the right channel, to make a decision that really positively impacts the customer? I can imagine multiple generations, multiple countries, cultural transformation is hard. >> It is a big issue, I think there's more awareness on both the culture of the agent and the culture of the buyer, and I think there's more stuff going on relative to sentiment, sentiment analysis. I do think that's a bigger issue, I think there's more time being spent on training, the better digital companies are investing tons of money in training, so I think there's more awareness relative to cultural differences, cultural nuances, and being more sensitive to maybe things that they would say sorry, can't help you with that, since they've been trained to be maybe more sensitive, they're going to be more understanding when they're actually on a call. >> So, Jim, in your research, where's the white space? Where's the real opportunity for growth and transformation, we've had some discussions here, it's early days in AI's, at AI, or is it not the technology, is it the cultural changes, that Lisa brings up, where are some of impediments and room for growth in the industry? >> So we do think that the enterprise will become more intelligent, and that the providers are going to lead that charge, where instead of you say to AI, we call it intelligent contact center, and we think that there's going to be more of a demand for automation, and that there will be more assistance that might take care of a customer's problem before it ever gets to a human. I do think that we're not going to, that's going to be something that's never going to go away, it's just that they're going to get smarter and more supportive. We have helped clients deploy chat bots for help desk internally for customer facing help desk, I think it's still early here, that people have them, but they're more rules based than AI based. AI's coming in the next two years but there's no doubt that is going to be one of the drivers, and by the way, sometimes people be like, is this the problem we were having, is this the question you have? Yes. Here's this answer, and it's the right answer, the correct answer, that's what people really want, they want the instant gratification, we all kind of grew up, we were used to that with our phones, I need the answer, and I do think that I would probably say the demand for Cloud is going to out-strip everything, so if somebody that's an On Premise provider doesn't have a Cloud option, then I would be worried about them. But I do think AI is not going to go away, we don't think it's going to be an AI or nothing, it's going to be basically intelligent digital assistance, it can answer questions intelligently and have a conversation with you, there's some tools that do that today, but most of them are very basic question and answer, they're not high-end, it can't be like Jarvis on Iron Man, where yes, yes, Mr. Spark, I will do that for you, they're not quite there yet, but the movies glamify that whole thing. Some people expect, well, why doesn't it talk back to me? >> Any last questions, Jim, are there any industries that you see is going to be early adopters to start creating and actually deploying the intelligent contact center? >> Well, let's put it this way. Every client we've talked to in survey work said we wish we had more intelligence in our contact center. I think they're a little scared that they want to make sure they do it right, but if you do it and deploy it and test it, you'd be amazed it's for some of the basic Q&A, how rockstar stuff that is, but sometimes people rush too quickly and deploy it when it's not quite ready. I think a lot of the providers here, including Five9, are going to try to do AI the right way, and not try to rush it, but I would also say this. There's an awful lot of fud about AI, and most of it's not true. >> Lisa, final, final question for Jim here, since John Ferger's not here to ask it, Five9's gone through a lot of changes here, brought in some pretty high-profile executives, any commentary on our host here? >> Look, I knew Rowan and Jonathan Rosenberg at Cisco, they had a rockstar team there, they've even, since they've joined here brought more talent in, and so, the Five9 people I knew have been blown away by the level of talent that has come in, and I think that's just going to help them continue to grow. The question is, when did they declare how big they're going to be? And that's what we're looking for them to do. >> To be continued, Jim, thanks so much for joining Stu and me on theCUBE this afternoon. >> Thank you very much. >> For Stu Miniman, I'm Lisa Martin, you're watching theCUBE. (light beat music)

okay welcome back to IBM's information on demand live in Las Vegas this is the cube SiliconANGLE movie bonds flagship program we go out to the events it's check the student from the noise talk to the thought leaders get all the data share that with you and you go to SiliconANGLE com or Wikibon or to get all the footage and we're if you want to participate with us we're rolling out our new innovative crowd activated innovation application called crowd chat go to crouch at net / IBM iod just login with your twitter handle or your linkedin and participate and share your voice is going to be on the record transcript of the cube conversations I'm John furrier with silicon items with my co-host hi buddy I'm Dave vellante Wikibon dork thanks for watching aren't you Oh bhambri is here she's the vice president of big data and analytics at IBM many time cube guests as you welcome back good to see you again thank you so we were both down at New York City last week for the hadoop world really amazing to see how that industry has evolved I mean you guys I've said the number of times today and I said this to you before you superglued your your big data or your analytics business to the Big Data meme and really created a new category I don't know if that was by design or you know or not but it certainly happened suddenly by design well congratulations then because because I think that you know again even a year a year and a half ago those two terms big data and analytics were sort of separate now it's really considered as one right yeah yeah I think because initially as people our businesses started getting really flooded with big data right dealing with the large volumes dealing with structured semi-structured or unstructured data they were looking at that you know how do you store and manage this data in a cost-effective manner but you know if you're just only storing this data that's useless and now obviously it's people realize that they need and there is insights from this data that has to be gleaned and there's technology that is available to do that so so customers are moving very quickly to that it's not just about cost savings in terms of handling this data but getting insights from it so so big data and analytics you know is becoming it's it's becoming synonymous heroes interesting to me on Jules is you know just following this business it's all it's like there's a zillion different nails out there and and and everybody has a hammer and they're hitting the nail with their unique camera but I've it's like IBM as a lot of different hammers so we could talk about that a little bit you've got a very diverse portfolio you don't try to force one particular solution on the client you it sort of an it's the Pens sort of answer we could talk about that a little bit yeah sure so in the context of big data when we look at just let's start with transactional data right that continues to be the number one source where there is very valuable insights to be gleaned from it so the volumes are growing that you know we have retailers that are handling now 2.5 million transactions per hour a telco industry handling 10 billion call data detailed records every day so when you look at that level that volume of transactions obviously you need to be you need engines that can handle that that can process analyze and gain insights from this that you can get you can do ad hoc analytics on this run queries and get information out of this at the same speed at which this data is getting generated so you know we we announced the blu acceleration rate witches are in memory columnstore which gives you the power to handle these kinds of volumes and be able to really query and get value out of this very quickly so but now when you look at you know you go beyond the structured data or beyond transactional data there is semi structured unstructured data that's where which is still data at rest is where you know we have big insights which leverages Apache Hadoop open source but we've built lots of capabilities on top of that where we get we give the customers the best of open source plus at the same time the ability to analyze this data so you know we have text analytics capabilities we provide machine learning algorithms we have provided integration with that that customers can do predictive modeling on this data using SPSS using open source languages like our and in terms of visualization they can visualize this data using cognos they can visualize this data using MicroStrategy so we are giving customers like you said it's not just you know there's one hammer and they have to use that for every nail the other aspect has been around real time and we heard that a lot at strada right in the like I've been going to start us since the beginning and those that time even though we were talking about real time but nobody else true nobody was talking nobody was back in the hadoop world days ago one big bats job yeah so in real time is now the hotbed of the conversation a journalist storm he's new technologies coming out with him with yarn has done it's been interesting yeah you seen the same thing yeah so so and and of course you know we have a very mature technology in that space you know InfoSphere streams for a real-time analytics has been around for a long time it was you know developed initially for the US government and so we've been you know in the space for more than anybody else and we have deployments in the telco space where you know these tens of billions of call detail records are being processed analyzed in real time and you know these telcos are using it to predict customer churn to prevent customer churn gaining all kinds of insights and extremely high you know very low latency so so it's good to see that you know other companies are recognizing the need for it and are you know bringing other offerings out in this space yes every time before somebody says oh I want to go you know low latency and I want to use spark you say okay no problem we could do that and streets is interesting because if I understand it you're basically acting on the data producing analytics prior to persisting the data on in memory it's all in memory and but yet at the same time is it of my question is is it evolving where you now can blend that sort of real-time yeah activity with maybe some some batch data and and talk about how that's evolving yeah absolutely so so streams is for for you know where as data is coming in it can be processed filtered patterns can be seen in streams of data by correlating connecting different streams of data and based on a certain events occurring actions can be taken now it is possible that you know all of this data doesn't need to be persisted but there may be some aspects or some attributes of this data that need to be persisted you could persist this data in a database that is use it as a way to populate your warehouse you could persist it in a Hadoop based offering like BigInsights where you can you know bring in other kinds of data and enrich the data it's it's like data loans from data and a different picture emerges Jeff Jonas's puzzle right so that's that that's very valid and so so when we look at the real time it is about taking action in real time but there is data that can be persisted from that in both the warehouse as well as on something like the insides are too I want to throw a term at you and see what what what this means to you we actually doing some crowd chats with with IBM on this topic data economy was going to SS you have no date economy what does the data economy mean to you what our customers you know doing with the data economy yes okay so so my take on this is that there are there are two aspects of this one is that the cost of storing the data and analyzing the data processing the data has gone down substantially the but the value in this data because you can now process analyze petabytes of this data you can bring in not just structured but semi-structured and unstructured data you can glean information from different types of data and a different picture emerges so the value that is in this data has gone up substantially I previously a lot of this data was probably discarded people without people knowing that there is useful information in this so to the business the value in the data has gone up what they can do with this data in terms of making business decisions in terms of you know making their customers and consumers more satisfied giving them the right products and services and how they can monetize that data has gone up but the cost of storing and analyzing and processing has gone down rich which i think is fantastic right so it's a huge win win for businesses it's a huge win win for the consumers because they are getting now products and services from you know the businesses which they were not before so that that to me is the economy of data so this is why I John I think IBM is really going to kill it in this in this business because they've got such a huge portfolio they've got if you look at where I OD has evolved data management information management data governance all the stuff on privacy these were all cost items before people looked at him on I gotta deal with all this data and now it's there's been a bit flip uh-huh IBM is just in this wonderful position to take advantage of it of course Ginny's trying to turn that you know the the battleship and try to get everybody aligned but the moons and stars are aligning and really there's a there's a tailwind yeah we have a question on domains where we have a question on Twitter from Jim Lundy analyst former Gartner analyst says own firm now shout out to Jim Jim thanks for for watching as always I know you're a cube cube alum and also avid watcher and now now a loyal member of the crowd chat community the question is blu acceleration is helps drive more data into actionable analytics and dashboards mm-hmm can I BM drive new more new deals with it I've sued so can you expound it answers yes yes yes and can you elaborate on that for Jim yeah I you know with blu acceleration you know we have had customers that have evaluated blue and against sa bihana and have found that what blue can provide is is they ahead of what SI p hana can provide so we have a number of accounts where you know people are going with the performance the throughput you know what blue provides is is very unique and it's very head of what anybody else has in the market in solving SI p including SI p and and you know it's ultimately its value to the business right and that's what we are trying to do that how do we let our customers the right technology so that they can deal with all of this data get their arms around it get value from this data quickly that's that's really of a sense here wonderful part of Jim's question is yes the driving new deals for sure a new product new deals me to drive new footprints is that maybe what he's asking right in other words you traditional IBM accounts are doing doing deals are you able to drive new footprints yeah yeah we you know there are there are customers that you know I'm not gonna take any names here but which have come to us which are new to IBM right so it's a it's that to us and that's happening that new business that's Nate new business and that's happening with us for all our big data offerings because you know the richness that is there in the portfolio it's not that we have like you were saying Dave it's not that we have one hammer and we are going to use it for every nail that is out there you know as people are looking at blue big insights for her to streams for real time and with all this comes the whole lifecycle management and governance right so security privacy all those things don't don't go away so all the stuff that was relevant for the relational data now we are able to bring that to big data very quickly and which is I think of huge value to customers and as people are moving very quickly in this big data space there's nobody else who can just bring all of these assets together from and and you know provide an integrated platform what use cases to Jim's point I don't you know I know you don't want to name names but can you name you how about some use cases that that these customers are using with blue like but use cases and they solving so you know I from from a use case a standpoint it is really like you know people are seeing performance which is you know 30 32 times faster than what they had seen when they were not using and in-memory columnstore you know so eight to twenty five thirty two times per men's gains is is you know something that is huge and is getting more and more people attracted to this so let's take an industry take financial services for example so the big the big ones in financial services are a risk people want to know you know are they credit risk yeah there's obviously marketing serving up serving up ads a fraud detection you would think is another one that in more real time are these these you know these will be the segments and of course you know retail where again you know there is like i was saying right that the number of transactions that are being handled is is growing phenomenally i gave one example which was around 2.5 million transactions per hour which was unheard of before and the information that has to be gleaned from it which is you know to leverage this for demand forecasting to leverage this for gaining insights in terms of giving the customers the right kind of coupons to make sure that those coupons are getting you know are being used so it was you know before the world used to be you get the coupons in your email in your mail then the world changed to that you get coupons after you've done the transaction now where we are seeing customers is that when a customer walks in the store that's where they get the coupons based on which i layer in so it's a combination of the transactional data the location data right and we are able to bring all of this together so so it's blue combined with you know what things like streams and big insights can do that makes the use cases even more powerful and unique so I like this new format of the crowd chatting emily is a one hour crowd chat where it's kind of like thought leaders just going to pounding away but this is more like reddit AMA but much better question coming in from grant case is one of the themes to you is one of the themes we've heard about in Makino was the lack of analytical talent what is going on to contribute more value for an organization skilling up the work for or implementing better software tools for knowledge workers so in terms so skills is definitely an issue that has been a been a challenge in the in the industry with and it got pretty compound with big data and the new technology is coming in from the standpoint of you know what we are doing for the data scientists which is you know the people who are leveraging data to to gain new insights to explore and and and discover what other attributes they should be adding to their predictive models to improve the accuracy of those models so there is there's a very rich set of tools which are used for exploration and discovery so we have which is both from you know Cognos has such such such capabilities we have such capabilities with our data Explorer absolutely basically tooling for the predictive on the modeling sister right now the efforts them on the modeling and for the predictive and descriptive analytics right I mean there's a lot of when you look at that Windows petabytes of data before people even get to predictive there's a lot of value to be gleaned from descriptive analytics and being able to do it at scale at petabytes of data was difficult before and and now that's possible with extra excellent visualization right so that it's it's taking things too that it the analytics is becoming interactive it's not just that you know you you you are able to do this in real time ask the questions get the right answers because the the models running on petabytes of data and the results coming from that is now possible so so interactive analytics is where this is going so another question is Jim was asking i was one of ibm's going around doing blue accelerator upgrades with all its existing clients loan origination is a no brainer upgrade I don't even know that was the kind of follow-up that I had asked is that new accounts is a new footprint or is it just sort of you it is spending existing it's it's boat it's boat what is the characteristic of a company that is successfully or characteristics of a company that is successfully leveraging data yeah so companies are thinking about now that you know their existing edw which is that enterprise data warehouse needs to be expanded so you know before if they were only dealing with warehouses which one handling just structure data they are augmenting that so this is from a technology standpoint right there augmenting that and building their logical data warehouse which takes care of not just the structure data but also semi-structured and unstructured data are bringing augmenting the warehouses with Hadoop based offerings like big insights with real-time offerings like streams so that from an IT standpoint they are ready to deal with all kinds of data and be able to analyze and gain information from all kinds of data now from the standpoint of you know how do you start the Big Data journey it the platform that at least you know we provide is a plug-and-play so there are different starting points for for businesses they may have started with warehouses they bring in a poly structured store with big inside / Hadoop they are building social profiles from social and public data which was not being done before matching that with the enterprise data which may be in CRM systems master data management systems inside the enterprise and which creates quadrants of comparisons and they are gaining more insights about the customer based on master data management based on social profiles that they are building so so this is one big trend that we are seeing you know to take this journey they have to you know take smaller smaller bites digests that get value out of it and you know eat it in chunks rather than try to you know eat the whole pie in one chunk so a lot of companies starting with exploration proof of concepts implementing certain use cases in four to six weeks getting value and then continuing to add more and more data sources and more and more applications so there are those who would say those existing edw so many people man some people would say they should be retired you would disagree with that no no I yeah I I think we very much need that experience and expertise businesses need that experience and expertise because it's not an either/or it's not that that goes away and there comes a different kind of a warehouse it's an evolution right but there's a tension there though wouldn't you say there's an organizational tension between the sort of newbies and the existing you know edw crowd i would say that maybe you know three years ago that was there was a little bit of that but there is i mean i talked to a lot of customers and there is i don't see that anymore so people are people are you know they they understand they know what's happening they are moving with the times and they know that this evolution is where the market is going where the business is going and where the technology you know they're going to be made obsolete if they don't embrace it right yeah yeah so so as we get on time I want to ask you a personal question what's going on with you these days with within IBM asli you're in a hot area you are at just in New York last week tell us what's going on in your life these days I mean things going well I mean what things you're looking at what are you paying attention to what's on your radar when you wake up and get to work before you get to work what's what are you thinking about what's the big picture so so obviously you know big data has been really fascinating right lots of lots of different kinds of applications in different industries so working with the customers in telco and healthcare banking financial sector has been very educational right so a lot of learning and that's very exciting and what's on my radar is we are obviously now seeing that we've done a lot of work in terms of helping customers develop and their Big Data Platform on-premise now we are seeing more and more a trend where people want to put this on the cloud so that's something that we have now a lot of I mean it's not like we haven't paid attention to the cloud but you know in the in the coming months you are going to see more from us are where you know how do we build cus how do we help customers build both private and and and public cloud offerings are and and you know where they can provide analytics as a service two different lines of business by setting up the clouds soso cloud is certainly on my mind software acquisition that was a hole in the portfolio and that filled it you guys got to drive that so so both software and then of course OpenStack right from an infrastructure standpoint for what's happening in the open source so we are you know leveraging both of those and like I said you'll hear more about that OpenStack is key as I say for you guys because you have you have street cred when it comes to open source I mean what you did in Linux and made a you know great business out of that so everybody will point it you know whether it's Oracle or IBM and HP say oh they just want to sell us our stack you've got to demonstrate and that you're open and OpenStack it's great way to do that and other initiatives as well so like I say that's a V excited about that yeah yeah okay I sure well thanks very much for coming on the cube it's always a pleasure to thank you see you yeah same here great having you back thank you very much okay we'll be right back live here inside the cube here and IV IBM information on demand hashtag IBM iod go to crouch at net / IBM iod and join the conversation where we're going to have a on the record crowd chat conversation with the folks out the who aren't here on-site or on-site Worth's we're here alive in Las Vegas I'm Java with Dave on to write back the q