(upbeat music) >> From around the globe, it's theCUBE with coverage of SUSECON Digital. Brought to you by SUSE. >> Welcome back. I'm Stuart Miniman coming to you from our Boston area studio and this is theCUBE coverage of SUSECON Digital 20. Happy to welcome to the program two of the keynote present presenters. First of all, we have Dr. Thomas Giacomo. He is the President of Engineering and innovation and joining him his co presenter from Makino state, Daniel Nelson, who is the Vice President of Product Solutions, both of you with SUSE. Gentlemen, thanks so much for joining us. >> Thank you. >> Thank you for having us. >> All right. So, Dr. T, Let's start out, innovation, open source, give us a little bit of the message for our audience that you and Daniel were talking about on stage. We've been watching for decades, the growth in the proliferation of open source communities, so give us the update there. >> Yeah. And then it's not stopping, it's actually growing even more and more and more and more innovations coming from open source. The way we look at it is that our customers there, they have their business problems, they have their business reality. And so we, we have to curate, and prepare and filter all the open source innovation that they can benefit from, because that takes time to understand how that can match your needs and fix problems. So at SUSE, we've always done that, since 27 plus years. So, working in the open source projects, innovating there but with customers in mind, and what is pretty clear in 2020 is that large enterprises, more startups, everybody's doing software, everybody's is doing IT and they all have the same type of needs in a way they need to simplify their landscape, because they've been accumulating investments all the way or infrastructure or software, different solutions, different platforms from different vendors. They need to simplify that. They need to modernize, and they need to accelerate their business stay relevant and competitive in their own industries. And that's what we are focusing on. >> Yeah, it's interesting, I completely agree when you say simplify thing, you know, Daniel, I go back in the opportunities about 20 years. And in those days, we were talking about the operating Linux was helping to go past the proprietary Unix platform, Microsoft, the big enemy. And you were talking about operating system, server storage, the application that on, it was a relatively simple environment in there compared to today's multi cloud, AI, container based architecture, applications going through this radical Information broke, though, gives a little bit of insight as to the impact this is having on ecosystems and, of course SUSE now has a broad portfolio that at all? >> It's a great question and I totally get where you're coming from, like, if you look 20 years ago, the landscape is completely different, the technologies we're using are completely different, the problems we're trying to solve with technology are more and more sophisticated. At the same time, though, there's kind of nothing new under the sun. Every company, every technology, every modality goes through this expansion of capabilities and the collapse around simplification as the capabilities become more and more complex and more manageable. So there's this continuous tension between capabilities, ease of use consume ability. What we see with open source is that, that kind of dynamic still exists, but it's more online of like developers want, easy to use technologies, but they want the cutting edge. They want the latest things. They want those things within their packages. And then if you look at operations groups or people that are trying to consume that technology, they want that technology to be consumable simple, works well with others be able to pick and choose and have one pane of glass to be able to operate within that. And that's where we see this dynamic. And that's kind of what the SUSE portfolio was built upon. It's like, how do we take the thousands and thousands of developers that are working on these really critical projects, whether it's Linux like you mentioned, or Kubernetes, or or Cloud Foundry? And how do we make that then more consumable to the thousands of companies that are trying to do it, who may even be new to open source or may not contribute directly, but when you have all the benefits that are coming to it, and that's where SUSE fits and where SUSE has fits historically, and where we see us continuing to fit long term is taken all those Legos, put into together for companies that want that, and then allow them a lot of autonomy and choice and how those technologies are consumed. >> Right, one of the themes that I heard you both talk about, in the keynote, it was simplifying, modernize, celebrate, really reminded me of the imperatives of the CIO. There's always run the business, they need to help grow the business, and if they have the opportunity, they want to transform the business. I think you said, run improve in scale. Scale absolutely a critical thing that we talk about these days, when I think back to the Cloud Foundry summit, in the keynote stage, it was the old way if I could do faster, better, cheaper, you could do them today. We know Faster, faster, faster is what you want. So give us a little bit of insight as to, you talked about Cloud Foundry and Kubernetes, application, modernization, what are the imperatives that you're hearing from customers and how are we, with all of these tools out there helping, IT, not just be responsive to the business but actually be a driver for that transformation of the business? >> It's a great question. And so when I talk to customers, and Dr. T, feel free to chime in, you talk to as many or more customers than I do. They do have these what are historically competing imperatives. But what we see with the adoption of some of these technologies is that faster is cheaper, faster is safer, creating more opportunities to grow and to innovate betters the business. It's not risk injection, when we change something, it's actually risk mitigation, when we get good at changing. And so it's kind of that modality of moving from, a simplified model or a very kind of like a manufacturing model of software to a much more organic, much more permissimuch more being able to learn within ecosystems model. And so that's how we see companies start to change the way they're adopting this technology. What's interesting about them is that same level of adoption. That same thought of adoption, It's also how open sources is developed. Open Source has developed organically, it's developed with many eyes make shallow bugs, it's developed by like, let me try this and see what happens, right? And be able to do that in smaller and smaller increments just like we look at Red Green deployments or being able to do micro services, or Canary or any of those things. It's like, let's not, do one greatly for what we're used to and waterfall is that's actually really risky. Let's do many, many, many steps forward and be able to transform it iteratively and be able to go faster iteratively and make that just part of what the business is good at. And so you're exactly right. Like those are the three imperatives of the CIO. What I see with customers is the more that they are aligning those three imperatives together and not making them separate, but we have to be better at being faster and being transformative. Those are the companies that are really using IT as a competitive advantage within their reach. >> Yeah, because most of the time they have different starting points. They have a history. They have different business strategy and things they've done in the past. So you need to be able to accommodate all of that and the faster microservice, native development posture for the new apps, but they're also coming from somewhere, and if you don't take care of that together, you can just accelerate if you simplify your existing because otherwise you spend your time making sure that your existing is running. So you have to combine all of that together, and the two, you mentioned Cloud Foundry and Kubernetes and I love those topics because, I mean, everybody knows about Kubernetes. Now it's picking up in terms of adoption, in terms of innovation technology, uilding AI ML framework on top of it. Now, what's very interesting as well is that, Cloud Foundry was designed for fast software development, and cloud native from the beginning that by the factor apps, and several like four or five years ago, right? What we see now is we can extract the value that Cloud Foundry brings to speed up and accelerate our software development cycles, and we can combine that very nicely and very smoothly simple in a simple way, with all the benefits you get from Kubernetes, and not from one Kubernetes. From your Kubernetes running in your public clouds because you have workloads there, you have services that you want to consume from one public clouds. We have a great SUSECON fireside chat with open shot from Microsoft. Asia, we're actually discussing those topics. Or you might have also Kubernetes clusters at the edge that you want to run in your factory or close to your data and workloads in the field. So those things and Daniel mentioned that as well taking care of the IT ops, like simplify, modernize and accelerate for the IT ops and also accelerate for the developers themselves, we benefiting from a combination of open source technologies. And today, there's not one open source technology that can do that. You need to bundle combine them together and best make sure that they are integrated, hat they are certified together, that they are stable together, that the security aspects, all the technology around them are deeply integrated into services as well. >> Well, I'm really glad you brought up some of those Kubernetes that are out there. We've been saying for a couple years on theCUBE, Kubernetes is getting baked in everywhere. SUSE's got partnership with all the cloud providers and you're not fighting them over whether to use a solution that you have versus theirs. I worry a little bit about, how do I manage all those environments? Do I end up with Kubernetes sprawl just like we have with every other technology out there? Help us understand what differentiates SUSE's offerings in this space? And how do you fit in with the rest of that very dynamic and diverse. >> So, let me start with the aspect of combining things together. And Daniel, maybe you can take the management piece. So, first of all, we are making sure at SUSE that we don't force our customers into a SUSE stack. Of course we have a SUSE stack, and we're very happy people use it. But the reality is that the customer knows that they have some investments, they have different needs, they use different technologies from the past, or they want to try different technologies. So you have to make sure that for Kubernetes like for any other part of the stack, the IT stack or the developer stack, your pieces are our modular that you can accommodate different different elements. So typically, at SUSE, we support different types of hypervisors We're not like focused on one but we can support KVM, Xen, Hyper-V, vSphere, all of the nutanix hypervisor, NetApp hypervisors and everything. Same thing with the OS, there's not only one Linux that people are running, and that's exactly the same with kubernetes. There's no one probably that I've seen in our customer base that will just need one vendor for Kubernetes because they have a hybrid cloud needs and strategy and they will benefit from the native Kubernetes they found on AKA, CKA, SDK, Alibaba clouds, you name them and we have cloud vendors in Europe as well doing that. So for us, it's very important that what we bring as SUSE to our customers can be combined with what they have, what they want, even if it's from the so called competition. And so the SUSE Cloud Foundry is running on. I guess, you can find it on the marketplace of public clouds. It could run on any Kubernetes. It doesn't have to be SUSE Kubernetes. But then you end up with a lot of cells, right? So how do we deal with that then? >> So it's a great question. And I'll actually even broaden that out because it's not like we're only running Kubernetes. Yes, we've got lots of clusters, we've got lots of containers, we've got lots of applications that are moving there. But it's not like all the VMs disappeared. It's not like all the beige boxes, like in the data center, like suddenly don't exist. We all bring all the sins and decisions of the past board with us wherever we go. So for us, it's not just that lens of how do we manage the most modern, the most cutting edge? That's definitely a part of it. But how do you do that within the context of all the other things you have to do within your business? How do I manage virtual machines? How do I manage bare metal? How do I manage all those. And so for us, it's about creating a presentation layer. On top of that, where you can look at your clusters, look at your VMs, look at all your deployments, and be able to understand what's actually happening within your environment. We don't take a prescriptive approach. We don't say you have to use one technology or have to use that technology. What we want to do is to be adaptive to the customer's needs. And say you've got these things. Here's some of our offerings. You've got some legacy offerings too. Let's show you how to bring those together. Let's show you how you modernize your viewpoints, how you simplify your operational framework and how you end up accelerating what you can do with the stuff that you've got in place. >> Yeah, I'm just on the management piece. Is there any recommendations from your team? Last year at Microsoft Ignite, there was a launch of Azure Arc, and, we're starting to see a lot of solutions come out there. Our concern is that any of us that live through the multi vendor management days, don't have good memories from those. It is a different discussion if we're just talking about kind of managing multiple Kubernetes. But, how do we learn from the past? And, what, what are you recommending for people in this multi cloud era? >> So my suggestion to customers is you always start with what are your needs, what is strategic problems you're trying to solve. And then choose a vendor that is going to help you solve those strategic problems. So isn't going to take a product centric view. Isn't going to tell you, use this technology and this technology and this technology, but it's going to take the view of like, this is the problem you're going to solve. Let me be your advisor within that and choose people that you're going to trust within that. That being said, you want to have relationships with customers that have been there for a while that have done this that have a breadth of experience in solving enterprise problems. Coz, I mean, everything that we're talking about, is mostly around the new things. But keep in mind that there are nuances about the enterprise, there are things that are that are intrinsically found within the enterprise, that it takes a vendor with a lot of experience to be able to meet customers where they are. I think you've seen that in some of the real growth opportunities within the hyper scalars. They've kind of moved into being more enterprise, view of things, kind of moving away from just an individual bill perspective to enterprise problems. You're seeing that more and more. I think vendors and customers need to choose companies that meet them where they are, that enable their decisions, not prescribe their decision. >> Okay. Oh-- >> Let me just add to that. >> Please go ahead. >> Yeah, sorry. Yeah. I also wanted to add that I would recommend people to look at open source based solutions because that will prevent them to be in a difficult situation potentially, in a few years from now. So there are open source solutions that can do that. And look at viable, sustainable, healthy open source solutions that are not just one vendor, but multi vendor as well, because that leaves doors options open for you in the future as well. So if you need to move for another vendor, or if you need to complement with an additional technology, or you've made a new investment or you go to a new public cloud, if you base your choices on open source, you have a better chance but from a data. >> I think that's a great point, Dr. T, and I would glom on to that by saying, customers need to bring a new perspective on how they adjudicate these solutions. Like it's really important to look at the health of the open source community. Just because it's open source doesn't mean that there's a secret army of gnomes that you know, in the middle of the night go and fix box, like there needs to be a healthy community around that. And that is not just individual contributors. That is also what are the companies that are invested in this? Where are they dedicating resources? Like that's another level of sophistication that a lot of customers need to bring into their own vendor selection process. >> Excellent. Speaking about communities and open ports, want to make sure you have time to tell us a little bit about the AI platform discussed. >> Yeah, it's it's very, very interesting and something I'm super excited about it SUSE. And it's kind of this, we're starting to see AI done and it's really interesting problems to solve. And like, I'll just give you one example, is that we're working with a Formula One team around using AI to help them actually manage in car mechanics and actually manage some of the things that they're doing to get super high performance out of their vehicles. And that is such an interesting problem to solve. And it's such a natural artificial intelligence problem that even then you're talking about cars instead of servers or you're talking about racing stack instead of data centers, you still got a lot of the same problems. And so you need an easy to use AI stack, you need it to be high performance, you need it to be real time, you need to be able to get decisions made really quickly. These are the same kinds of problems. But we're starting to see them in all these really interesting real world scenarios, which is one of the coolest things that I've seen in my career, especially as it turns of IT, is that IT is really everywhere. It's not just grab your sweater and go to the data centre, because it's 43 degrees in there, it's also get on the racetrack, it's also go to the airfield, it's also go to the grocery store and look at some of the problems being addressed and solved there. And that is super fascinating. One of the things that I'm super excited about in our industry in total. >> All right, well, really good discussion here. Daniel, Dr. T, thank you so much for sharing everything from your keynote and been a pleasure watching. >> Thank you. >> All right back with lots more covered from SUSECON Digital 20 I'm Stuart Miniman and as always, thank you for watching theCUBE. (upbeat 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

okay we're back this is Dave Volante with Jeff Kelly we're with Ricky bond on organ this is the cubes silicon angles flagship product we go out to the events we extract the signal from the noise we bring you the tech athletes who are really changing the industry and we have one here today christiane sabo is the CEO the leader the spiritual leader of of this conference and of Tablo Kristin welcome to the cube thanks for having me yeah it's our pleasure great keynote the other day I just got back from Italy so I'm full of superlatives right it really was magnificent I was inspired I think the whole audience was inspired by your enthusiasm and what struck me is I'm a big fan of simon Sinek who says that people don't buy what you do they buy why you do it and your whole speech was about why you're here everybody can talk about their you know differentiators they can talk about what they sell you talked about why you're here was awesome so congratulations I appreciate that yeah so um so why did you start then you and your colleagues tableau well it's how below really started with a series of breakthrough research innovations that was this seed there are three co-founders of tableau myself dr. crystal T and professor Pat Hanrahan and those two are brilliant inventors and designers and researchers and the real hero of the tableau story and the company formed when they met on entrepreneur and a customer I had spent several years as a data analyst when I first came out of college and I understood the problems making sense of data and so when I encountered the research advancements they had made I saw a vision of the future a much better world that could bring the power of data to a vastly larger number of people yeah and it's really that simple isn't it and and so you gave some fantastic examples them in the way in which penicillin you know was discovered you know happenstance and many many others so those things inspire you to to create this innovation or was it the other way around you've created this innovation and said let's look around and see what others have done well I think the thing that we're really excited about is simply put as making databases and spreadsheets easy for people to use I can talk to someone who knows nothing about business intelligence technology or databases or anything but if I say hey do you have any spreadsheets or data files or databases you you just feel like it could it could get in there and answer some questions and put it all together and see the big picture and maybe find a thing or two everyone not everyone has been in that situation if nothing else with the spreadsheet full of stuff like your readership or the linkage the look the the traffic flow on on the cube website everyone can relate to that idea of geez why can't I just have a google for databases and that's what tableau is doing right right so you've kind of got this it's really not a war it's just two front two vectors you know sometimes I did I did tweet out they have a two-front war yeah what'd you call it the traditional BI business I love how you slow down your kids and you do that and then Excel but the point I made on Twitter in 140 characters was you it will be longer here I'm a little long-winded sometimes on the cube but you've got really entrenched you know bi usage and you've got Excel which is ubiquitous so it sounds easy to compete with those it's not it's really not you have to have a 10x plus value problem solutely talked about that a little bit well I think the most important thing we're doing is we're bringing the power of data and analytics to a much broader population of people so the reason the answer that way is that if you look at these traditional solutions that you described they have names like and these are the product brand names forget who owns them but the product brand names people are used to hearing when it comes to enterprise bi technology our names like Business Objects and Cognos and MicroStrategy and Oracle Oh bi and big heavy complicated develop intensive platforms and surprise surprise they're not in the hands of very many people they're just too complicated and development heavy to use so when we go into the worlds even the world's biggest companies this was a shocker for us even when we go into the world's most sophisticated fortune 500 companies and the most cutting-edge industries with the top-notch people most of the people in their organization aren't using those platforms because of theirs their complication and expense and development pull and so usually what we end up doing is just bringing the power of easy analytics and dashboards and visualization and easy QA with data to people who have nothing other than maybe a spreadsheet on their desk so in that sense it's actually a little easier than it sounds well you know I have to tell you I just have a cio consultancy and back in the day and we used to go in and do application portfolio analysis and we would look at the applications and we always advise the CIOs that the value of an application is a function of its use how much is being adopted and the impact of that use you know productivity of the users right and you'd always find that this is the dss system the decision support system like you said there were maybe 3 to 15 users yeah and an organization of tens of thousands of people yeah if they were very productive so imagine if you can you can permeate the other you know hundreds of thousands of users that are out there do you see that kind of impact that productivity impact as the potential for your marketplace absolutely I you know the person who I think said it best was the CEO of Cisco John Chambers and I'll paraphrase him here but he has this great thing he said which is he said you know if I can get each of the people on my team consulting data say oh I don't know twice per day before making a decision and they do the same thing with their people and their people and so you know that's a million decisions a month you did the math better made than my competition I don't want people waiting around for top top management to consult some data before making a decision I want all of our people all the time Consulting data before making a decision and that's the real the real spirit of this new age of BI for too long it's been in the hands of a high priesthood of people who know how to operate these complicated convoluted enterprise bi systems and the revolution is here people are fed up with it they're taking power into their hands and they're driving their organizations forward with the power of data thanks to the magic of an easy-to-use suite like tableau well it's a perfect storm right because everybody wants to be a data-driven organization absolutely data-driven if you don't have the tools to be able to visualize the data absolutely so Jeff if you want to jump in well Christian so in your keynote you talked for the majority of the keynote about human intuition and the human element talk a little bit about that because when we hear about in the press these days about big data it's oh well the the volume of data will tell you what the answer is you don't need much of the human element talk about why you think the human element is so important to data-driven decision-making and how you incorporate that into your design philosophy when you're building the product and you're you know adding new features how does the human element play in that scenario yeah I mean it's funny dated the data driven moniker is coming these days and we're tableaus a big big believer in the power of data we use our tools internally but of course no one really wants to be data driven if you drive your company completely based on data say hello to the cliff wall you will drive it off a cliff you really want people intelligent domain experts using a combination of act and intuition and instinct to make data informed decisions to make great decisions along the way so although pure mining has some role in the scheme of analytics frankly it's a minor role what we really need to do is make analytic software that as I said yesterday is like a bicycle for our minds this was the great Steve Jobs quote about computers that their best are like bicycles for our mind effortless machines that just make us go so much faster than any other species with no more effort expended right that's the spirit of computers when they're at our best Google Google is effortless to use and makes my brain a thousand times smarter than it is right unfortunately over an analytic software we've never seen software that does tap in business intelligence software there's so much development weight and complexity and expense and slow rollout schedules that were never able to get that augmentation of the brain that can help lead to better decisions so at tableau in terms of design we value our product requirements documents say things like intuition and feel and design and instinct and user experience they're focused on the journey of working with data not just some magic algorithm that's gonna spit out some answer that tells you what to do yeah I mean I've often wondered where that bi business would be that traditional decision support business if it weren't for sarbanes-oxley I mean it gave it a new life right because you had to have a single version of the truth that was mandated by by the government here we had Bruce Boston on yesterday who works over eight for a company that shall not be named but anyway he was talking about okay Bruce in case you're watching we're sticking to our promise but he was talking about intent desire and satisfaction things those are three things intent desire and satisfaction that machines can't do like the point being you just you know it was the old bromide you can't take the humans in the last mile yeah I guess yeah do you see that ever changing no I mean I think you know I I went to a friend a friend of mine I just haven't seen in a while a friend of mine once said he was an he was an artificial intelligence expert had Emilie's PhD in a professorship in AI and once I naively asked him I said so do we have artificial intelligence do we have it or not and we've been talking about for decades like is it here and he said you're asking the wrong question the question is how smart our computers right so I just think we're analytics is going is we want to make our computers smarter and smarter and smarter there'll be no one day we're sudden when we flip a switch over and the computer now makes the decision so in that sense the answer to your question is I keep I see things going is there is it going now but underneath the covers of human human based decision making it are going to be fantastic advancements and the technology to support good decision making to help people do things like feel and and and chase findings and shift perspectives on a problem and actually be creative using data I think there's I think it's gonna be a great decade ahead ahead of us so I think part of the challenge Christian in doing that and making that that that evolution is we've you know in the way I come the economy and and a lot of jobs work over the last century is you know you're you're a cog in a wheel your this is how you do your job you go you do it the same way every day and it's more of that kind of almost assembly line type of thinking and now we're you know we're shifting now we're really the to get ahead in your career you've got to be as good but at an artist you've got to create B you've got to make a difference is the challenge do you see a challenge there in terms of getting people to embrace this new kind of creativity and again how do you as a company and as a you know provider of data visualization technology help change some of those attitudes and make people kind of help people make that shift to more of less of a you know a cog in a larger organization to a creative force inside that organ well mostly I feel like we support what people natively want to do so there are there are some challenges but I mostly see opportunity there in category after category of human activity we're seeing people go from consumers to makers look at publishing from 20 years ago to now self-publishing come a few blogs and Twitter's Network exactly I mean we've gone from consumers to makers everyone's now a maker and we have an ecosystem of ideas that's so positive people naturally want to go that way I mean people's best days on the job are when they feel they're creating something and have that sense of achievement of having had an idea and seeing some progress their hands made on that idea so in a sense we're just fueling the natural human desire to have more participation with data to id8 with data to be more involved with data then they've been able to in the past and again like other industries what we're seeing in this category of technology which is the one I know we're going from this very waterfall cog in a wheel type process is something that's much more agile and collaborative and real-time and so it's hard to be creative and inspired when you're just a cog stuck in a long waterfall development process so it's mostly just opportunity and really we're just fueling the fire that I think is already there yeah you talked about that yesterday in your talk you gave a great FAA example the Mayan writing system example was fantastic so I just really loved that story you in your talk yesterday basically told the audience first of all you have very you know you have clarity of vision you seem to have certainty in your vision of passion for your vision but the same time you said you know sometimes data can be confusing and you're not really certain where it's going don't worry about that it's no it's okay you know I was like all will be answered eventually what but what about uncertainty you know in your minds as the you know chief executive of this organization as a leader in a new industry what things are uncertain to you what are the what are the potential blind spots for you that you worry about do you mean for tableau as a company for people working with data general resource for tableau as a company oh I see well I think there's always you know I got a trip through the spirit of the question but we're growing a company we're going a disruptive technology company and we want to embrace all the tall the technologies that exist around us right we want to help to foster day to day data-driven decision-making in all of its places in forms and it seems to me that virtually every breakthrough technology company has gone through one or two major Journal technology transformations or technology shocks to the industry that they never anticipated when they founded the company okay probably the most recent example is Facebook and mobile I mean even though even though mobile the mobile revolution was well in play when when Facebook was founded it really hadn't taken off and that was a blind Facebook was found in oh seven right and look what happened to them right after and here's that here's new was the company you can get it was founded in oh seven yeah right so most companies I mean look how many companies were sort of shocked by the internet or shocked by the iPod or shocked by the emergence of a tablet right or shocked by the social graph you know I think for us in tableaus journey if this was the spirit of the thought of the question we will have our own shocks happen the first was the tablet I mean when we founded tableau like the rest of the world we never would have anticipated that that a brilliant company would finally come along and crack the tablet opportunity wide open and before in a blink of an eye hundreds of millions of people are walking around with powerful multi-touch graphic devices in their I mean who would have guessed people wouldn't have guessed it no six let alone oh three know what and so luckily that's what that's I mean so this is the good kind of uncertainty we've been able to really rally around that there are our developers love to work on this area and today we have probably the most innovative mobile analytics offering on the market but it's one we never could have anticipated so I think the biggest things in terms of big categories of uncertainty that we'll see going forward are similar shocks like that and our success will be determined by how well we're able to adapt to those so why is it and how is it that you're able to respond so quickly as an organization to some of those tectonic shifts well I think the most important thing is having a really fleet-footed R&D team we have just an exceptional group of developers who we have largely not hired from business technology companies we have something very distributed going a tableau yeah one of the amazing things about R&D key our R&D team is when we decided to build just this amazing high-wattage cutting-edge R&D team and focus them on analytics and data we decided not to hire from other business intelligence companies because we didn't think those companies made great products so we've actually been hiring from places like Google and Facebook and Stanford and MIT and computer gaming companies if you look at the R&D engineers who work on gaming companies in terms of the graphic displays and the response times and the high dimensional data there are actually hundreds of times more sophisticated in their thinking and their engineering then some engineer who was working for an enterprise bi reporting company so this incredible horsepower this unique team of inspired zealots and high wattage engineers we have in our R&D team like Apple that's the key to being able to respond to these disruptive shocks every once in a while and rule and really sees them as an opportunity well they're fun to I mean think of something on the stage yesterday and yeah we're in fucky hats and very comfortable there's never been an R&D team like ours assembled in analytics it's been done in other industries right Google and Facebook famously but in analytics there's never been such an amazing team of engineers and Christian what struck me one of the things that struck me yesterday during your keynote or the second half of the keynote was bringing up the developers and talking about the specific features and functions you're gonna add to the product and hearing the crowd kind of erupt at different different announcements different features that you're adding and it's clear that you're very customer focused at this at tableau of you I mean you're responding to the the needs and the requests of your customers and I that's clearly evident again in the in the passion that these customers have for your for your product for your company how do you know first I'm happy how do you maintain that or how do you get get to that point in the first place where you're so customer focused and as you go forward being a public company now you're gonna get pressure from Wall Street and quarter results and all that that you know that comes with that kind of comes with the territory how do you remain that focused on the customer kind of as your you know you're going to be under a lot of pressure to grow and and you know drive revenue yeah I keep that focus well there's two things we do it's a it's always a challenge to stay really connected to your customers as you get big but it's what we pride ourselves on doing and there's two specific things we do to foster it the first is that we really try to focus the company and we try to make a positive aspect of the culture the idea of impact what is the impact of the work we're having and in fact a great example of how we foster that is we bring our entire support and R&D team to this conference no matter where it is we take we fly I mean in this case we literally flew the entire R&D team and product management team and whatnot across country and the time they get here face to face face to face with customers and hearing the customer stories and the victories and actually seeing the feedback you just described really inspires them it gives them specific ideas literally to go back and start working on but it also just gives them a sense of who comes first in a way that if you don't leave the office and you don't focus on that really doesn't materialize and the way you want it the second thing we do is we are we are big followers of I guess what's called the dog food philosophy of eat your own dog so drink your own champagne and so one of our core company values that tableau is we use our products facility a stated value of the company we use our products and into an every group at tableau in tests in bug regressions in development in sales and marketing and planning and finance and HR every sip marketing marketing is so much data these these every group uses tableau to run our own business and make decisions and what happens Matt what's really nice about a company because you know we're getting close to a thousand people now and so it's keeping the spirit you just described alive is really important it becomes quite challenging vectors leagues for it because when that's one of your values and that's the way the culture has been built every single person in the company is a customer everyone understands the customer's situation and the frustrations and the feature requests and knows how to support them when they meet them and can empathize with them when they're on the phone and is a tester automatically by virtue of using the product so we just try to focus on a few very authentic things to keep our connection with the customer as close as possible I'll say christen your company is a rising star we've been talking all this week of the similarities that we were talking off about the similarities with with ServiceNow just in terms of the passion within the customer base we're tracking companies like workday you know great companies that are that are that are being built new emerging disruptive companies we put you in that in that category and we're very excited for different reasons you know different different business altogether but but there are some similar dynamics that we're watching so as observers it's independent observers what kinds of things do you want us to be focused on watching you over the next 12 18 24 months what should we be paying attention to well I think the most important thing is tableau ultimately is a product company and we view ourselves very early in our product development lifecycle I think people who don't really understand tableau think it's a visualization company or a visualization tool I don't I don't really understand that when you talk about the vision a lot but okay sure we can visualization but there's just something much bigger I mean you asked about people watching the company I think what's important to watch is that as I spoke about makino yesterday tableau believes what is called the business intelligence industry what's called the business analytics technology stack needs to be completely rewritten from scratch that's what we believe to do over it's a do-over it's based on technology from a prior hair prior era of computing there's been very little innovation the R&D investment ratios which you can look up online of the companies in this space are pathetically low and have been for decades and this industry needs a Google it needs an apple it's a Facebook an RD machine that is passionate and driven and is leveraging the most recent advances in computing to deliver products that people actually love using so that people start to enjoy doing analytics and have fun with it and make data-driven driven decision in a very in a very in a way that's just woven into their into their into their enjoyment and work style every every single day so the big series of product releases you're going to see from us over the next five years that's the thing to watch and we unveiled a few of them yesterday but trust me there's a lot more that's you a lot of applause christina is awesome you can see you know the passion that you're putting forth your great vision so congratulations in the progress you've made I know I know you're not done we'll be watching it thanks very much for coming to me I'm really a pleasure thank you all right keep right there everybody we're going wall to wall we got a break coming up next and then we'll be back this afternoon and this is Dave Volante with Jeff Kelly this is the cube we'll be right back