from the cube studios in palo alto in boston connecting with thought leaders all around the world this is a cube conversation [Music] hello everyone this is dave vellante with the cube and welcome to this conversation with me is anil singal who is the ceo of netscout anil it's a pleasure to speak with you today thanks so much for coming on the program thank you so i want to talk a little bit about uh netscout we're kind of at the cube we're sort of enamored by founder-led companies i mean you started net scout right around the same time that i entered the tech business and you remember back then it was an industry dominated by ibm monolithic systems were then with a norm in the form of mainframes you had mini computers pcs and things like pc local area networks they were in their infancy in fact most of the pcs as you remember they didn't have hard disks in them so i want to start with what was it that you saw 35 years ago to let you let that led you to start net scout and at the time did you even imagine that you'd be creating a company with a billion dollars worth of revenue and a much larger market cap well certainly i'd not imagine where we'll be right now and uh we didn't need we didn't know that this will be the outcome where i mean we just happened to be at the right place at the right time but we did have a vision some of you had the feeling we are enamored by networking and we thought that network will be the business in fact our business card in 91 said network is the business and so somehow we got that right and and we said these things will be connected and overall we found then that with the ip convergence first in the enterprise in 90s and then internet and then carriers moving from analog to digital we call talk about digital transformation in last few years but this has been going on for the last 30 years and as we add what we were doing become relevant to more and more people over time for example right now even power companies use our product okay and we have iot devices coming in so so basically what we do is we we said we're going to provide visibility through looking at the traffic through the lens and the vantage point of the network a lot of people think we're just doing network monitoring or have been doing that but actually we use the network as the vantage point which is other people are not doing most of the people have accidental data from devices at the basis of visibility and that turned out to be a very successful and but at some point different points in our life we became responsible for the market not just for netscope and that changed the shape of the company and what we did and how we drove the innovation yeah now i want to get into some of that but i i i'm still really enamored of and and fascinated by by the beginnings i worked for a founder led a chairman a guy named pat mcgovern who built the media empire he had these 10 sort of core principles we he used to test us on him we'd carry him around a little little note card things that today still serve us you know stay close to the customer uh you know keep the corporate staff lean promote from within respect for individuals the things that are drilled into your head i wonder you know what are the principles that you know sometimes they come become dogma but they're good dogma i don't mean that as a pejorative what are the things that that you built your business on the principles that you're sort of most proud of well i think there is so there are five in fact we call um uh some of the standards so five tenants we have we call we call this high ambition leadership which is more than just about making money and as just like the us is the leader of the free world we have a responsibility beyond u.s same way netscout has a responsibility beyond our own company and and revenue and our stakeholders so with that in mind we have these five things which i think i wouldn't have been able to articulate that 20 years ago like this and but they were always there so first is this guardians of the connected world which you see it on our website guardians care about their asset it's not just about money we are going to solve problems in the connected world which nobody else is able to solve or have the passion or have the resources and willpower to do it so that's that's the overall theme of the company guardians of the connected world connected world is changing broad new problems are coming our goal is there are pros and cons of every new thing our goal is to remove all the cons so you can enjoy the pros so that's guardian of the connected world then our mission is accelerate digital transformation meaning remove the road blocks people are looking at enablers but there are barriers also how do you remove the barriers for our customers so they can improve the fruits of digital transformation for example going to the cloud allows you to outsource some of the stuff especially in this time of agility and and dependency you can cut your cost but that comes with the price that you lose control so our product big bring the control back so now you can enjoy the pros and the cons and i call it sometime how do you change the wheels of your car while driving well if you change the four wheels then carve is going to fall down but how do you put one wheel in the cloud well that's what the our vision is visibility without water we'll give you the same information which is the third part so we have this uh tagline and for the company and then we have the mission accelerating digital transformation our vision is visibility without border when you run your application no matter where you run we'll give you the same piece of information that allows the people to make this transparent transparent migra that's migration transparent from a monitoring and visibility point of view then the fourth area is about a technology we call it smart data technology the whole world is talking about artificial intelligence machine learning but who are you going to learn for is your ai really authentic or is it truly artificial and that comes from smart data data is the oil of the new industry that's the oil and and people are not focusing on that they're saying i have lots of data but you don't have the data which we have in the past we said we are not going to share the data with third parties so in recently we have changed that you say yeah we'll there is the price for that we'll do that so we are branding ourselves as a smart data company where the whole industry is talking about smart analytics and i said we make smart people smarter and lastly uh the the value system of netscout is called lean but not mean okay and uh anybody can get lean if you get fat you can get your operation but how do you do lean decision making so you never have to be in me like net score never had delay in the last 35 years we have ups and down our stock has gone to three dollars and has gone to forty dollars but company continued to invest and uh and that's why we have this reputation we have with this tom here or steve here the tenure at netscout is 10 15 years minimum even in sales and people don't realize the power of that because some of our customers tell us hey your sales people are around longer than our employees and that how it builds a franchise of loyalty in the customer base we underestimate that this continuity part so there are many aspects of not what is the definition of not being mean the lean and mean is is sort of people are very proud of that and i think you can be lean without being mean and how do you become lean is don't hire when in good times unless you need them the reason people are able to do it is because they think i can fire any time so let's build up the fact so there are a lot of decision making we do around this and that's what i talk about in the book it's not about technology and this is i would say it's just one of the five diamonds but it's probably one of the most important ones and is one of the biggest differentiator of netscope well it's obviously served you well i mean no layoffs in 35 years the the retention metric is is very impressive i mean again i go back to my experience i was at idg for 15 years my passion was always to start my own company but i didn't want to leave because it was such a great culture and it seems like you've created something similar you know i talk to cios and ctos a lot too about about you know it's always people process technology and of course we want to talk about tech because we love talking about tech but they always tell me look tech comes and goes it's the processes that you put in place the culture that you have in place we could deal with the tech and it and it sounds like you've created a similar dynamic and i think back again when you started there were proprietary networks it was ibm sna dec network every mini computer had its own network then you know tcpip came in the whole world it changed and exploded but yet you said guardians of the connected world and that's kind of been your your focus from really day one you know i i loved what you said about the business the the network is the business remember the network is the computer that scott mcneely popularized so really kind of a similar dynamic there so it seems anneal that that framework that you just laid out those core principles have actually allowed you to ebb to flow to deal with stock prices and still retain people for very long periods of time maybe one more thing to add there is that on the lean but not when you talk about generalities we don't look any different like everyone cares about happy customers they care about happy employees and they care about happy stakeholders shareholders everyone including us but what's the order what's uh what's where do you start so we start with employees we say if they're happy employees they create success happy customers and then because of that they drive they buy more stuff and we create happy shareholders whereas if you start with happy shareholders you may not get happy employees and so and so all i'm saying is that everyone probably believes in what what we are saying or what i'm saying but how they implement it and then like really walking the talk is the most important part well i think you're right i mean i think you know the financials is a byproduct of happy employees which drive happy customers if you take care of employees and customers then good good things will happen uh if you start with trying to micromanage the finances of course we all attempted to to do that um i i wonder if we could talk a little bit about so just to bring it forward a little bit we're talking about how netscout has essentially from a cultural standpoint been able to withstand the ups the downs i mean you've seen since since you know over 35 years a lot of the the the downturns and the the tech softness the tech bubbles the great you know recession obviously now we're in the middle of the pandemic um i and i wonder if you could talk to that specifically so the data that we have from our survey partner etr enterprise technology research shows that before the pandemic around 16 of employees worked from home we're talking about truly remote workers not you know a couple days a week and when we talked to cios today they tell us it's you know well over 70 percent now but they fully expect that when you know the world comes back to the new abnormal i call it that it's it's that number is going to that 16 is going to double to more than double the 34 so it's it puts stress on on the the network it changes the the direction of the traffic it changes the security uh emphasis maybe you could talk a little bit about that just in terms of how you you are helping your customers respond specifically so i always talk about like is this a new problem or is the bad problem getting worse and so i put it in that bad problem getting worse so if you make the bad to zero then you can't multiply it so i think it's highlighting some of the problems which are already there are being highlighted by a lot of people are telling are you seeing more attacks no we are becoming more conscious of the attacks we always had we have more time by the way hackers have more time too because they are also sitting at home doing things so what i'm saying what i feel is that two parts one is that i think people should not in the when the new normal comes or new abnormal then i think people should not make people work from her for the wrong reason certain people are saying oh i can save money that's the wrong reason but if it's efficient we should do this so we are doing some interesting things for home users to feel how they can feel that they're really working from the office and so yeah there are some new challenges on how we monitor because when a user complains now about a performance to it because they can't get their work they don't know whether it's our network or is the isp or is their wi-fi network so we try to provide the root cause analysis as quickly as possible which we call mean time to know and one of the things i didn't mention earlier about the what is the uniqueness of our technology when we use the network vantage point to drive visibility it's almost like the blood test when you have a problem if you tell the doctor i said hey what is my problem and they start looking at all kinds of things it's going to take forever but if i take the blood test i'll be able to do the i will know what the next thing to do so in a way we are doing the blood test of the user experience security problems and when we do that we can come up with some very unique things so in the we think that we'll be moving on into other areas so the visibility is the means to an end the end could be performance management could be visibility troubleshooting uh and could be security forensics like blood tests can be used for dna evidence also and so we have all the technology so we are moving on as we move to the home user we are applying that our techniques not just for service assurance or end user experience monitoring but also for security financing and one example i give you the i always talk about and you'll see that in my book being different before being be better first be different get the earplugs out of the audience before you tell the story and you don't do that even though we are very big we are very small compared to a lot of companies in the industry compared to big players like cisco ibm and all those so the new thing which we are looking at in security is the security industry is catching the act we are going to catch the actor if i can get into the what they were doing before the act before they did the ransomware what were they doing well that required continuous monitoring of the traffic and that's what we do so when we do catch the actor catching the thief not what they're stealing then you're preventing tomorrow's attack and that's basically the innovation part of netscout which we have been pushing for but we somehow decided not to apply that to security because we had enough problems to be sold as guardians of the connected world from a monitoring point of view and so those are those are some of the things we'll be applying as as we move forward and i feel that those are equally applicable before the pandemic and after the pandemic and it's just polarized more because more people are working from home it's interesting what you're saying about the blood test uh that's a great analogy because it kind of eliminates the guesswork uh and and removes the opaqueness uh goes right to sort of the hard heart of the matter you call it mean time to know um and and it's interesting too to look at productivity i i mentioned some of the survey work when we talked to organizations they say to us that actually productivity has gone up since the the pandemic and my response to that is yeah no kidding because people are working 15-hour days you can't keep that up and and the silent killer of productivity is is the the not has having an elongated mean time to know um and having to to guess and so my premise is that this productivity gain if in fact it exists is not sustainable because we're doing it on the backs of our employees and it's going to it's going to burn them out i'm not sure whether it's real also see there are both sides it's not possible practical as you are saying because for example you're a sales person and you're working six seven hours and you're traveling six hours you can't be on the phone for 12 hours with the customer right now right how can they be productive is there both sides going some people are overworked and so definition of productivity itself is in question and how do you measure that and so that's what we'll have to look i think basically what i'm saying is we should do it whatever we do after the pandemic is over about how many people work from home should be based on your business model your expectation not just based on cost and a lot of people are looking at once again oh this is another cost saving exercise and that should not be the reason that's the wrong reason because then they're measuring the productivity in terms of reduced cost not everything else plus at least in net stock is a company which i mean every meeting i go to i use chalkboard and it's very very hard as a for our company like somebody like ibm where most of the people were there 50 offices they were remote is the easy transition it's not easy for netscout and so right now we focus on safety but we need to come up with a good hybrid model later on and different people will set up differently but what we do will be relevant in all cases yeah but i think you're making a good point that it's not some kind of mandate to drive your costs down or we saw last decade there were a couple of prominent companies that were mandating actually working in the office eliminating work from home so obviously the wrong side of history you know who they didn't know a pandemic was coming but so so how how will you make that decision uh will you is it really a discussion case by case with the employees or how what's the framework for you guys to decide that well i think so right now our focus is on safety so it's completely optional in fact we don't even allow more than 20 percent and that's only in the headquarters other places we have less than five percent people coming right and only essential workers manufacturing and all those so right now is completely optional but my personal preference when there is no risk these people should come to work like they were coming before we like to make it as close as possible to the old normal but that's not going to be the case for other companies because they're bigger in size they have other things at play but certainly we are not going to do it or because it's cheaper for net scores because we when people work from home and so we will see how it goes i think it will be a transition but i can see we going back to new normal in a year from now if the things start winding down in six months within a year or so we should be getting back to uh some normalcy and but that doesn't mean it's going to be true for our customers so from a product point of view we are doing several things so we can help the customer through this transition and by the way one other thing i wanted to mention earlier when we talk about the blood test how does it relate to guardians of the connective connected world if you believe in that what did the industry do they made sure needles were not painful that blood test was reliable you could there is no hygiene issues or no issues like that the cost has come down as a guardian of the connected world because we do that that's what we have been doing we are removing the banners to a great idea but lot of other companies gave up and then they have different strategy and some are successful some are not so as a guardian of the connected wall our goal is to continue to make this practical use imagine if blood test industry has not done that where we'll be right now and that's what what i meant by guardian of the connected world this is not easy to do and sustain that in for a period of 20 30 years but we have been able to do that and we get a lot of challenges from naysayers or this will not work at high speed when i started mad scout it was 10 megabit ethernet now we have 100 gigs 100 gig ethernet and we are still able to handle it and nobody thought in those days that you can even get 200 likes people were questioning us but what happens is other things keep working in the market intel is making improvements a lot of people are doing work to solve the problem and we leverage that and and that's how we are able to uh sort of sustain this guardian of the connected world team yeah you know the other key aspect of the guardian of the connected world again not to overdo the blood test analogy but the time to results is very important if you if you have an issue and you have to wait wait weeks for the results and your doctor you can't get a hold of her and so you're you're successfully dealing with that in real time or near real time and that that to me is is critical a very important point thanks for reminding me because i forgot today that's one of the things i say all the time hey this one of the big things we have done if blood test industry has done it how long take to get results nowadays you can get results done in in like two hours and doctors can get a report in couple of hours that's what we have done that's like mean time to know which we talked about with our technology i think we're basically the all the issues that you can't even breathe without doing something on the network so if you're listening to the traffic or hearing that uh what the conversation you can form an independent view of what is happening and that could be the that's the smart data which then becomes the basis of analytics whether analytics in the security space or not and so that's uh and that one thing we have not changed this technique now the outcomes are different what are we doing with the visibility is different is keep changing the number of customers and the type of customers are different but ultimately that part has interestingly has not changed i wonder if i could ask you i'd like to ask ceos especially those that are technologists and business leaders you know their thoughts on on the cloud i mean our data shows that the public cloud is growing in the 30 plus range annually the big three cloud public cloud players now account this year probably for close to 75 billion dollars in revenue maybe even a little bit more you know what what do you see driving this growth what does it mean for your customers well i think so forth we have a big announcement coming out called smart cloud monitoring to address this but what's the meaning of that i think what our customers are looking for is that it's it's not all or nothing it's not that everything is in the cloud or everything is in the program it could be private cloud public cloud colos the way vpns are laid out so they want to make sure that they can use our technology to do this react and analytics regardless of what decision they make and even five years from now there'll be enough non-cloud stuff okay so that's what we are trying to do we want to that's what is visibility without water and when they do that they say that helps them decide what's the best mode of operation for them for what application moving blindly to the cloud is a problem not going into that area is is also a problem but i think this the two new things have happened recently i would say one is sort of because of this crisis people don't want to own uh like hospitality industry okay this would i mean they're obviously having a big big issues with them but if they want a lot of the infrastructure they could have turned off some of that and so that's driving more movement to the cloud but i think there is a lot of choices available about a year or two ago i think affordable pricing model multiple choices not just aws and technology maturing where you can you can really implement and have a good experience i think those have become big enablers and so i think now it is possible to get to massive movement to the cloud but then they want to make sure that i'm now i'm outsourcing my problems but i'm not also outsourcing my vision to the cloud vendors because previously the way in the iit industry a lot of problems were solved is it was called the war rule let's get everyone who reports to me and everyone who reported to you but now that everyone doesn't report to you so how do you maintain the control when i complain to my ci hey my webex is slow or office three seriously and how does it resolve that problem because they cannot tell me oh we outsource them so i can't tell you that well we should not have outsourced them to the cloud so how do you drive this collaboration between the providers and the consumers is going to be key to accelerating this transformation because otherwise the cost of capex cost of reduction of moving to the cloud will be offseted by the increase in operax and customer satisfaction for the customer and so if we can help deal with one of the parts industry is already doing the other big part of making cloud work i think then we'll have the best chance of success yeah and of course the security has implications on the security model you were talking earlier about that as an opportunity people sometimes think oh yeah i put put my data in the cloud i'm good on security but there's there's a shared responsibility uh again we talked about different traffic patterns uh you've got work from home going on uh so and it's interesting when you juxtapose a sort of industry narrative on security which is it's it gets harder and harder and harder and you hear some of the cloud players say hey the state of security is really good uh but when you talk to csos you know they'll talk about the lack of talent uh the challenges they have the tools tools creep the fact that they spend more but the adversaries just keep getting stronger and stronger and stronger it's a really serious problem i mean maybe we close there i mean kind of how do you see it from your your vantage point let's look at the blood test so i look at if you don't the technique which we are talking about at least in the dimension of security monitoring then you are going to a lot of little things because you are doing little things you are going to be do a tool creep and because of that you have a like a talent issue and i think if you can make the right stuff work then you will not have this this talent issue and i feel that we are always looking solving yesterday's problem okay because we are not watching what led to the attack we are just dealing with the attack as an incident a security issue so i think continuous monitoring of deviation traffic allows you look at the deviation of the north so signature based security is a big portion but how do you know the signature of tomorrow and well you know that because you know the normal but only way you know normal is if you have been monitoring what was going on not for a specific event but deviation from normal that's what our approach is going to be anomalous behavior detection through our smart data and then you apply machine learning and ai algorithms to that i think that could be nirvana and but we don't have all the smart people for analytics but we can feed our data to those smart people and that's something we are going to bring up and the reason i feel it will be successful because this idea has been widely successful for netscout in the non-security space yeah i think you're bringing up another point that i've talked about a lot which is we've the industry has gone from sort of an industry of products to platforms and now ecosystems is really driving a lot of the innovation it's exactly what you're talking about feeding data to other partners data partners and now you start thinking about iot and the edge and machines talking to machines i mean i put you know video cameras up in my house to to make my environment more secure but of course i'm scared to death that those things can get hacked um it's a very complicated situation and the the power of many is going to trump the the the resources of one and so i'm glad you you brought that out um maybe give us your final thoughts anil it really has been a pleasure talking to you well i think the vr one of the things people have asked me is uh is why did you start another company especially in silicon valley i said with this spot many companies but they all happened to be called netstar netscout 1.0 2.0 3.0 actually we we are into the 4.0 i sometimes say you know george foreman's four sons they're all called george foreman so it's like one and so every time we do something different and now we are in the process of launching netscore 5.0 it was partly because maybe accelerated because of what's what's going on with the pandemic because there are some new challenges which we then here for and we are entering the security space so i'm very excited about repeating what we did in the traditional monitoring space service assurance space both for enterprise and carriers to the security space and people will question us how come it took so long while we were solving other problems which were more interesting than this for netscout and now we're going to bring that technology and all the tenants guardian of the connected world smart data to the security space and also i mean people are around for a long time we are also building the next generation of leaders at netstar and and so we have our hands full over the next two three years in uh building the next generation of net scout solving some of the problems which industry is facing without abandoning our tenants and the culture and if we can do that i think uh there'll be uh we'll be going to uh to the next level in terms of netscore branding and leadership well given given the guiding principles that you shared with us earlier the the the fundamental technology that you have around visibility uh i think that's served you very well and i think there's no shortage of of opportunity uh for netscout so neil thanks so much for sharing your story and coming on thecube good thank you all right and thank you for watching everybody this is dave vellante for the cube we'll see you next time [Music] you

from the cube studios in Palo Alto in Boston connecting with thought leaders all around the world this is a cube conversation hi everybody this is Dave Volante and welcome to this special digital cube presentation sponsored by IBM we're going to focus in on data op data ops in action a lot of practitioners tell us that they really have challenges operationalizing in infusing AI into the data pipeline we're going to talk to some practitioners and really understand how they're solving this problem and really pleased to bring Victoria stayshia vich who's the Global Information Systems Manager for information management at harley-davidson Vik thanks for coming to the cube great to see you wish we were face to face but really appreciate your coming on in this manner that's okay that's why technology's great right so you you are steeped in a data role at harley-davidson can you describe a little bit about what you're doing and what that role is like definitely so obviously a manager of information management >> governance at harley-davidson and what my team is charged with is building out data governance at an enterprise level as well as supporting the AI and machine learning technologies within my function right so I have a portfolio that portfolio really includes DNA I and governance and also our master data and reference data and data quality function if you're familiar with the dama wheel of course what I can tell you is that my team did an excellent job within this last year in 2019 standing up the infrastructure so those technologies right specific to governance as well as their newer more modern warehouse on cloud technologies and cloud objects tour which also included Watson Studio and Watson Explorer so many of the IBM errs of the world might hear about obviously IBM ISEE or work on it directly we stood that up in the cloud as well as db2 warehouse and cloud like I said in cloud object store we spent about the first five months of last year standing that infrastructure up working on the workflow ensuring that access security management was all set up and can within the platform and what we did the last half of the year right was really start to collect that metadata as well as the data itself and bring the metadata into our metadata repository which is rx metadata base without a tie FCE and then also bring that into our db2 warehouse on cloud environment so we were able to start with what we would consider our dealer domain for harley-davidson and bring those dimensions within to db2 warehouse on cloud which was never done before a lot of the information that we were collecting and bringing together for the analytics team lived in disparate data sources throughout the enterprise so the goal right was to stop with redundant data across the enterprise eliminate some of those disparity to source data resources right and bring it into a centralized repository for reporting okay Wow we got a lot to unpack here Victoria so but let me start with sort of the macro picture I mean years ago you see the data was this thing that had to be managed and it still does but it was a cost was largely a liability you know governance was sort of front and center sometimes you know it was the tail that wagged the value dog and then the whole Big Data movement comes in and everybody wants to be data-driven and so you saw some pretty big changes in just the way in which people looked at data they wanted to you know mine that data and make it an asset versus just a straight liability so what what are the changes that you discerned in in data and in your organization over the last let's say half a decade we to tell you the truth we started looking at access management and the ability to allow some of our users to do some rapid prototyping that they could never do before so what more and more we're seeing as far as data citizens or data scientists right or even analysts throughout most enterprises is it well they want access to the information they want it now they want speed to insight at this moment using pretty much minimal Viable Product they may not need the entire data set and they don't want to have to go through leaps and bounds right to just get access to that information or to bring that information into necessarily a centralized location so while I talk about our db2 warehouse on cloud and that's an excellent example of one we actually need to model data we know that this is data that we trust right that's going to be called upon many many times from many many analysts right there's other information out there that people are collecting because there's so much big data right there's so many ways to enrich your data within your organization for your customer reporting the people are really trying to tap into those third-party datasets so what my team has done what we're seeing right change throughout the industry is that a lot of teams and a lot of enterprises are looking at s technologists how can we enable our scientists and our analysts right the ability to access data virtually so instead of repeating right recuperating redundant data sources we're actually ambling data virtualization at harley-davidson and we've been doing that first working with our db2 warehouse on cloud and connecting to some of our other trusted versions of data warehouses that we have throughout the enterprise that being our dealer warehouse as well to enable obviously analysts to do some quick reporting without having to bring all that data together that is a big change I see the fact that we were able to tackle that that's allowed technology to get back ahead because most backup Furnish say most organizations right have given IT the bad rap wrap up it takes too long to get what we need my technologists cannot give me my data at my fingertips in a timely manner to not allow for speed to insight and answers the business questions at point of time of delivery most and we've supplied data to our analysts right they're able to calculate aggregate brief the reporting metrics to get those answers back to the business but they're a week two weeks too late the information is no longer relevant so data virtualization through data Ops is one of the ways and we've been able to speed that up and act as a catalyst for data delivery but we've also done though and I see this quite a bit is well that's excellent we still need to start classifying our information and labeling that at the system level we've seen most most enterprises right I worked at Blue Cross as well with IBM tool had the same struggle they were trying to eliminate their technology debt reduce their spend reduce the time it takes for resources working on technologies to maintain technologies they want to reduce their their IT portfolio of assets and capabilities that they license today so what do they do to do that it's time to start taking a look at what systems should be classified as essential systems versus those systems that are disparate and could be eliminated and that starts with data governance right so okay so your your main focus is on governance and you talked about real people want answers now they don't want to have to wait they don't want to go big waterfall process so what was what would you say was sort of some of the top challenges in terms of just operationalizing your data pipelining getting to the point that you are today you know I have to be quite honest um standing up the governance framework the methodology behind it right to get it data owners data stewards at a catalog established that was not necessarily the heavy lifting the heavy lifting really came with I'm setting up a brand new infrastructure in the cloud for us to be quite honest um we with IBM partnered and said you know what we're going to the cloud and these tools had never been implemented in the cloud before we were kind of the first do it so some of the struggles that we aren't they or took on and we're actually um standing up the infrastructure security and access management network pipeline access right VPN issues things of that nature I would say is some of the initial roadblocks we went through but after we overcame those challenges with the help of IBM and the patience of both the Harley and IBM team it became quite easy to roll out these technologies to other users the nice thing is right we at harley-davidson have been taking the time to educate our users today up for example we had what we call the data bytes a Lunch and Learn and so in that Lunch and Learn what we did is we took our entire GIS team our global information services team which is all of IT through these new technologies it was a form of over 250 people with our CIO and CTO on and taking them through how do we use these tools what are the purpose of schools why do we need governance to maintain these pools why is metadata management important to the organization that piece of it seems to be much easier than just our initial scanning it up so it's good enough to start letting users in well sounds like you had real sponsorship from from leadership and input from leadership and they were kind of leaning into the whole process first of all is that true and how important is that for success oh it's essential we often said when we were first standing up the tools to be quite honest is our CIO really understand what it is that were for standing up as our CIO really understand governance because we didn't have the time to really get that face-to-face interaction with our leadership so I myself made it a mandate having done this previously at Blue Cross to get in front of my CIO and my CTO and educate them on what it is we are exactly standing up and once we did that it was very easy to get at an executive steering committee as well as an executive membership Council right I'm boarded with our governance council and now they're the champions of that it's never easy that was selling governance to leadership and the ROI is never easy because it's not something that you can easily calculate it's something that has to show its return on investment over time and that means that you're bringing dashboards you're educating your CIO and CTO and how you're bringing people together how groups are now talking about solutions and technologies in a domain like environment right where you have people from at an international level we have people from Asia from Europe from China that join calls every Thursday to talk about the data quality issue specific to dealer for example what systems were using what solutions on there are on the horizon to solve them so that now instead of having people from other countries that work for Harley as well as just even within the US right creating one-off solutions that are answering the same business questions using the same data but creating multiple solutions right to solve the same problem we're now bringing them together and we're solving together and we're prioritizing those as well so that return on investment necessarily down the line you can show that is you know what instead of this printing into five projects we've now turned this into one and instead of implementing four systems we've now implemented one and guess what we have the business rules and we have the classification I to this system so that you CIO or CTO right you now go in and reference this information a glossary a user interface something that a c-level can read interpret understand quickly write dissect the information for their own need without having to take the long lengthy time to talk to a technologist about what does this information mean and how do i how do I use it you know what's interesting is take away based on what you just said is you know harley-davidson is an iconic brand cool company with fuckin motorcycles right and but you came out of an insurance background which is a regulated industry where you know governance is sort of de rigueur right I mean it's it's a table steak so how are you able that arleigh to balance the sort of tension between governance and the sort of business flexibility so there's different there's different lovers I would call them right obviously within healthcare in insurance the importance becomes compliance and risk and regulatory right they're big pushes gosh I don't want to pay millions of dollars for fines start classifying this information enabling security reducing risk all that good stuff right for Harley Davidson it was much different it was more or less we have a mission right we want to invest in our technologies yet we want to save money how do we cut down the technologies that we have today reduce our technology spend yet and able our users have access to more information in a timely manner that's not an easy that's not an easy pass right um so what we did is I took that my married governance part-time model and our time model is specific worried they're gonna tolerate an application we're going to invest in an application we're gonna migrate an application or we're gonna eliminate that so I'm talking to my CIO said you know we can use governance the classifier system help act as a catalyst when we start to implement what it is we're doing with our technologies which technologies are we going to eliminate tomorrow we as IG cannot do that unless we discuss some sort of business impact unless you look at a system and say how many users are using us what reports are essential the business teams do they need this system is this something that's critical for users today to eat is this duplicate 'iv right we have many systems that are solving the same capability that is how I sold that off my CIO and it made it important to the rest of the organization they knew we had a mandate in front of us we had to reduce technology spend and that really for me made it quite easy and talking to other technologists as well as business users on why if governance is important why it's going to help harley-davidson and their mission to save money going forward I will tell you though that the businesses of biggest value right is the fact that they now owns the data they're more likely right to use your master data management systems like I said I'm the owner of our MDM services today as well as our customer knowledge center today they're more likely to access and reference those systems if they feel that they built the rule and they own the rules in those systems so that's another big value add to write as many business users will say ok you know you think I need access to this system I don't know I'm not sure I don't know what the data looks like within it is it easily accessible is it gonna give me the reporting metrics that I need that's where governance will help them for example like our state a scientist beam using a catalog right you can browse your metadata you can look at your server your database your tables your fields understand what those mean understand the classifications the formulas within them right they're all documented in a glossary versus having to go and ask for access to six different systems throughout the enterprise hoping right that's Sally next few that told you you needed access to these systems was right just to find out that you don't need the access and hence it took you three days to get the access anyway that's why a glossary is really a catalyst a lot of that well it's really interesting what you just said about you went through essentially an application rationalization exercise which which saved your organization money that's not always easy because you know businesses even though the you know IIT may be spending money on these systems businesses don't want to give them up but you were able to use it sounds like you're able to use data to actually inform which applications you should invest in versus you know sunset as well you'd sounds like you were giving the business a real incentive to go through this exercise because they ended up as you said owning the data well then what's great right who wants pepper what's using the old power and driving a new car if they can buy the I'm sorry bull owning the old car right driving the old park if they can truly own a new car for a cheaper price nobody wants to do that I've even looked at Tesla's right I can buy a Tesla for the same prices I can buy a minivan these days I think I might buy the Tesla but what I will say is that we also use that we built out a capabilities model with our enterprise architecture team and building that capabilities model we started to bucket our technologies within those capabilities models right like AI machine learning warehouse on cloud technologies are even warehousing technologies governance technologies you know those types of classifications today integrations technologies reporting technologies by kind of grouping all those into a capabilities matrix right and was Eve it was easy for us to then start identifying alright we're the system owners for these when it comes to technologies who are the business users for these based on that right let's go talk to this team the dealer management team about access to this new profiling capability with an IBM or this new catalog with an IBM right that they can use stay versus this sharepoint excel spreadsheets they were using for their metadata management right or the profiling tools that were old you know ten years old some of our sa peoples that they were using before right let's sell them on the noodles and start migrating them that becomes pretty easy because I mean unless you're buying some really old technology when you give people a purview into those new tools and those new capabilities especially with some of the IBM's new tools we have today there the buy-in is pretty quick it's pretty easy to sell somebody on something shiny and it's much easier to use than some of the older technologies let's talk about the business impact in my understanding is you were trying to increase the improve the effectiveness of the dealers not not just go out and brute force sign up more dealers were you able to achieve that outcome and what does it meant for your business yes actually we were so right now what we did is we slipped something called a CDR and that's our consumer dealer and development repository right that's where a lot of our dealer information resides today it's actually argue ler warehouse we had some other systems that we're collecting that information Kalinin like speed for example we were able to bring all that reporting man to one location sunset some of those other technologies but then also enable for that centralized reporting layer which we've also used data virtualization to start to marry submit information to db2 warehouse on cloud for users so we're allowing basically those that want to access CDR and our db2 warehouse and called dealer information to do that within one reporting layer um in doing so we were able to create something called a dealer harmonized ID really which is our version of we have so many dealers today right and some of those dealers actually sell bytes some of those dealers sell just apparel material some of those dealers just sell parts of those dealers right can we have certain you IDs kind of a golden record mastered information if you will right bought back in reporting so that we can accurately assess the dealer performance up to two years ago right it was really hard to do that we had information spread out all over it was really hard to get a good handle on what dealers were performing and what dealers weren't because was it was tough right for our analysts to wrangle that information and bring it together it took time many times we you would get multiple answers to one business question which is never good right one one question should have one answer if it's accurate um that is what we worked on within us last year and that's where really our CEO so the value at is now we can start to act on what dealers are performing at an optimal level versus what dealers are struggling and that's allowed even our account reps or field steel fields that right to go work with those struggling dealers and start to share with them the information of you know these are what some of our stronger dealer performing dealers are doing today that is making them more affecting it inside sorry effective is selling bikes you know these are some of the best practices you can implement that's where we make right our field staff smarter and our dealers smarter we're not looking to shut down dealers we just want to educate them on how to do better well and to your point about a single version of the truth if you will the the lines of business kind of owning their own data that's critical because you're not spending all your time you know pointing at fingers trying to understand the data if the if the users own it then they own it I and so how does self-service fit in were you able to achieve you know some level of self-service how far could you and you go there we were we did use some other tools I'll be quite honest aside from just the IBM tools today that's enabled some of that self-service analytics si PSAC was one of them Alteryx is another big one that we like to that our analyst team likes to use today to wrangle and bring that data together but that really allowed for our analysts spread in our reporting teams to start to build their own derivations their transformations for reporting themselves because they're more user interface space versus going in the backend systems and having to write straight pull right sequel queries things of that nature it usually takes time then requires a deeper level of knowledge then what we'd like to allow for our analysts right to have today I can say the same thing with the data scientist scheme you know they use a lot of the R and Python coding today what we've tried to do is make sure that the tools are available so that they can do everything they need to do without us really having to touch anything and I will be quite honest we have not had to touch much of anything we have a very skilled data scientist team so I will tell you that the tools that we put in place today Watson explore some of the other tools as well they haven't that has enabled the data scientists to really quickly move do what they need to do for reporting and even in cases where maybe Watson or Explorer may not be the optimal technology right for them to use we've also allowed for them to use some of our other resources are open source resources to build some of the models that they're that they were looking to build well I'm glad you brought that up Victoria because IBM makes a big deal out of you know being open and so you're kind of confirming that you can use third-party tools and and if you like you know tool vendor ABC you can use them as part of this framework yeah it's really about TCO right so take a look at what you have today if it's giving you at least 80% of what you need for the business or for your data scientists or reporting analysts right to do what they need to do it's to me it's good enough right it's giving you what you need it's pretty hard to find anything that's exactly 100 percent it's about being open though to when you're scientists or your analysts find another reporting tool right that requires minimal maintenance or let's just say did a scientist flow that requires minimal maintenance it's free right because it's open source IBM can integrate with that and we can enable that to be a quicker way for them to do what they need to do versus telling them no right you can't use the other technologies or the other open source information out there for you today you've got to use just these spools that's pretty tough to do and I think that would shut most IT shops down pretty quick within larger enterprises because it would really act as a roadblock to allow most of our teams right to do what they need to do reporting well last question so a big part of this the data ops you know borrowing from DevOps is this continuous integration continuous improvement you know kind of ongoing MOOC raising the bar if you will what do you see going from here oh I definitely see I see a world I see a world of where we're allowing for that rapid prototyping like I was talking about earlier I see a very big change in the data industry you said it yourself right we are in the brink of big data and it's only gonna get bigger there are organizations right right now that have literally understood how much of an asset their data really is today but they're starting to sell their data ah to other of their similar people are smaller industries right similar vendors within the industry similar spaces right so they can make money off of it because data truly is an asset now the key to it that was obviously making sure that it's curated that it's cleanse that it's rusted so that when you are selling that back you can't really make money off of it but we've seen though and what I really see on the horizon is the ability to vet that data right is in the past what have you been doing the past decade or just buying big data sets we're trusting that it's you know good information we're not doing a lot of profiling at most organizations arts you're gonna pay this big top dollar you're gonna receive this third-party data set and you're not gonna be able to use it the way you need to what I see on the horizon is us being able to do that you know we're building data Lake houses if you will right we're building um really those Hadoop link environments those data lakes right where we can land information we can quickly access it we can quickly profile it with tools that it would take hours for an ALICE write a bunch of queries do to understand what the profile of that data look like we did that recently at harley-davidson we bought and some third-party data evaluated it quickly through our agile scrum team right within a week we determined that the data was not as good as it as the vendor selling it right pretty much sold it to be and so we told the vendor we want our money back the data is not what we thought it would be please take the data sets back now that's just one use case right but to me that was golden it's a way to save money and start betting the data that we're buying otherwise what I would see in the past or what I've seen in the past is many organizations are just buying up big third-party data sets and just saying okay now it's good enough we think that you know just because it comes from the motorcycle and council right for motorcycles and operation Council then it's good enough it may not be it's up to us to start vetting that and that's where technology is going to change data is going to change analytics is going to change is a great example you're really in the cutting edge of this whole data op trend really appreciate you coming on the cube and sharing your insights and there's more in the crowd chatter crowd chatter off the Thank You Victoria for coming on the cube well thank you Dave nice to meet you it was a pleasure speaking with you yeah really a pleasure was all ours and thank you for watching everybody as I say crowd chatting at flash data op or more detail more Q&A this is Dave Volante for the cube keep it right there but right back right after this short break [Music]

>> Innovation Day, brought to you by Comcast. >> Hey, welcome back everybody, Jeff Rick, here with theCube. We're at the Comcast Silicon Valley Innovation Center here in Sunnyvale. It's a very cool space, I think it's grown up over a number of years as they've originated with some acquired companies, and now they got a huge setup here, and we had a big day today talking about customer experience, and really, if you look at the Comcast Voice Remote, and there's a lot of stuff going on that's maybe under the covers, you don't really give Comcast credit for, but they're actually doing a lot. And we're excited to, kind of dive into it a little bit deeper with our next guest, she's Annie Weskesser, she's a CMO of Uniphore. Annie, welcome. >> Yeah, thank you for having me here today. >> Absolutely. So what is Uniphore, for people that aren't familiar with the company. >> So Uniphore is a global leader in conversational service automation, and our vision is to bridge the gap between human and machine, through voice AI and automation. >> That's a mouth full. >> Yes. >> Conversational... >> Service. >> Service. >> Yes. >> So, people talk, and so you guys are heavily involved in voice. So what are the applications where people are using your voice? >> Yep, well primarily our focus is call centers. >> Okay. >> So large enterprises who have massive call centers, where we want to go in and help them with AI and automation, to help better listen to their customers, help better listen to the customers voice, and solve the problems in a faster manner. >> So I don't have to repeat my account number six different times to six different agents. >> Exactly, right. >> Or caught an in IVR cycle, or perhaps the chat that you were talking to doesn't-- The person on the phone, you have to repeat your story. This is something where the AI and automation will actually assist the agent to become a superhero. >> So, it's pretty interesting cause you know there's a lot of conversation about AI and ML, but really you know where it's going to have its impact is applied AI. >> Yes. And you said the company started out really more just on a pure voice, but now you're applying more and more kind of AI in the back end. So what kind of opportunities do you have now beyond just simply being able to do voice conversion?. >> To the first part of your question, the company started at IIT Madras back in 2008. And originally the focus of the company was really centered on voice, voice being the lowest common denominator and in Indie where the languages are 260 you know, potential languages to understand and maybe 25 at the top. We set out really to focus on voice and then realize that customer service was a large market and somewhere we can have a big impact. >> Right, right. So you reckon as you said a 100 different languages. >> A 100 different languages through our platform which is pretty incredible when you think about it. All of the different people calling in to customer service potentially or maybe through a chatbot or a voicebot to get their issues solved. >> And then you integrate in whatever the core system is that the customer services agent are using. >> Yes. >> So what are the types of tips and tricks that the call agent gets by using your guys service? >> So think about it as a platform where the customer can help they agents be more affective agents. So one of the things that call centers struggle with is something called after call work, where agents may spend two to three minutes after a call, summarizing the call. One of the things that our technology does and this is primarily for one of our customers who's a health care client. They said "Wouldn't it be great if we can automate that completely". So we've taken the after call work for one customer client, taken that two to three minutes down to 10 seconds, where that work that the agent would have done is completely summarized and the agent validates it, can correct it if needed and its completely done. So that not only saves the agent time to either pick up more calls and help other customers or it can get them of the phone in a quicker manner to save the call center more money. >> So that's doing more than just simply providing a transcript of the call which is something a different track than actually listening into to provide suggestions is actually taking it to the next level in terms of what categorizing, what type of call, the outcome etc. >> it's actually quite interesting because often times less than 1% of calls are listened to somewhere between 1 and 10% of calls are listened to in calls centers. So we can listen to a 100% of those calls in addition we offer something called that's more along the line of like a live agent coach to where the agent can concentrate on the conversation with the customer which is the primary thing listening to the customer. And our technology will serve you up coaching mechanism in terms of getting to faster resolution for the customer and getting them better insights to be almost a superhero of a agent. >> Right, and I would imagine the accuracy in terms of recording what happened in the call to go back and do the analytics and have a text base search you can do all types of analysis on those calls which was data that was probably just lost before right into (mumbles) >> You're exactly right. I think the accuracy is clearly a lot lower than if you were to have the AI and automation and Machine learning technology there. >> So the other conversation in the sit down that we had earlier today was really about driving a customer centric culture in your own company, not only just enabling it but really building it inside. I wonder if you could share some of the things that you guys have done to help make sure that everybody stays focused on the objective, which is the customer. >> Yip, I think it really starts at the top it starts with the leader of the organization. So we have a CEO whose extremely focused on customer centricity and in fact its our number one core value within the organization. So you see everyone from the CEO down to the rest of the organization completely focused on the customer and their needs. >> What about when the customer doesn't know what they need? What about you know, you bringing a new technology and your inviting a slightly different process or a slightly different change and your saying "Hey, this is actually a better way to keep text and transactions and we actually have a really coach that can help", you know, kind of guy to people. How do you help move customers to a place they don't necessarily know they want to go? >> Yeah, I mean you find that a lot, right. Its not necessarily the technology that we're providing for today but its having the innovation and having the foresight to create a platform that will be future proof. So that's critical, you know, I think that there are a lot of customers who might not know what they need today but that's our job to help them innovate and push the envelope on all things AI and automation. >> Right, I'm just curious to in terms of the impact of your technology on kind of the tracking software for those call center agents, right. So this is a group of people that have to process a lot of calls, you know everything is track to the minute and you know its funny I had a demo with Westworld and you know when Westworld's funny cause we started treating machines like machines and they wanted to be treated like people sometimes I wonder on some of these technologies You know is it enabling them to have more time to be more thoughtful, is it enabling them to have more time to get the better outcomes or is it sometimes perceived as 'oh my gosh you just trying to jam' you know, 'four more calls on in my hour by taking care of my two more minutes that I used to spend wrapping up the call". Do you think about those things and the end customer? >> The time is really the premium, right. So the number one focus is giving people time back and whether that's the customer who's calling in and you want to solve an issue and get them faster resolution or whether that's the agent that wants to free up more time in having the conversation with the customer, solving their problem and then getting of the phone I think that's the most effective way of doing it. >> Final question in terms of voice and the evolution of voice. `Cause I don't think people are really completely tuned in certainly not people old like we are. What are some of the conversations when people finally get, you know, kind of the enabler that voice communications opens up that's not necessarily available with texts or not necessarily available with other types of channels? >> Yeah, I mean I see it most easily in my children they expect everything to be voice enabled and so everything from the Comcast remote that they pick up in our living room everywhere they go when they see a remote they expect everything to be voice enabled. So that's really the future and I think a lot of customer service will be listening to your customers voice however, they want to communicate with you, whatever channel they want to communicate on. >> Great, really cool story Annie and thanks for taking the few minutes and sharing it with us. >> Yeah, thanks for inviting me. >> All right, she's Annie, I'm Jeff your watching theCube with the Comcast CX Experience Innovation day here at the Sillicon Valley Innovation Center. Thanks for watching see you next time.

(upbeat instrumental music) >> Welcome to the special CUBE Conversation here, in Palo Alto, I'm John Furrier, host of theCUBE. I'm here with David Richards the CEO of WANdisco, CUBE alumni, been on many times. WANdisco continues to make the right bets. The bet they recently made has been on cloud many years. We've covered it certainly on theCUBE. But live data is the new hot thing. Multiple clouds is turning out to be the trend. That's your friend. David, good to see you. >> Great to be back. >> Thanks for coming on. So we talk all the time about how you guys have always evolved the business and continued to stay out front in all the major waves. Now again, another good call. You've certainly bet on Cloud. We've talked about that, Open Source, Big Data, Cloud, you saw that coming, positioned for that. But now you got some great momentum and resonance with customers around live data, which is not a stretch, given what you guys have done with replication, things in the past, the core intellectual property. Give us the update. You guys have been in the news lately. >> So, thanks and I think you enumerated the past history over the past two or three years, which we like to say that we're living in dog years. Everything's happening seven times faster than it would do normally. So of course, we started out life by making a prediction that storage arrays would change. People are beginning to store, companies beginning to store structured and unstructured data, mammoth sizes that we've never seen previously. We're going to have to resort to Open Source software, running a commoditized hardware that we'd already seen the social media companies move to. Then we've seen, we began to see a problem emerge, even in that marketplace, where spike computes all the applications which were going to be heavily compute, would need to run in Cloud and Cloud environments where you have complete elastic compute at remarkably low cost. And that leads to a problem. So this iceberg kind of that we like to talk about underneath the oceans, so moving data for static archival data really simple problem. And that's not live data, that's archival data. You just FTP it from point A to point B. But if we're talking about transactional systems where 10, 20, 30, 40, 50 percent of the data set changes all of the time, that creates a humongous problem in moving data from one premises to cloud, either for hybrid cloud or between clouds for multi-cloud. And that's the precise problem that WANdisco solves. And we've seen customer attraction, recently we've just announced the deal, jointly with Microsoft Azure. Where a big healthcare company, who 12 months ago were not talking about cloud suddenly they got over that hump where security keys could be managed by themselves within the cloud, were able to move petabytes-scale data from their on-premise systems into the cloud, without any interruption to service, without any blocking. That's a trend that we're seeing our pipelines now full of companies, all trying to do that. >> It's like you hit the oil gusher with data, because the data tsunami has been there, and we've documented certainly on theCUBE, and our Research team at Wikibon, have been talking about it for years, and now you're starting to see it, and you guys are getting the benefits of it, is that people figured out that it's moving data around is expensive. And it's hard to do so you push compute to the edge, but you still got to move the data around because the key part of the latency piece of the cloud. So how do you do that at scale? So this is the thing that you guys have, and I want you to explain what it is. You guys have live data from multi-cloud. What does that mean? What is all the hubbub about? What's the buzz? Why is this such a hot topic, live data from multi-cloud. >> Okay so let's just take a step back and talk about what multi-cloud actually is in today's definition, which is the vendor's definition, which is very convenient. So what they mean is, moving, putting applications into a container, Kubernetes or whatever, picking it up and shifting it somewhere else. And hey presto, I've got applications running, the same applications running in two different clouds. That is not multi-cloud because you're forgetting about the data, and the iceberg underneath the ocean of this colossal amount of data. If I've got petabyte-scale, multi-terabyte-scale data sets, and I need to run the same applications, or different applications but against the same data set, I need guaranteed consistent data, and that is, by definition, a data consistency problem. It is not a data replication problem. So all of the stuff that we used to use in the past for gigabyte-scale data, for traditional, relational database problems, none of that stuff works in a live data world. And by live data, we're talking about multi-terabyte, petabyte-scale data. Data sets that are so large that we've never seen them before running in end cloud locations. It's different or same applications, but guaranteed consistent data in every location. >> So you guys have had this core composite around integrity around the data, whether it's in replication. Sounds like the same thing's true around moving data. >> Yep. >> You guys are managing the life cycle of end-to-end of data movement. >> Yep. >> Point A to point B. >> Yep. >> The other approach is to move compute to the data. >> Yep. >> We're just seeing Amazon do a deal with VMware on-premise. So there's two schools of thought. When should customers think about each approach? Can you just kind of debunk or just clarify those two positions? >> So it's not really a chicken and egg because we know which comes first. It's definitely the chicken. It's definitely the data. So if I'm going to rebuild my application infrastructure, in the cloud, I'm going to do it piece-by-piece. I can't do lift-and-shift for a thousand applications that are running against this data set and just hope that the data that block for six months because I've got petabyte-scale data, and wait for it to all arrive in the cloud, or put it to the back of you know, use a snowmobile or some physical device to move the data. I need to do this, I need to kind of build the aircraft while it's taking off and flying and that's probably a good analogy. So what we see, is companies the first step is to get consistent data on-premise to cloud, or between different clouds. Then what that enables me to do of course, is to piece-by-piece then rebuild my application infrastructure at the pace that I want to. I mean there's a great add that I keep on seeing on t.v. Where it's migration day. As though I can press a button and then suddenly you know, in this Alice in Wonderland magical world, everything just appears. Realistically, and I saw the CEO of VMware a couple of years ago talk about being in a hybrid cloud scenario for 20 years. I think that's probably accurate. We've got billions of applications. A mix of homegrown stuff, a mix of, you know, actuarial applications in the insurance industry that are impossible to build overnight. This is going to take an elongated period of time. >> I was talking on Twitter with a bunch of thought leaders. We were talking about hybrid cloud and multi-cloud, and the kindergarten class is hybrid, right? >> Yeah. >> So you got some public cloud, then you got some on-premise data center. So getting that operational thing nailed down is great. But as you get old, you know, you progress in the grades, and get smarter, as you increase your I.T. I.Q., you're dealing with multiple, potentially multiple data centers or bigger on site, or an IOT edge, and multiple clouds. >> Yep. >> So that sounds easy on paper, but when you have to move data around the different work loads, that's the core problem that people are talking about today. How do you guys address this problem? Because I buy multi-cloud, I can see that certain tools and certain clouds the right work load and the right cloud, I get that. >> Yeah. It makes a lot of sense to me. The data is the problem. >> Yep. >> So how do you guys address that? This is the number one concern. >> So the closest, people ask me all the time about competition. The closest is Google. Google have got a product called Google Spanner. And Google Spanner is a time-sensitive, active-active WAN-scope data replication solution. That looks on paper very close to what WANdisco does. It enables them to keep active data in all of their different geolocations that they've built for their add services years and years and years ago. The trouble with that is, it only works on their own proprietary network, against their own proprietary applications because they launched a satellite and stuck it in the sky, they put dark fiber under the ocean, and they put GPS atomic clocks on every single one of their servers because it uses time and time accuracy in order to synchronize all of their data. We can do all of that over the public internet. So we're not a hardware solution. This is a pure software solution that can work over the public internet. So we can do that for any cloud vendor, and any provider of applications. And that's what we do. We're licensing our I.P. all over the place at the moment. >> So which clouds are, I imagine there's a great uptake for the clouds. Which one are you working with now? Can you talk about the deals you've done? >> We're very close. We announced the Azure partnership with Microsoft, and their Azure product, and we've been very impressed with the traction that we're seeing with them, particularly an enterprise cloud. I mean the early stage of cloud obviously was dominated by Amazon, Amazon Web Services. And they did a fantastic job of really bringing cloud to the market by accident kind of inventing cloud and then bringing it to market very very quickly. The fastest ever company to, if it's and independent company to 15 billion dollars, but most of those applications and projects and companies were born in the cloud. I mean a lot of the modern companies today were actually of course, you have Airbnb et cetera, were born in the cloud. So that, the second inning of cloud is certainly enterprise. We've also been impressed with the traction that we've seen from Google GCP as being extremely impressive. And of course Amazon continued to thrive. In cloud we also have an OEM deal with Ali, with Alibaba with their cloud as well. So they're really the only full. >> If Google has Spanner, how do you differentiate between Google Spanner? >> So Google Spanner only works on their proprietary network. Which is great for Google and between their data centers, but what about 99.9 percent of the rest of the problem, which is the rest of us right, who operate on the public internet. So we can do what Google Spanner does active-active, geo, one scope replication of data but over the public internet. >> So you guys have been talking active-active for many times. We've had many conversations here on theCUBE. So I get that. How has your business changed with cloud? You had mentioned prior to coming on camera. You made a bet on cloud. It's paying off obviously. People who have made the right bets on cloud at the right time, it's certainly paying off. You're one of them. How does the live data in the multi-cloud change your business? Does it increase your trajectory? Is there a pivot? I mean what does it mean for WANdisco? >> So the very, so my thesis or the company's thesis, I won't take the credit for it, but the company's thesis was really simplistic, which is our bet was in the small data world of gigabyte-scale data, in order to do data replication, small data equals small outage. When you get data sets that are growing exponentially, and you get, you know, data sets through a thousand or a million times greater than what we've seen previously, what was a small outage or small blocking of client applications will become an elongated blocking of client applications that we're talking about, you know, six months to move 20 petabytes of data. You can't block applications, business critical applications for six months. That was the bet that we made. We expected initially to see that happen on-premise in the data like world, in the Hadoop world if you will. That didn't quite happen, or has not happen to date. We don't think that's probably going to happen. We're certainly seeing a huge desire of companies moving those data lakes into cloud, and we've actually innovated, we've got some new inventions coming out that enable you to move in a single pass, massive quantity of data that will be exponentially faster than anything else, and just doing a unidirectional data move into clouds. That was our bet that we said "Okay, companies in order to achieve the kind of scale "that they need to achieve, "they're going to have to do this in cloud." "In order to get to cloud, "they're going to have to move that data there, "and they're not going to be able to block even for a day "in order to move that data to cloud." And that was the bet we made, and it was the right bet. >> Talk about where you guys go from here. Give a company update. What's the status of the company? Get some new personnel? Any changes, notable updates? >> So we, really interestingly, my Co-Founder and Chief Scientist is a genius, Dr. Yeturu Aahlad, Ph.D. from UT, and undergrad from IIT, a new VP of Engineering Sakthi, IIT, Ph.D. at U.T. under Draxler. This fantastic Ph.D. program they did there. My new Head of Research came from, was Chairman of Computer Science at the University of Denver. He's was an IIT undergrad, Ph.D with Aahlad at UT. And I said jokingly to Aahlad: "There must be a fourth guy "that we can bring on board here "that went through the same program." He said, "We can but we can't hire him, "because he's the CTO of Microsoft, so." That was, he was the forth guy. Joel, who I know, is going to be coming on theCUBE shortly. He also has joined us from IBM to run Marketing for us. So we've made some fantastic new hires. The company's doing really well. You know cloud certainly has played a big part in the second half of last year. I think it's going to play a big part. It's definitely going to play a big part in 2019. We've seen a pivot in pipeline, that's moved away from possibly even disaster recovery, data lake in the first half of last year. We pivoted to more of a reliable subscription revenue in the second half of the year. We announced some pretty big deals, big healthcare companies. We've got really good public reference with AMD. We announced a motor vehicle company one of the new used cases there is four petabytes of data per day they're generating. That all has to be moved from on-premise to cloud. So we've got some ginormous deals in pipeline. We'll see how they play out in the coming weeks and months. >> It's great to see the change, and certainly on theCUBE. We've been talking, I think we've known each other for almost, this is our tenth year. >> Yeah. Ever since we first met. It's fun to see how you guys entered the market at Hadoop, staying on the data wave and thinking enterprise, integrity of the data, active-active, the key I.P. And how cloud is just assumed data, and it's not just data, it's large scale. So if you look at the new people you hired, you've got jobs in large scale systems. >> Yep. >> We're talking about a large systems, now data is just given. So you're really nailing the large scale, moving from an enterprise nice feature, certainly table stakes for fault tolerance, and active-active. Just add recovery to mission critical >> Yep. >> Ingredient in large scale cloud. >> Well it's ironic isn't it because our value actually increases with the volume of data. So we're an unusual company in that context where the larger the data site, the greater the problem, and the greater the problem that we solve. See we made a pretty good bet, the active-active replication, that live data would be a critical component of both hybrid cloud and multi-cloud. And that's playing out I think really well for us. >> And certainly a lot more changes to come. Great to have you on. >> Yeah. >> Cloud and multi-cloud. Certainly cloud has proven the economics proven large scale value of moving at cloud speed but now you have multiple clouds. That's going to change the game on applications, work loads. It's not going to change the data equation. There's still more tsunami of data that's not stopping. >> Exactly. >> I think you've got a good wave you're riding. >> Yeah. >> Data cloud wave. David Richards, CEO of WANdisco here in CUBE Conversations here in Palo Alto. I'm John Furrier, thanks for watching. (upbeat instrumental music)