from the cube studios in palo alto in boston bringing you data driven insights from the cube and etr this is breaking analysis with dave vellante predictions are all the rage at this time of year now on december 29th 2020 in collaboration with eric porter bradley of enterprise technology research etr we put forth our predictions for 2021 and the focus of our prognostications included tech spending remote work productivity apps cyber security ipos specs m a data architecture cloud hybrid cloud multi-cloud ai containers automation and semiconductors we covered a lot of ground now over the past several weeks we've been inundated with literally thousands of inbound emails pitching us on various predictions and trends in these and other areas here's my predictions folder and this is only a portion of the documents that i've received by email obviously printed them out killed a few trees sorry hello and welcome to this week's wikibon cube insights powered by etr in this breaking analysis we're going to review briefly each of our predictions for this past year 2021 and suggest a grade as to how we did we're going to do this as a little warm up for our 2022 predictions which we'll be doing in the next over the next couple of weeks now before we dig in i want to make an observation many of the predictions that we received they were observations of trends and sometimes not really predictions or you know or not surprising we got a lot of self-serving marketing statements you know predictions in our view they should be measurable so you can look back and say okay did they get it right now granted there are gray areas so that's why we'll use a grading system today now there are also many really well done and thought-provoking predictions and there's an example of one that we received that is strong it's from equinix cio milan waglay who said within the decade data centers will be powered by a hundred percent renewable energy okay so you know that's clear and we can measure that but anyway thanks to all the pr folks who sent along like i said literally thousands of predictions we tried to read them all but the volume over the past week or so was just so overwhelming and we'll try to scan them before we do our 2022 predictions but today we want to do that warm up by evaluating how we did in 2021 so let's get started our first prediction was that tech spending would increase by four percent this year coming off of what we had thought was a contraction in 2020 and depending on which data you look at you know best case maybe was flat we definitely correctly called the continuation into 2022 of the remote work trend and the positive impact it would have on pcs and the like but we underestimated the shape of that rebound that that spend back curve idc has tech spending wrote this year at five and a half percent so we feel like while we called the bounce back it was more pronounced than we had thought in fact you know we think that idc number is probably going to go up even higher and we'll address that in our 2022 predictions so so we'll give ourselves a b minus here okay next prediction was remote worker trends become fossilized settling in at an average of 34 percent by year end 2021. so on average 34 of the workers would be remote by the end of this year now you know we made the call but we missed delta no we missed omacrom we said 34 remote which would be 2x the historical norms now the etr data suggests it was 52 in september and it's probably going to be somewhere in the 40 to 45 range by by the end of this month into december and the thing is 75 of the workforce is probably still working either fully remote or in a hybrid model and hybrid work is probably going to be the dominant trend and we're going to have to revisit that framework or how we think about this whole structure and we'll do that again in our 2022 predictions so we'll give ourselves a c on that one we'll take some credit for the permanence of the trend but the percentage was well off the mark you know thanks to the variance as well as some cultural shifts that whole hybrid notion okay so hey not really a great start for eric and me but we rebound with the next one the productivity increases we said seen in 2020 will lead organizations to double down on the successes and certain productivity apps will benefit so to measure this we said let's take a look at the most recent quarterly earnings and gauge the revenue growth year on year as an indicator docusign was up 42 smartsheet who we also called up was up 46 in revenue twilio up 65 zoom growth was 35 down from 325 confirming our layup call the zoom growth would moderate it had nowhere to go but down and microsoft teams has never been more ubiquitous has never seen greater adoption with hundreds of companies having a hundred thousand or more users and thousands of companies with ten thousand users or more so we really feel like we nailed this one so we're gonna give us give ourselves an a plus okay so now on to cyber it's an area that we've been making calls in for a couple of years now and we're really pleased looking back here we said permanent shifts in cso strategies are going to lead to share shifts in network security now we said to give you more detail maybe that sounds like an easy one but we said specifically identity cloud security and endpoint security would continue to benefit and we specifically named crowdstrike octa zscaler and a few others that are targeting their growth rates now gartner has the security market growing at 11 percent octa and zscaler revenues last quarter grew at 62 percent year over year crowdstrike 63 illumia we also called out they raised 225 million dollars on a 2.75 billion valuation on the strength of its growth that was in september now akamai acquired guardiocor for 600 million dollars another company we called out that they would do it they did that as a ransomware protection play and they paid a huge revenue multiple for the company and it seems the guys listed on the last line are all talking about subscriptions sas arr remaining performance obligations or rpo so we feel very good about this look back we'll take an a on this one no it's not an a plus because we're too conservative on the growth of octa crowdstrike and zscaler topping at 50 they they blew that away by another 10 points or so 10 to 15. but look pretty good call nonetheless okay again the next one you might feel like is a layup but not really so we said the increased tech spend would drive even more ipos spax and m a according to spac analytics ipos were up 109 this year the spac attack continued up 109 percent in 2021 on top of a record 2020 and according to kpmg m a dollar volume was up 19 okay you might say uh that was easy call but there was much more underneath this prediction we called out uipass ipo which was a lock but also said automation anywhere would go public uipath did aa didn't we did correctly call the hashicorp ipo we said they'd either get go ipo or get acquired and cloud flare grew revenue 219 percent last quarter but akamai was not acquired so the degree of difficulty on the overall prediction wasn't high but the automation anywhere in akamai events we made those calls that didn't happen and those were you know obviously tougher calls so we think this still deserves a b grade all right as you know data is one of our favorite subjects and we've reported extensively in the successes and failures of so-called big data we said next in the next prediction that in the 2020s 75 percent of large organizations will re-architect their big data platforms and we said this would occur you know in earnest over the next four to five years now again you may say duh dave but you have to evaluate the prediction based on the underlying comments here the jury is still out on things like snowflakes data cloud but we absolutely believe that it's the right direction but then you have then you have data bricks coming in taking a different approach they're coming at the problem from a data science angle trying to take on traditional bi and then you get snowflake coming from the analytics space and moving into ai and data science and you know we asked at aws aws re invent we asked benoit dejaville on the cube if there needs to be a semantic layer to bring these two worlds together and he said yes and that's what he claims snowflake is building meanwhile you got the big whales like oracle they continue to invest in their capabilities to try to eliminate data movement and then there's aws taking a totally different approach to data where it gives customers maximum optionality of offerings and database and other services and you can't forget microsoft and google so many customers might not take the steps that we predicted because they're comfortable where they are specifically we're talking about here a shift toward domain ownership and data product thinking and the reorganization of hyper-specialized technical teams many of the principles put forth by data mesh and we've said this change is going to take a number of years to play out four to five years so we start noticing in 2021 that that's clearly been the case as we reported on parts of jpmorgan chase uh rethinking its data architecture hellofresh and many others so this is still an incomplete the professor we'll give ourselves an incomplete on this one but we think it's trending in the right direction okay the next one is always fun discussion that's the battle to define hybrid and multi-cloud we said that's going to escalate in 2021 and we'll create bifurcated cio strategies now here we go aws sees the world as bringing its apis and primitives and model to the edge and the data center to aws is just another edge node and the company says that in still believes in the fullness of time that all data will be in the cloud however that's defined and aws awareness would say all this talk about hybrid of connecting on-prem to a cloud they would flat out say adam silipsky told us this that's not cloud is what he said then on the other side of the table you have the likes of cisco dell hpe etc saying hold on cloud is an operating model it's not a place and aws might say yeah and aws along with its customers is defining that operating model and these other guys would say no actually you're not we are with our customers and this battle 100 percent escalated in 2021 with the launch of apex by dell hp e double down on green lake cisco's as the service models and then of course oracle which actually announced a true same same public to on-prem hybrid capability two years before aws announced outpost and of course oracle's executing on that strategy in earnest in 2021 and the other nuance here is a concept that we introduced called super cloud which refers to the notion that look something like for example multi-cloud is not about running within a respective cloud it's not about cloud compatibility rather it's about abstracting the complexity of the underlying cloud primitives and building value on top of those cloud services on top of the investments in capex that the hyperscalers have made now some people didn't like the term super cloud maybe uber cloud would be a better term we're going to continue to use it to describe this capability we think it has meaning and we're seeing new examples like goldman sachs's financial cloud running on top of aws so a super cloud is not as an application or a suite of applications running on a single cloud now if those applications span multiple clouds like like snowflake is trying to do okay that's a service that could span multiple clouds or in the case of goldman sachs it's a portfolio of data tools and software that's made accessible as a service that floats on top of a single or even multiple clouds regardless we feel that this was a correct call given the evidence and we'll give ourselves an a minus taking points off for the somewhat anecdotal and observational measurement system that we apply to look back at this prediction okay the next prediction was we made was cloud containers ai and ml automation uh are gonna power that those big four are gonna power 2021 spending here's a graphic we use to predict that it plots survey data for the various technologies within the etr taxonomy net score or spending momentum on the vertical axis and market share or presence in the data set it's a pervasive measurement on the horizontal axis the one that matters here is the vertical that dotted line of 40 percent anything above that is considered highly elevated and these four areas have held served this year based on recent etr survey data that we're not showing here we'll we'll bring that into our 2022 prediction so this prediction came in correctly for the most recent survey data and that's our measurement system on this one so we're going to take an a for this one too now on the penelope ultimate prediction here we came back to automation saying that the automation mandate accelerates in 2021 uipath and automation anywhere we said would go public but microsoft remains a threat to these pure play rpa vendors well we gave ourselves a b on this one doubling down on automation anywhere going public you know that was wrong but we definitely saw this year companies leaning hard into automation and microsoft despite the fact that it doesn't have as feature rich a product and offering as uipath and automation anywhere microsoft remains a very large presence you know we spoke to a lot of customers at the uipath forward four event in october in las vegas physical event and they confirmed you know this is true but at the same time so they're using power automate from microsoft but also using in this case uipath so they've kind of confirmed that yeah it's not the same we use that for some of our productivity we're an azure customer it's easy for us but they're still leaning heavily and investing heavily into uipath and i think the same can be said for automation anywhere but autom but power automate shows up as a big time leader in the magic gartner magic quadrant so it can't be ignored but clearly the two leaders in rpa have a sizable product advantage relative to the legacy software players now if you look at the comment on pega systems they cooled off a bit as measured by their stock price their revenue grew 13 percent last quarter on a year-on-year basis but perhaps we overestimated the tailwind effect and the company's momentum so we'll take a b on this prediction correct call on the automation trend and the big software vendors piling in ibm et cetera but the chance we took on automation anywhere again was a miss so we'll dig ourselves on that and our last prediction for 2021 was 5g rollouts push new edge iot workloads and necessitate new system architectures now much of this prediction you can see in the underlying bullets here really related to the observation that arm was dominating at the edge it would find its way into the mainstream enterprise workloads and we've been asking a lot of the mainstream you know companies the oems you know what do you what do you see with with arm in the enterprise and they say yeah we don't see it yet but very clearly this came into focus in 2021 is aws announced graviton 3 now and new inference and new training silicon these are different types of workloads that are emerging in the enterprise these are all based on arm microsoft google alibaba oracle and others are now shipping or readying arm-based systems for the enterprise when you look at new storage network and security appliances and other systems they're very offering and often including arm-based processors to assist with the offloads and look intel is definitely under product under pressure as we've predicted many times not just in our predictions post even pat gelsinger has admitted this is a turnaround it's going to take at least five years that's kind of new and recent data that he's made public so we're going to take an a minus on this one we're going to take off some points for the fact that you know 5g rollouts in edge are evolving and this is a longer term trend but the underlying points that we made on this slide are still pretty solid now if we use the following scale where a plus is a hundred out of a hundred a minus is a 90 a b is an 85 a b minus is an 80 and a c is a 75 out of 100 and we exclude that incomplete prediction on data architectures we average out to an 87.8 so that's a solid b plus and so the professor in us said hey little yellow sticky good effort as most of the predictions could be quantified and or you know we tried to object objectively score them there were some layups in there so yeah maybe we'll try to take more risks uh you know or not you know we we we'll see we like winning and so you know you always have to couch some of these things with some obvious ones but but really try to give some detail underneath that's maybe non-obvious um and we'll try to keep it down in the legs we did this year to one or two multi-year predictions so what's next well eric bradley and i were working on our 2022 predictions we're going to release those in the next couple of weeks so stay tuned for that you know what do you think how did we do you know we're grading ourselves here love to know you know for we're off base on base we're too hard on ourselves too easy give us your feedback don't forget these episodes are all available as podcasts wherever you listen all you do is search breaking analysis podcast check out etr's website at etr dot plus remember we also publish a full report every week on wikibon.com and siliconangle.com you can always get in touch with email david.velante at siliconangle.com you can dm me at divalante or comment on our linkedin posts this is dave vellante for the cube insights powered by etr have a great week everybody stay safe be well we'll see you next time [Music] you

>>Welcome back to the cubes coverage of AWS public sector summit live in Washington D. C. A face to face event were on the ground here is to keep coverage. I'm john Kerry, your hosts got two great guests. Both cuba alumni Shannon Kellogg VP of public policy for the Americas and john would ceo tell us congratulations on some announcement on stage and congressional john being a public company. Last time I saw you in person, you are private. Now your I. P. O. Congratulations >>totally virtually didn't meet one investor, lawyer, accountant or banker in person. It's all done over zoom. What's amazing. >>We'll go back to that and a great great to see you had great props here earlier. You guys got some good stuff going on in the policy side, a core max on stage talking about this Virginia deal. Give us the update. >>Yeah. Hey thanks john, it's great to be back. I always like to be on the cube. Uh, so we made an announcement today regarding our economic impact study, uh, for the commonwealth of Virginia. And this is around the amazon web services business and our presence in Virginia or a WS as we all, uh, call, uh, amazon web services. And um, basically the data that we released today shows over the last decade the magnitude of investment that we're making and I think reflects just the overall investments that are going into Virginia in the data center industry of which john and I have been very involved with over the years. But the numbers are quite um, uh, >>just clever. This is not part of the whole H. 20. H. Q. Or whatever they call HQ >>To HQ two. It's so Virginia Amazon is investing uh in Virginia as part of our HQ two initiative. And so Arlington Virginia will be the second headquarters in the U. S. In addition to that, AWS has been in Virginia for now many years, investing in both data center infrastructure and also other corporate facilities where we house AWS employees uh in other parts of Virginia, particularly out in what's known as the dullest technology corridor. But our data centers are actually spread throughout three counties in Fairfax County, Loudoun County in Prince William County. >>So this is the maxim now. So it wasn't anything any kind of course this is Virginia impact. What was, what did he what did he announce? What did he say? >>Yeah. So there were a few things that we highlighted in this economic impact study. One is that over the last decade, if you can believe it, we've invested $35 billion 2020 alone. The AWS investment in construction and these data centers. uh it was actually $1.3 billion 2020. And this has created over 13,500 jobs in the Commonwealth of Virginia. So it's a really great story of investment and job creation and many people don't know John in this Sort of came through in your question too about HQ two, But aws itself has over 8000 employees in Virginia today. Uh, and so we've had this very significant presence for a number of years now in Virginia over the last, you know, 15 years has become really the cloud capital of the country, if not the world. Uh, and you see all this data center infrastructure that's going in there, >>John What's your take on this? You've been very active in the county there. Um, you've been a legend in the area and tech, you've seen this many years, you've been doing so I think the longest running company doing cyber my 31st year, 31st year. So you've been on the ground. What does this all mean to you? >>Well, you know, it goes way back to, it was roughly 2005 when I served on the Economic Development Commission, Loudon County as the chairman. And at the time we were the fastest-growing county in America in Loudon County. But our residential real property taxes were going up stratospherically because when you look at it, every dollar real property tax that came into residential, we lose $2 because we had to fund schools and police and fire departments and so forth. And we realized for every dollar of commercial real property tax that came in, We made $97 in profit, but only 13% of the money that was coming into the county was coming in commercially. So a small group got together from within the county to try and figure out what were the assets that we had to offer to companies like Amazon and we realized we had a lot of land, we had water and then we had, you know this enormous amount of dark fiber, unused fibre optic. And so basically the county made it appealing to companies like amazon to come out to Loudon County and other places in northern Virginia and the rest is history. If you look today, we're Loudon County is Loudon County generates a couple $100 million surplus every year. It's real property taxes have come down in in real dollars and the percentage of revenue that comes from commercials like 33 34%. That's really largely driven by the data center ecosystem that my friend over here Shannon was talking. So >>the formula basically is look at the assets resources available that may align with the kind of commercial entities that good. How's their domicile there >>that could benefit. >>So what about power? Because the data centers need power, fiber fiber is great. The main, the main >>power you can build power but the main point is is water for cooling. So I think I think we had an abundance of water which allowed us to build power sources and allowed companies like amazon to build their own power sources. So I think it was really a sort of a uh uh better what do they say? Better lucky than good. So we had a bunch of assets come together that helps. Made us, made us pretty lucky as a, as a region. >>Thanks area too. >>It is nice and >>john, it's really interesting because the vision that john Wood and several of his colleagues had on that economic development board has truly come through and it was reaffirmed in the numbers that we released this week. Um, aws paid $220 million 2020 alone for our data centers in those three counties, including loud >>so amazon's contribution to >>The county. $220 million 2020 alone. And that actually makes up 20% of overall property tax revenues in these counties in 2020. So, you know, the vision that they had 15 years ago, 15, 16 years ago has really come true today. And that's just reaffirmed in these numbers. >>I mean, he's for the amazon. So I'll ask you the question. I mean, there's a lot of like for misinformation going around around corporate reputation. This is clearly an example of the corporation contributing to the, to the society. >>No, no doubt. And you think >>About it like that's some good numbers, 20 million, 30 >>$5 million dollar capital investment. You know, 10, it's, what is it? 8000 9000 >>Jobs. jobs, a W. S. jobs in the Commonwealth alone. >>And then you look at the economic impact on each of those counties financially. It really benefits everybody at the end of the day. >>It's good infrastructure across the board. How do you replicate that? Not everyone's an amazon though. So how do you take the formula? What's your take on best practice? How does this rollout? And that's the amazon will continue to grow, but that, you know, this one company, is there a lesson here for the rest of us? >>I think I think all the data center companies in the cloud companies out there see value in this region. That's why so much of the internet traffic comes through northern Virginia. I mean it's I've heard 70%, I've heard much higher than that too. So I think everybody realizes this is a strategic asset at a national level. But I think the main point to bring out is that every state across America should be thinking about investments from companies like amazon. There are, there are really significant benefits that helps the entire community. So it helps build schools, police departments, fire departments, etcetera, >>jobs opportunities. What's the what's the vision though? Beyond data center gets solar sustainability. >>We do. We have actually a number of renewable energy projects, which I want to talk about. But just one other quick on the data center industry. So I also serve on the data center coalition which is a national organization of data center and cloud providers. And we look at uh states all over this country were very active in multiple states and we work with governors and state governments as they put together different frameworks and policies to incent investment in their states and Virginia is doing it right. Virginia has historically been very forward looking, very forward thinking and how they're trying to attract these data center investments. They have the right uh tax incentives in place. Um and then you know, back to your point about renewable energy over the last several years, Virginia is also really made some statutory changes and other policy changes to drive forward renewable energy in Virginia. Six years ago this week, john I was in a coma at county in Virginia, which is the eastern shore. It's a very rural area where we helped build our first solar farm amazon solar farm in Virginia in 2015 is when we made this announcement with the governor six years ago this week, it was 88 megawatts, which basically at the time quadruple the virginias solar output in one project. So since that first project we at Amazon have gone from building that one facility, quadrupling at the time, the solar output in Virginia to now we're by the end of 2023 going to be 1430 MW of solar power in Virginia with 15 projects which is the equivalent of enough power to actually Enough electricity to power 225,000 households, which is the equivalent of Prince William county Virginia. So just to give you the scale of what we're doing here in Virginia on renewable energy. >>So to me, I mean this comes down to not to put my opinion out there because I never hold back on the cube. It's a posture, we >>count on that. It's a >>posture issue of how people approach business. I mean it's the two schools of thought on the extreme true business. The government pays for everything or business friendly. So this is called, this is a modern story about friendly business kind of collaborative posture. >>Yeah, it's putting money to very specific use which has a very specific return in this case. It's for everybody that lives in the northern Virginia region benefits everybody. >>And these policies have not just attracted companies like amazon and data center building builders and renewable energy investments. These policies are also leading to rapid growth in the cybersecurity industry in Virginia as well. You know john founded his company decades ago and you have all of these cybersecurity companies now located in Virginia. Many of them are partners like >>that. I know john and I both have contributed heavily to a lot of the systems in place in America here. So congratulations on that. But I got to ask you guys, well I got you for the last minute or two cybersecurity has become the big issue. I mean there's a lot of these policies all over the place. But cyber is super critical right now. I mean, where's the red line Shannon? Where's you know, things are happening? You guys bring security to the table, businesses are out there fending for themselves. There's no militia. Where's the, where's the, where's the support for the commercial businesses. People are nervous >>so you want to try it? >>Well, I'm happy to take the first shot because this is and then we'll leave john with the last word because he is the true cyber expert. But I had the privilege of hosting a panel this morning with the director of the cybersecurity and Infrastructure Security agency at the department, Homeland Security, Jenness easterly and the agency is relatively new and she laid out a number of initiatives that the DHS organization that she runs is working on with industry and so they're leaning in their partnering with industry and a number of areas including, you know, making sure that we have the right information sharing framework and tools in place, so the government and, and we in industry can act on information that we get in real time, making sure that we're investing for the future and the workforce development and cyber skills, but also as we enter national cybersecurity month, making sure that we're all doing our part in cyber security awareness and training, for example, one of the things that are amazon ceo Andy Jassy recently announced as he was participating in a White house summit, the president biden hosted in late august was that we were going to at amazon make a tool that we've developed for information and security awareness for our employees free, available to the public. And in addition to that we announced that we were going to provide free uh strong authentication tokens for AWS customers as part of that announcement going into national cybersecurity months. So what I like about what this administration is doing is they're reaching out there looking for ways to work with industry bringing us together in these summits but also looking for actionable things that we can do together to make a difference. >>So my, my perspective echoing on some of Shannon's points are really the following. Uh the key in general is automation and there are three components to automation that are important in today's environment. One is cyber hygiene and education is a piece of that. The second is around mis attribution meaning if the bad guy can't see you, you can't be hacked. And the third one is really more or less around what's called attribution, meaning I can figure out actually who the bad guy is and then report that bad guys actions to the appropriate law enforcement and military types and then they take it from there >>unless he's not attributed either. So >>well over the basic point is we can't as industry hat back, it's illegal, but what we can do is provide the tools and methods necessary to our government counterparts at that point about information sharing, where they can take the actions necessary and try and find those bad guys. >>I just feel like we're not moving fast enough. Businesses should be able to hack back. In my opinion. I'm a hawk on this one item. So like I believe that because if people dropped on our shores with troops, the government will protect us. >>So your your point is directly taken when cyber command was formed uh before that as airlines seeing space physical domains, each of those physical domains have about 100 and $50 billion they spend per year when cyber command was formed, it was spending less than Jpmorgan chase to defend the nation. So, you know, we do have a ways to go. I do agree with you that there needs to be more uh flexibility given the industry to help help with the fight. You know, in this case. Andy Jassy has offered a couple of tools which are, I think really good strong tokens training those >>are all really good. >>We've been working with amazon for a long time, you know, ever since, uh, really, ever since the CIA embrace the cloud, which was sort of the shot heard around the world for cloud computing. We do the security compliance automation for that air gap region for amazon as well as other aspects >>were all needs more. Tell us faster, keep cranking up that software because tell you right now people are getting hit >>and people are getting scared. You know, the colonial pipeline hack that affected everybody started going wait a minute, I can't get gas. >>But again in this area of the line and jenny easterly said this this morning here at the summit is that this truly has to be about industry working with government, making sure that we're working together, you know, government has a role, but so does the private sector and I've been working cyber issues for a long time to and you know, kind of seeing where we are this year in this recent cyber summit that the president held, I really see just a tremendous commitment coming from the private sector to be an effective partner in securing the nation this >>full circle to our original conversation around the Virginia data that you guys are looking at the Loudon County amazon contribution. The success former is really commercial public sector. I mean, the government has to recognize that technology is now lingua franca for all things everything society >>well. And one quick thing here that segues into the fact that Virginia is the cloud center of the nation. Um uh the president issued a cybersecurity executive order earlier this year that really emphasizes the migration of federal systems into cloud in the modernization that jOHN has worked on, johN had a group called the Alliance for Digital Innovation and they're very active in the I. T. Modernization world and we remember as well. Um but you know, the federal government is really emphasizing this, this migration to cloud and that was reiterated in that cybersecurity executive order >>from the, well we'll definitely get you guys back on the show, we're gonna say something. >>Just all I'd say about about the executive order is that I think one of the main reasons why the president thought was important is that the legacy systems that are out there are mainly written on kobol. There aren't a lot of kids graduating with degrees in COBOL. So COBOL was designed in 1955. I think so I think it's very imperative that we move has made these workloads as we can, >>they teach it anymore. >>They don't. So from a security point of view, the amount of threats and vulnerabilities are through the >>roof awesome. Well john I want to get you on the show our next cyber security event. You have you come into a fireside chat and unpack all the awesome stuff that you're doing. But also the challenges. Yes. And there are many, you have to keep up the good work on the policy. I still say we got to remove that red line and identified new rules of engagement relative to what's on our sovereign virtual land. So a whole nother Ballgame, thanks so much for coming. I appreciate it. Thank you appreciate it. Okay, cute coverage here at eight of public sector seven Washington john ferrier. Thanks for watching. Mhm. Mhm.

from the cube studios in palo alto in boston bringing you data-driven insights from the cube and etr this is breaking analysis with dave vellante by our estimates aws will generate around nine billion dollars in storage revenue this year and is now the second largest supplier of enterprise storage behind dell we believe aws storage revenue will hit 11 billion in 2022 and continue to outpace on-prem storage growth by more than a thousand basis points for the next three to four years at its third annual storage day event aws signaled a continued drive to think differently about data storage and transform the way customers migrate manage and add value to their data over the next decade hello and welcome to this week's wikibon cube insights powered by etr in this breaking analysis we'll give you a brief overview of what we learned at aws's storage day share our assessment of the big announcement of the day a deal with netapp to run ontap natively in the cloud as a managed service and we'll share some new data on how we see the market evolving with aws executive perspectives on its strategy how it thinks about hybrid and where it fits into the emerging data mesh conversation let's start with a snapshot of the announcements made at storage day now as with most aws events this one had a number of announcements and introduced them at a pace that was predictably fast and oftentimes hard to follow here's a quick list of most of them with some comments on each the big big news is the announcement with netapp netapp and aws have engineered a solution which ports the rich netapp stack onto aws and will be delivered as a fully managed service this is a big deal because previously customers either had they had to make a trade-off they had a settle for cloud-based file service with less functionality than you could get with netapp on-prem or it had to lose the agility and elasticity of the cloud and the whole pay-by-the-drink model now customers can get access to a fully functional netapp stack with services like data reduction snaps clones the full multi-protocol support replication all the services ontap delivers in the cloud as a managed service through the aws console our estimate is that 80 of the data on-prem is stored in file format and that's not the revenue but that's the data and we all know about s3 object storage but the biggest market from a capacity standpoint is file storage you know this announcement reminds us quite a bit of the vmware cloud on aws deal but applied to storage netapp's aunt anthony lai told me dave this is bigger and we're going to come back to that in a moment aws announced s3 multi-region access points it's a service that optimizes storage performance it takes into account latency network congestion and the location of data copies to deliver data via the best route to ensure our best performance this is something we've talked about for quite some time using metadata to optimize that that access aws also announced improvements to s3 tiering where it will no longer charge for small objects of less than 128k so for example customers won't be charged for most metadata and other smaller objects remember aws years ago hired a bunch of emc engineers and those guys built a lot of tiering functionality into their boxes and we'll come back to that later in this episode aws also announced backup and monitoring tools to ensure backups are in compliance with regulations and corporate edicts this frankly is table stakes and was was overdue in my view aws also made a number of other announcements that have been well covered in the press around block storage and simplified data migration tools so we'll leave that to your perusal through other outlets i want to come back to the big picture on the market dynamics now as we've reported in previous breaking analysis segments aws storage revenue is on a path to 10 billion dollars we reported this last year this chart puts the market in context it shows our estimates for worldwide enterprise storage revenue in the calendar year 2021. this data is meant to include all storage revenue including primary secondary and archival storage and related maintenance services dell is the leader in the 60 billion market with aws now hot on its tail with 15 of the market in terms of the way we've cut it now in the pre-cloud days customers would tell us our storage strategy is the following we buy emc for block and netapp for file keeping it simple while remnants of this past habit continue the market is definitely changing as you can see here the companies highlighted in red represent the growing hyperscaler presence and you can see in the pi on the right they now account for around 25 percent of the market and they're growing much much faster than the on-prem vendors well over that thousand basis points when you combine them all a couple of other things to note in the data we're excluding kindrel from ibm's figures that's ibm spinout but including our estimates of storage software for example spectrums protect that is sold as part of the ibm cloud but not reported in ibm's income statement by the way pre-kindred spin ibm storage business we believe would approach the size of netapp's business now in the yellow we've highlighted the portion of hyper-converged that comprises storage this includes vmware nutanix cisco and others vmware and nutanix are the largest hci players but in total the storage piece of that market is less than two billion okay so the way to look at this market is changing traditional on-prem is vying for budgets with cloud storage services which are rapidly gaining presence in the market and we're seeing the on-prem piece evolve of course into as a service models with hpe's green lake dell's apex and other on-prem cloud-like models now let's come back to the netapp aws deal netapp as we know is the gold standard for file services they've been the market leader for a long long time and other than pure which is considerably smaller netapp is the one company that consistently was able to beat emc in the market emc developed its its nas business and developed on its own nasdaq and it bought isilon to compete with netapp with isilon's excellent global file system but generally netapp remains the best file storage company today now emerging disruptors like cumulo vast weka they would take issue with this statement and rightly so as they have really promising technology but netapp remains the king of the file hill you can't debate that now netapp however has had some serious headwinds as the largest independent storage player as seen in this etr chart the data shows a nine-year view of netapp's presence in the etr survey presence is referred to by etr as market share it's not traditional market share it measures the pervasiveness of responses in the etr survey over a thousand customers each quarter so the percentage of mentions essentially that netapp is getting and you can see well netapp remains a leader it has had a difficult time expanding its tam and it's become frankly less relevant in the eye in the grand scheme and the grand eyes of it buyers the company hit headwinds when it began migrating its base to ontap 8 and was late riding a number of new waves including flash but generally it is recovered from those headwinds and it's really now focused on the cloud opportunity opportunity as evidenced by this deal with aws now as i said earlier netapp evp anthony lai told me that this deal is bigger than vmware cloud on aws like me you may be wondering how can that be vmware is the leader in the data center it has half a million customers its deal with aws has been a tremendous success as seen in this etr chart the data here shows spending momentum or net score from when vmware cloud on aws was picked up in the etr surveys with a meaningful n which today is approaching 100 responses in the survey the yellow line is there for context it's vmware's overall business so repeat it buyers who responded vmware versus specifically vmware cloud on aws so you see vmware overall has a huge presence in the survey more than 600 n the red line is vmware cloud on aws and that red dotted line you see that that's that's my magic 40 mark anything above that line we consider elevated net score or spending velocity and while we saw some deceleration earlier this year in that line that top line for vmware cloud vmware cloud and aws has been consistently showing well in the survey well above that 40 percent line so could this netapp deal be bigger than vmware cloud on aws well probably not in our view but we like the strategy of netapp going cloud native on aws and aws's commitment to deliver this as a managed service now where could get interesting is across clouds in other words if netapp can take a page out of snowflake and build an abstraction layer that hides the underlying complexity of not only the aws cloud but also gcp and azure where you log into the netapp cloud netapp data cloud if you will just go ahead and steal steal it from snowflake and then netapp optimizes your on-prem your aws your azure and or your gcp file storage we see that as a winning strategy that could dramatically expand netapp's tam politically it may not sit well with aws but so what netapp has to go multi-cloud to expand that tam when the vmware deal was announced many people felt it was a one-way street where all the benefit would eventually accrue to aws in reality this has certainly been a near-term winner for aws and vmware and of course importantly vmware and aws join customers now longer term it's going to clearly be a win for aws because it gets access to vmware's customer base but we also think it will serve vmware well because it gives the company a clear and concise cloud strategy especially if it can go across clouds and eventually get to the edge so with this netapp aws deal will it be as big probably not in our view but it is big netapp in our view just leapfrogged the competition because of the deep engineering commitment aws has made this isn't a marketplace deal it's a native managed service and we think that's pretty huge okay we're going to close with a few thoughts on aws storage strategy and some other thoughts on hybrid talk about capturing mission critical workloads and where aws fits in the overall data mesh conversation which is one of our favorite topics first let's talk about aws's storage strategy overall as with other services aws approach is to give builders access to tools at a very granular level that means it does mean a lot of apis and access to primitives that are essentially building blocks while this may require greater developer skills it also allows aws to get to market quickly and add functionality faster than the competition enterprises however where they will pay up for solutions so this leaves some nice white space for partners and also competitors and especially the on-prem folks but let's hear from an aws executive i spoke to milan thompson bucheveck an aws vp on the cube and asked her to describe aws's storage strategy here's what she said play the clip we are dynamically and constantly evolving our aws storage services based on what the application and the customer want that is fundamentally what we do every day we talked a little bit about those deployments that are happening right now dave that is something that idea of constant dynamic evolution just can't be replicated by on-premises where you buy a box and it sits in your data center for three or more years and what's unique about us among the cloud services is again that perspective of the 15 years where we are building applications in ways that are unique because we have more customers and we have more customers doing more things so you know i i've said this before uh it's all about speed of innovation dave time and change wait for no one and if you're a business and you're trying to transform your business and base it on a set of technologies that change rapidly you have to use aws services i mean if you look at some of the launches that we talk about today and you think about s3's multi-region access points that's a fundamental change for customers that want to store copies of their data in any number of different regions and get a 60 performance improvement by leveraging the technology that we've built up over over time the the ability for us to route to intelligently router requests across our network that and fsx for netapp ontap nobody else has these capabilities today and it's because we are at the forefront of talking to different customers and that dynamic evolution of storage that's the core of our strategy so as you hear and can see by milan's statements how these guys think outside the box mentality at the end of the day customers want rock solid storage that's dirt cheap and lightning fast they always have and they always will but what i'm hearing from aws is they think about delivering these capabilities in the broader context of an application or a business think deeper business integration not the traditional suppliers don't think about that as well but the services mentality the cloud services mentality is different than dropping off a box at a loading dock turning it over to a professional services organization and then moving on to the next deal now i also had a chance to speak with wayne dusso he's another aws vp in the storage group wayne do so is a long time tech athlete for years he was responsible for building storage arrays at emc aws as i said hired a bunch of emcs years ago and those guys did a lot of tiered storage so i asked wayne what's the difference in mentality when you're building boxes versus cloud services here's what he said you have physical constraints you have to worry about the physical resources on that device for the life of that device which is years think about what changes in three or five years think about the last two years alone and what's changed can you imagine having being constrained by only uh having boxes available to you during this last two years versus having the cloud and being able to expand or contract based on your business needs that would be really tough right and it has been tough and that's why we've seen customers from every industry accelerate uh their use of the cloud during these last two years so i get that so what's your mindset when you're building storage services and data services so so each of the surfaces that we have in object block file movement services data services each of them provides very specific customer value in each are deeply integrated with the rest of aws so that when you need object services you start using them the integrations come along with you when if you're using traditional block we talked about ebs io2 block express when using file just the example alone today with ontap you know you get to use what you need when you need it and the way that you're used to using it without any concern so so the big difference is no constraints in the box but lots of opportunities to blend in with other services now all that said there are cases where the box is gonna win because of locality and and physics and latency issues you know particularly where latency is king that's where a box is gonna be advantageous and we'll come back to that in a bit okay but what about hybrid how does aws think about hybrid and on-prem here's my take and then let's hear from milan again the cloud is expanding it's moving out to the edge and aws looks at the data center as just another edge node and it's bringing its infrastructure as code mentality to that edge and of course to data centers so if aws is truly customer centric which we believe it is it will naturally have to accommodate on-prem use cases and it is doing just that here's how milan thompson-bucheveck explained how aws is thinking about hybrid roll the clip for us dave it always comes back to what the customer is asking for and we were talking to customers and they were talking about their edge and what they wanted to do with it we said how are we going to help and so if i just take s3 for outposts as an example or ebs and outposts you know we have customers like morningstar and morningstar wants outposts because they are using it as a step in their journey to being on the cloud if you take a customer like first adudabi bank they're using outposts because they need data residency for their compliance requirements and then we have other customers that are using outposts to help like dish networks as an example to place the storage as close as account to the applications for low latency all of those are customer driven requirements for their architecture for us dave we think in the fullness of time every customer and all applications are going to be on the cloud because it makes sense and those businesses need that speed of innovation but when we build things like our announcement today of fxs for netapp ontap we build them because customers asked us to help them with their journey to the cloud just like we built s3 and evs for outposts for the same reason so look this is a case where the box or the appliance wins latency matters as we said and aws gets that this is where matt baker of dell is right it's not a zero-sum game this is especially accurate as it pertains to the cloud versus on-prem discussion but a budget dollar is a budget dollar and the dollar can't go to two places so the battle will come down to who has the best solution the best relationships and who can deliver the most rock solid storage at the lowest cost and highest performance let's take a look at mission critical workloads for a second we're seeing aws go after these it's doing a database it's doing it with block storage we're talking about oracle sap microsoft sql server db2 that kind of stuff high volume oltp transactions mission critical work now there's no doubt that aws is picking up a lot of low hanging fruit with business critical workloads but the really hard to move work isn't going without a fight frankly it's not going that fast aws and mace has made some improvements to block storage to remove some of the challenges related but generally we see this is a very long road ahead for aws and other cloud suppliers oracle is the king of mission critical work along with ibm mainframes and those infrastructures generally it's not easy to move to the cloud it's too risky it's too expensive and the business case oftentimes isn't there because very frequently you have to freeze applications to do so what generally what people are doing is they're building an abstraction layer over that putting that abstraction layer maybe in the cloud building new apps that can connect to the back end and the into the cloud but that back end is largely cemented and fossilized look it's all in the definition no doubt there's plenty of mission critical work that is going to move but just really depends on how you define it even aws struggles to move its most critical transaction systems off of oracle but we'll continue to keep an open mind there it's just that today we define the most mission-critical workloads as we define them we don't see a lot of movement to the hyperscale clouds and we're going to close with some thoughts on data mesh so one of our favorite topics we've written extensively about this and interviewed and are collaborating with jamaa dagani who has coined the term and we've announced a media collaboration with the data mesh community and believe it's a strong direction for the industry so we wanted to understand how aws thinks about data mesh and where it fits in the conversation here's what milan had to say about that play the clip we have customers today that are taking the data mesh architectures and implementing them with aws services and dave i want to go back to the start of amazon when amazon first began we grew because the amazon technologies were built in microservices fundamentally a data match is about separation or abstraction of what individual components do and so if i look at data mesh really you're talking about two things you're talking about separating the data storage and the characteristics of data from the data services that interact and operate on that storage and with data mesh it's all about making sure that the businesses the decentralized business model can work with that data now our aws customers are putting their storage in a centralized place because it's easier to track it's easier to view compliance and it's easier to predict growth and control costs but we started with building blocks and we deliberately built our storage services separate from our data services so we have data services like lake formation and glue we have a number of these data services that our customers are using to build that customized data mesh on top of that centralized storage so really it's about at the end of the day speed it's about innovation it's about making sure that you can decentralize and separate your data services from your storage so businesses can go faster so it's very true that aws has customers that are implementing data mess data mesh data mess data mesh can be a data mess if you don't do it right jpmorgan chase is a firm that is doing that we've we've covered that they've got a great video out there check out the breaking analysis archive you'll see that hellofresh has also initiated a data mesh architecture in the cloud and several others are starting to pop up i think the point is the issues and challenges around data mesh are more organizational and process related and less focused on the technology platform look data by its very nature is decentralized so when mylan talks about customers building on centralized storage that's a logical view of the storage but not necessarily physically centralized it may be in a in a hybrid device it may be a copy that lives outside of that same physical location this is an important point as jpmorgan chase pointed out the data mesh must accommodate data products and services that are in the cloud and also on-prem it's got to be inclusive the data mesh looks at the data store as a node on the data mesh it shouldn't be confined by the technology whether it's a data warehouse a data hub a data mart or an s3 bucket so i would say this while people think of the cloud as a centralized walled garden and in many respects it is that very same cloud is expanding into a massively distributed architecture and that fits with the data mesh architectural model as i say the big challenges of data mesh are less technical and more cultural and we're super excited to see how data mesh plays out over time and we're really excited to be part of part of the the community and a media partner of the data mesh community okay that's it for now remember i publish each week on wikibon.com and siliconangle.com and these episodes they're all available as podcasts all you do is search for breaking analysis podcasts you can always connect on twitter i'm at d vellante or email me at david.velante at siliconangle.com i appreciate the comments you guys make on linkedin and don't forget to check out etr.plus for all the survey action this is dave vellante for the cube insights powered by etr be well and we'll see you next time [Music] you

>>from around the >>globe. It's the Cube with digital coverage of AWS reinvent 2020 sponsored by Intel and AWS. Yeah, >>Hi. We are the Cube live covering AWS reinvent 2020. I'm Lisa Martin, and I've got one of our cube alumni back with me. Mike Miller is here. General manager of A W s AI Devices at AWS. Mike, welcome back to the Cube. >>Hi, Lisa. Thank you so much for having me. It's really great to join you all again at this virtual reinvent. >>Yes, I think last year you were on set. We have always had to. That's at reinvent. And you you had the deep race, your car, and so we're obviously socially distance here. But talk to me about deepracer. What's going on? Some of the things that have gone on the last year that you're excited >>about. Yeah, I'd love to tell. Tell you a little bit about what's been happening. We've had a tremendous year. Obviously, Cove. It has restricted our ability to have our in person races. Eso we've really gone gone gangbusters with our virtual league. So we have monthly races for competitors that culminate in the championship. Um, at reinvent. So this year we've got over 100 competitors who have qualified and who are racing virtually with us this year at reinvent. They're participating in a series of knockout rounds that are being broadcast live on twitch over the next week. That will whittle the group down to AH Group of 32 which will have a Siris of single elimination brackets leading to eight finalists who will race Grand Prix style five laps, eight cars on the track at the same time and will crown the champion at the closing keynote on December 15th this year. >>Exciting? So you're bringing a reinforcement, learning together with with sports that so many of us have been missing during the pandemic. We talked to me a little bit about some of the things that air that you've improved with Deep Racer and some of the things that are coming next year. Yeah, >>absolutely so, First of all, Deep Racer not only has been interesting for individuals to participate in the league, but we continue to see great traction and adoption amongst big customers on dare, using Deep Racer for hands on learning for machine learning, and many of them are turning to Deep Racer to train their workforce in machine learning. So over 150 customers from the likes of Capital One Moody's, Accenture, DBS Bank, JPMorgan Chase, BMW and Toyota have held Deep Racer events for their workforces. And in fact, three of those customers Accenture, DBS Bank and J. P. Morgan Chase have each trained over 1000 employees in their organization because they're just super excited. And they find that deep racers away to drive that excitement and engagement across their customers. We even have Capital one expanded this to their families, so Capital One ran a deep raise. Their Kids Cup, a family friendly virtual competition this past year were over. 250 Children and 200 families got to get hands on with machine learning. >>So I envisioned some. You know, this being a big facilitator during the pandemic when there's been this massive shift to remote work has have you seen an uptick in it for companies that talking about training need to be ableto higher? Many, many more people remotely but also train them? Is deep Racer facilitator of that? Yeah, >>absolutely. Deep Racer has ah core component of the experience, which is all virtualized. So we have, ah, console and integration with other AWS services so that racers can participate using a three d racing simulator. They can actually see their car driving around a track in a three D world simulation. Um, we're also selling the physical devices. So you know, if participants want to get the one of those devices and translate what they've done in the virtual world to the real world, they can start doing that. And in fact, just this past year, we made our deep race or car available for purchase internationally through the Amazon Com website to help facilitate that. >>So how maney deep racers air out there? I'm just curious. >>Oh, thousands. Um, you know, And there what? What we've seen is some companies will purchase you, know them in bulk and use them for their internal leagues. Just like you know, JP Morgan Chase on DBS Bank. These folks have their own kind of tracks and racers that they'll use to facilitate both in person as well as the virtual racing. >>I'm curious with this shift to remote that we mentioned a minute ago. How are you seeing deepracer as a facilitator of engagement. You mentioned engagement. And that's one of the biggest challenges that so Maney teams develops. Processes have without being co located with each other deep Brister help with that. I mean, from an engagement perspective, I think >>so. What we've seen is that Deep Racer is just fun to get your hands on. And we really lower the learning curve for machine learning. And in particular, this branch called reinforcement Learning, which is where you train this agent through trial and error toe, learn how to do a new, complex task. Um, and what we've seen is that customers who have introduced Deep Racer, um, as an event for their employees have seen ah, very wide variety of employees. Skill sets, um, kind of get engaged. So you've got not just the hardcore deep data scientists or the M L engineers. You've got Web front end programmers. You even have some non technical folks who want to get their hands dirty. Onda learn about machine learning and Deep Racer really is a nice, gradual introduction to doing that. You can get engaged with it with very little kind of coding knowledge at all. >>So talk to me about some of the new services. And let's look at some specific use case customer use cases with each service. Yeah, >>absolutely. So just to set the context. You know, Amazon's got hundreds. A ws has hundreds of thousands of customers doing machine learning on AWS. No customers of all sizes are embedding machine learning into their no core business processes. And one of the things that we always do it Amazon is We're listening to customers. You know, 90 to 95% of our road maps are driven by customer feedback. And so, as we've been talking to these industrial manufacturing customers, they've been telling us, Hey, we've got data. We've got these processes that are happening in our industrial sites. Um, and we just need some help connecting the dots like, how do we really most effectively use machine learning to improve our processes in these industrial and manufacturing sites? And so we've come up with these five services. They're focused on industrial manufacturing customers, uh, two of the services air focused around, um, predictive maintenance and, uh, the other three services air focused on computer vision. Um, and so let's start with the predictive maintenance side. So we announced Amazon Monitor On and Amazon look out for equipment. So these services both enable predictive maintenance powered by machine learning in a way that doesn't require the customer to have any machine learning expertise. So Mono Tron is an end to end machine learning system with sensors, gateway and an ML service that can detect anomalies and predict when industrial equipment will require maintenance. I've actually got a couple examples here of the sensors in the gateway, so this is Amazon monitor on these little sensors. This little guy is a vibration and temperature sensor that's battery operated, and wireless connects to the gateway, which then transfers the data up to the M L Service in the cloud. And what happens is, um, the sensors can be connected to any rotating machinery like pump. Pour a fan or a compressor, and they will send data up to the machine learning cloud service, which will detect anomalies or sort of irregular kind of sensor readings and then alert via a mobile app. Just a tech or a maintenance technician at an industrial site to go have a look at their equipment and do some preventative maintenance. So um, it's super extreme line to end to end and easy for, you know, a company that has no machine learning expertise to take advantage of >>really helping them get on board quite quickly. Yeah, >>absolutely. It's simple tea set up. There's really very little configuration. It's just a matter of placing the sensors, pairing them up with the mobile app and you're off and running. >>Excellent. I like easy. So some of the other use cases? Yeah, absolutely. >>So So we've seen. So Amazon fulfillment centers actually have, um, enormous amounts of equipment you can imagine, you know, the size of an Amazon fulfillment center. 28 football fields, long miles of conveyor belts and Amazon fulfillment centers have started to use Amazon monitor on, uh, to monitor some of their conveyor belts. And we've got a filament center in Germany that has started using these 1000 sensors, and they've already been able to, you know, do predictive maintenance and prevent downtime, which is super costly, you know, for businesses, we've also got customers like Fender, you know, who makes guitars and amplifiers and musical equipment. Here in the US, they're adopting Amazon monitor on for their industrial machinery, um, to help prevent downtime, which again can cost them a great deal as they kind of hand manufacture these high end guitars. Then there's Amazon. Look out for equipment, which is one step further from Amazon monitor on Amazon. Look out for equipment. Um provides a way for customers to send their own sensor data to AWS in order to build and train a model that returns predictions for detecting abnormal equipment behavior. So here we have a customer, for example, like GP uh, E P s in South Korea, or I'm sorry, g S E P s in South Korea there in industrial conglomerate, and they've been collecting their own data. So they have their own sensors from industrial equipment for a decade. And they've been using just kind of rule basic rules based systems to try to gain insight into that data. Well, now they're using Amazon, look out for equipment to take all of their existing sensor data, have Amazon for equipment, automatically generate machine learning models on, then process the sensor data to know when they're abnormalities or when some predictive maintenance needs to occur. >>So you've got the capabilities of working with with customers and industry that that don't have any ML training to those that do have been using sensors. So really, everybody has an opportunity here to leverage this new Amazon technology, not only for predicted, but one of the things I'm hearing is contact list, being able to understand what's going on without having to have someone physically there unless there is an issue in contact. This is not one of the words of 2020 but I think it probably should be. >>Yeah, absolutely. And in fact, that that was some of the genesis of some of the next industrial services that we announced that are based on computer vision. What we saw on what we heard when talking to these customers is they have what we call human inspection processes or manual inspection processes that are required today for everything from, you know, monitoring you like workplace safety, too, you know, quality of goods coming off of a machinery line or monitoring their yard and sort of their, you know, truck entry and exit on their looking for computer vision toe automate a lot of these tasks. And so we just announced a couple new services that use computer vision to do that to automate these once previously manual inspection tasks. So let's start with a W A. W s Panorama uses computer vision toe improve those operations and workplace safety. AWS Panorama is, uh, comes in two flavors. There's an appliance, which is, ah, box like this. Um, it basically can go get installed on your network, and it will automatically discover and start processing the video feeds from existing cameras. So there's no additional capital expense to take a W s panorama and have it apply computer vision to the cameras that you've already got deployed, you know, So customers are are seeing that, um, you know, computer vision is valuable, but the reason they want to do this at the edge and put this computer vision on site is because sometimes they need to make very low Leighton see decisions where if you have, like a fast moving industrial process, you can use computer vision. But I don't really want to incur the cost of sending data to the cloud and back. I need to make a split second decision, so we need machine learning that happens on premise. Sometimes they don't want to stream high bandwidth video. Or they just don't have the bandwidth to get this video back to the cloud and sometimes their data governance or privacy restrictions that restrict the company's ability to send images or video from their site, um, off site to the cloud. And so this is why Panorama takes this machine learning and makes it happen right here on the edge for customers. So we've got customers like Cargill who uses or who is going to use Panorama to improve their yard management. They wanna use computer vision to detect the size of trucks that drive into their granaries and then automatically assign them to an appropriately sized loading dock. You've got a customer like Siemens Mobility who you know, works with municipalities on, you know, traffic on by other transport solutions. They're going to use AWS Panorama to take advantage of those existing kind of traffic cameras and build machine learning models that can, you know, improve congestion, allocate curbside space, optimize parking. We've also got retail customers. For instance, Parkland is a Canadian fuel station, um, and retailer, you know, like a little quick stop, and they want to use Panorama to do things like count the people coming in and out of their stores and do heat maps like, Where are people visiting my store so I can optimize retail promotions and product placement? >>That's fantastic. The number of use cases is just, I imagine if we had more time like you could keep going and going. But thank you so much for not only sharing what's going on with Deep Racer and the innovations, but also for show until even though we weren't in person at reinvent this year, Great to have you back on the Cube. Mike. We appreciate your time. Yeah, thanks, Lisa, for having me. I appreciate it for Mike Miller. I'm Lisa Martin. You're watching the cubes Live coverage of aws reinvent 2020.

>> Data is at the heart of transformation and the change every company needs to succeed, but it takes more than new technology. It's about teams, talent and cultural change. Empowering everyone on the front lines to make decisions all at the speed of digital. The transformation starts with you. It's time to lead the way it's time for Thought leaders. >> Welcome to "Thought Leaders" a digital event brought to you by ThoughtSpot. My name is Dave Vellante. The purpose of this day is to bring industry leaders and experts together to really try and understand the important issues around digital transformation. We have an amazing lineup of speakers and our goal is to provide you with some best practices that you can bring back and apply to your organization. Look, data is plentiful, but insights are not. ThoughtSpot is disrupting analytics by using search and machine intelligence to simplify data analysis and really empower anyone with fast access to relevant data. But in the last 150 days, we've had more questions than answers. Creating an organization that puts data and insights at their core requires not only modern technology, but leadership, a mindset and a culture that people often refer to as data-driven. What does that mean? How can we equip our teams with data and fast access to quality information that can turn insights into action. And today we're going to hear from experienced leaders who are transforming their organizations with data, insights and creating digital first cultures. But before we introduce our speakers, I'm joined today by two of my co-hosts from ThoughtSpot first chief data strategy officer at the ThoughtSpot is Cindi Howson. Cindi is an analytics and BI expert with 20 plus years experience and the author of "Successful Business Intelligence "Unlock the Value of BI & Big Data." Cindi was previously the lead analyst at Gartner for the data and analytics magic quadrant. And early last year, she joined ThoughtSpot to help CDOs and their teams understand how best to leverage analytics and AI for digital transformation. Cindi, great to see you welcome to the show. >> Thank you, Dave. Nice to join you virtually. >> Now our second cohost and friend of the cube is ThoughtSpot CEO Sudheesh Nair Hello, Sudheesh how are you doing today? >> I'm well Dave, it's good to talk to you again. >> It's great to see you thanks so much for being here. Now Sudheesh please share with us why this discussion is so important to your customers and of course, to our audience and what they're going to learn today. (upbeat music) >> Thanks, Dave. I wish you were there to introduce me into every room and that I walk into because you have such an amazing way of doing it. Makes me feel all so good. Look, since we have all been cooped up in our homes, I know that the vendors like us, we have amped up our sort of effort to reach out to you with invites for events like this. So we are getting very more invites for events like this than ever before. So when we started planning for this, we had three clear goals that we wanted to accomplish. And our first one that when you finish this and walk away, we want to make sure that you don't feel like it was a waste of time. We want to make sure that we value your time and this is going to be useful. Number two, we want to put you in touch with industry leaders and thought leaders, generally good people that you want to hang around with long after this event is over. And number three, as we plan through this, we are living through these difficult times. We want an event to be this event, to be more of an uplifting and inspiring event too. Now, the challenge is how do you do that with the team being change agents because change and as much as we romanticize it, it is not one of those uplifting things that everyone wants to do, or like to do. The way I think of it sort of like a, if you've ever done bungee jumping and it's like standing on the edges waiting to make that one more step, all you have to do is take that one step and gravity will do the rest, but that is the hardest step to take. Change requires a lot of courage. And when we are talking about data and analytics, which is already like such a hard topic, not necessarily an uplifting and positive conversation in most businesses, it is somewhat scary. Change becomes all the more difficult. Ultimately change requires courage. Courage to first of all challenge the status quo. People sometimes are afraid to challenge the status quo because they are thinking that maybe I don't have the power to make the change that the company needs. Sometimes they feel like I don't have the skills. Sometimes they may feel that I'm probably not the right person do it. Or sometimes the lack of courage manifest itself as the inability to sort of break the silos that are formed within the organizations, when it comes to data and insights that you talked about. There are people in the company who are going to hog the data because they know how to manage the data, how to inquire and extract. They know how to speak data. They have the skills to do that. But they are not the group of people who have sort of the knowledge, the experience of the business to ask the right questions off the data. So there is the silo of people with the answers, and there is a silo of people with the questions. And there is gap. This sort of silos are standing in the way of making that necessary change that we all know the business needs. And the last change to sort of bring an external force sometimes. It could be a tool. It could be a platform, it could be a person, it could be a process, but sometimes no matter how big the company is or how small the company is, you may need to bring some external stimuli to start the domino of the positive changes that are necessary. The group of people that we are brought in, the four people, including Cindi, that you will hear from today are really good at practically telling you how to make that step, how to step off that edge, how to dress the rope, that you will be safe and you're going to have fun. You will have that exhilarating feeling of jumping, for a bungee jump. All four of them are exceptional, but my honor is to introduce Michelle and she's our first speaker. Michelle, I am very happy after watching her presentation and reading our bio, that there are no country vital worldwide competition for cool patterns, because she will beat all of us because when her children were small, they were probably into Harry Potter and Disney. She was managing a business and leading change there. And then as her kids grew up and got to that age where they like football and NFL, guess what? She's the CIO of NFL. What a cool mom? I am extremely excited to see what she's going to talk about. I've seen the slides, tons of amazing pictures. I'm looking to see the context behind it. I'm very thrilled to make the acquaintance of Michelle and looking forward to her talk next. Welcome Michelle, it's over to you. (upbeat music) >> I'm delighted to be with you all today to talk about thought leadership. And I'm so excited that you asked me to join you because today I get to be a quarterback. I always wanted to be one. And I thought this is about as close as I'm ever going to get. So I want to talk to you about quarterbacking, our digital revolution using insights data. And of course, as you said, leadership, first a little bit about myself, a little background, as I said, I always wanted to play football. And this is something that I wanted to do since I was a child. But when I grew up, girls didn't get to play football. I'm so happy that that's changing and girls are now doing all kinds of things that they didn't get to do before. Just this past weekend on an NFL field, we had a female coach on two sidelines and a female official on the field. I'm a lifelong fan and student of the game of football. I grew up in the South. You can tell from the accent. And in the South football is like a religion and you pick sides. I chose Auburn university working in the athletic department. So I'm Testament to you can start the journey can be long. It took me many, many years to make it into professional sports. I graduated in 1987 and my little brother, well, not actually not so little. He played offensive line for the Alabama Crimson Tide. And for those of you who know SCC football, you know this is a really big rivalry. And when you choose sides, your family is divided. So it's kind of fun for me to always tell the story that my dad knew his kid would make it to the NFL. He just bet on the wrong one. My career has been about bringing people together for memorable moments at some of America's most iconic brands, delivering memories and amazing experiences that delight from Universal Studios, Disney to my current position as CIO of the NFL. In this job I'm very privileged to have the opportunity to work with the team that gets to bring America's game to millions of people around the world. Often I'm asked to talk about how to create amazing experiences for fans, guests, or customers. But today I really wanted to focus on something different and talk to you about being behind the scenes and backstage because behind every event, every game, every awesome moment is execution, precise, repeatable execution. And most of my career has been behind the scenes doing just that assembling teams to execute these plans. And the key way that companies operate at these exceptional levels is making good decisions, the right decisions at the right time and based upon data so that you can translate the data into intelligence and be a data-driven culture. Using data and intelligence is an important way that world-class companies do differentiate themselves. And it's the lifeblood of collaboration and innovation. Teams that are working on delivering these kinds of world casts experiences are often seeking out and leveraging next-generation technologies and finding new ways to work. I've been fortunate to work across three decades of emerging experiences, which each required emerging technologies to execute a little bit first about Disney in the 90s, I was at Disney leading a project called destination Disney, which it's a data project. It was a data project, but it was CRM before CRM was even cool. And then certainly before anything like a data-driven culture was ever brought up, but way back then we were creating a digital backbone that enabled many technologies for the things that you see today, like the magic band, Disney's magical express. My career at Disney began in finance, but Disney was very good about rotating you around. And it was during one of these rotations that I became very passionate about data. I kind of became a pain in the butt to the IT team asking for data more and more data. And I learned that all of that valuable data was locked up in our systems. All of our point of sales systems, our reservation systems, our operation systems. And so I became a shadow IT person in marketing, ultimately leading to moving into IT. And I haven't looked back since. In the early two thousands, I was at universal studios theme park as their CIO preparing for and launching "The Wizarding World of Harry Potter" bringing one of history's most memorable characters to life required many new technologies and a lot of data. Our data and technologies were embedded into the rides and attractions. I mean, how do you really think a wan selects you at a wan shop. As today at the NFL? I am constantly challenged to do leading edge technologies, using things like sensors, AI, machine learning, and all new communication strategies and using data to drive everything from player performance, contracts, to where we build new stadiums and hold events with this year being the most challenging yet rewarding year in my career at the NFL. In the middle of a global pandemic, the way we are executing on our season is leveraging data from contract tracing devices joined with testing data, talk about data, actually enabling your business without it w wouldn't be having a season right now. I'm also on the board of directors of two public companies where data and collaboration are paramount. First RingCentral, it's a cloud based unified communications platform and collaboration with video message and phone all in one solution in the cloud and Quotient technologies whose product is actually data. The tagline at Quotient is the result in knowing I think that's really important because not all of us are data companies where your product is actually data, but we should operate more like your product is data. I'd also like to talk to you about four areas of things to think about as thought leaders in your companies. First just hit on it is change how to be a champion and a driver of change. Second, how do you use data to drive performance for your company and measure performance of your company? Third, how companies now require intense collaboration to operate. And finally, how much of this is accomplished through solid data driven decisions. First let's hit on change. I mean, it's evident today more than ever, that we are in an environment of extreme change. I mean, we've all been at this for years and as technologists we've known it, believed it, lived it and thankfully for the most part, knock on what we were prepared for it. But this year everyone's cheese was moved. All the people in the back rooms, IT, data architects and others were suddenly called to the forefront because a global pandemic has turned out to be the thing that is driving intense change in how people work and analyze their business. On March 13th, we closed our office at the NFL in the middle of preparing for one of our biggest events, our kickoff event, the 2020 draft. We went from planning a large event in Las Vegas under the bright lights, red carpet stage to smaller events in club facilities. And then ultimately to one where everyone coaches GM's prospects and even our commissioner were at home in their basements. And we only had a few weeks to figure it out. I found myself for the first time being in the live broadcast event space, talking about bungee jumping. This is really what it felt like. It was one in which no one felt comfortable because it had not been done before. But leading through this, I stepped up, but it was very scary. It was certainly very risky, but it ended up being all so rewarding when we did it. And as a result of this, some things will change forever. Second, managing performance. I mean, data should inform how you're doing and how to get your company to perform at it's level. Highest level. As an example, the NFL has always measured performance, obviously, and it is one of the purest examples of how performance directly impacts outcome. I mean, you can see performance on the field. You can see points being scored in stats, and you immediately know that impact those with the best stats usually when the games. The NFL has always recorded stats since the beginning of time here at the NFL a little this year is our 101 year and athletes ultimate success as a player has also always been greatly impacted by his stats. But what has changed for us is both how much more we can measure and the immediacy with which it can be measured. And I'm sure in your business it's the same. The amount of data you must have has got to have quadrupled and how fast you need it and how quickly you need to analyze it is so important. And it's very important to break the silos between the keys, to the data and the use of the data. Our next generation stats platform is taking data to a next level. It's powered by Amazon web services. And we gathered this data real-time from sensors that are on players' bodies. We gather it in real time, analyze it, display it online and on broadcast. And of course it's used to prepare week to week in addition to what is a normal coaching plan would be. We can now analyze, visualize route patterns, speed match-ups, et cetera. So much faster than ever before. We're continuing to roll out sensors too that will gather more and more information about a player's performance as it relates to their health and safety. The third trend is really, I think it's a big part of what we're feeling today and that is intense collaboration. And just for sort of historical purposes, it's important to think about for those of you that are IT professionals and developers, more than 10 years ago, agile practices began sweeping companies where small teams would work together rapidly in a very flexible, adaptive, and innovative way. And it proved to be transformational. However, today, of course, that is no longer just small teams, the next big wave of change. And we've seen it through this pandemic is that it's the whole enterprise that must collaborate and be agile. If I look back on my career, when I was at Disney, we owned everything 100%. We made a decision, we implemented it. We were a collaborative culture, but it was much easier to push change because you own the whole decision. If there was buy-in from the top down, you've got the people from the bottom up to do it and you executed. At Universal we were a joint venture. Our attractions and entertainment was licensed. Our hotels were owned and managed by other third parties. So influence and collaboration and how to share across companies became very important. And now here I am at the NFL and even the bigger ecosystem, we have 32 clubs that are all separate businesses. 31 different stadiums that are owned by a variety of people. We have licensees, we have sponsors, we have broadcast partners. So it seems that as my career has evolved, centralized control has gotten less and less and has been replaced by intense collaboration, not only within your own company, but across companies. The ability to work in a collaborative way across businesses and even other companies that has been a big key to my success in my career. I believe this whole vertical integration and big top-down decision-making is going by the wayside in favor of ecosystems that require cooperation yet competition to co-exist. I mean, the NFL is a great example of what we call co-op petition, which is cooperation and competition. We're in competition with each other, but we cooperate to make the company the best it can be. And at the heart of these items really are data driven decisions and culture. Data on its own isn't good enough. You must be able to turn it to insights. Partnerships between technology teams who usually hold the keys to the raw data and business units who have the knowledge to build the right decision models is key. If you're not already involved in this linkage, you should be. Data mining isn't new for sure. The availability of data is quadrupling and it's everywhere. How do you know what to even look at? How do you know where to begin? How do you know what questions to ask it's by using the tools that are available for visualization and analytics and knitting together strategies of the company. So it begins with first of all, making sure you do understand the strategy of the company. So in closing, just to wrap up a bit, many of you joined today, looking for thought leadership on how to be a change agent, a change champion, and how to lead through transformation. Some final thoughts are be brave and drive. Don't do the ride along program. It's very important to drive. Driving can be high risk, but it's also high reward. Embracing the uncertainty of what will happen is how you become brave. Get more and more comfortable with uncertainty, be calm and let data be your map on your journey. Thanks. >> Michelle, tank you so much. So you and I share a love of data and a love of football. You said you want to be the quarterback. I'm more an old line person. (Michelle and Cindi laughing) >> Well, then I can do my job without you. >> Great. And I'm getting the feeling now, Sudheesh is talking about bungee jumping. My vote is when we're past this pandemic, we both take them to the Delaware water gap and we do the cliff jumping. >> That sounds good, I'll watch. >> Yeah, you'll watch, okay. So Michelle, you have so many stakeholders when you're trying to prioritize the different voices. You have the players, you have the owners, you have the league, as you mentioned, the broadcasters, your partners here and football mamas like myself. How do you prioritize when there's so many different stakeholders that you need to satisfy? >> I think balancing across stakeholders starts with, aligning on a mission. And if you spend a lot of time understanding where everyone's coming from, and you can find the common thread that ties them all together, you sort of do get them to naturally prioritize their work. And I think that's very important. So for us, at the NFL and even at Disney, it was our core values and our core purpose, is so well known and when anything challenges that we're able to sort of lay that out. But as a change agent, you have to be very empathetic. And I would say empathy is probably your strongest skill if you're a change agent. And that means listening to every single stakeholder, even when they're yelling at you, even when they're telling you your technology doesn't work and you know that it's user error, or even when someone is just emotional about what's happening to them and that they're not comfortable with it. So I think being empathetic and having a mission and understanding it is sort of how I prioritize and balance. >> Yeah, empathy, a very popular word this year. I can imagine those coaches and owners yelling. So, thank you for your leadership here. So Michelle, I look forward to discussing this more with our other customers and disruptors joining us in a little bit. (upbeat music) So we're going to take a hard pivot now and go from football to Chernobyl. Chernobyl what went wrong? 1986, as the reactors were melting down, they had the data to say, this is going to be catastrophic. And yet the culture said, "no, we're perfect, hide it. "Don't dare tell anyone." Which meant they went ahead and had celebrations in Kiev. Even though that increased the exposure, the additional thousands getting cancer and 20,000 years before the ground around there can even be inhabited again, this is how powerful and detrimental a negative culture, a culture that is unable to confront the brutal facts that hides data. This is what we have to contend with. And this is why I want you to focus on having, fostering a data-driven culture. I don't want you to be a laggard. I want you to be a leader in using data to drive your digital transformation. So I'll talk about culture and technology. Is it really two sides of the same coin, real-world impacts and then some best practices you can use to and innovate your culture. Now, oftentimes I would talk about culture and I talk about technology. And recently a CDO said to me, "Cindi, I actually think this is two sides "of the same coin. "One reflects the other." What do you think? Let me walk you through this. So let's take a laggard. What does the technology look like? Is it based on 1990s BI and reporting largely parametrized reports, on premises data, warehouses, or not even that operational reports at best one enterprise data warehouse, very slow moving and collaboration is only email. What does that culture tell you? Maybe there's a lack of leadership to change, to do the hard work that Sudheesh referred to, or is there also a culture of fear, afraid of failure, resistance to change complacency. And sometimes that complacency it's not because people are lazy. It's because they've been so beaten down every time a new idea is presented. It's like, no we're measured on least cost to serve. So politics and distrust, whether it's between business and IT or individual stakeholders is the norm. So data is hoarded. Let's contrast that with a leader, a data and analytics leader, what is their technology look like? Augmented analytics search and AI driven insights, not on premises, but in the cloud and maybe multiple clouds. And the data is not in one place, but it's in a data Lake and in a data warehouse, a logical data warehouse. The collaboration is being a newer methods, whether it's Slack or teams allowing for that real time decisioning or investigating a particular data point. So what is the culture in the leaders? It's transparent and trust. There is a trust that data will not be used to punish that there is an ability to confront the bad news. It's innovation, valuing innovation in pursuit of the company goals, whether it's the best fan experience and player safety in the NFL or best serving your customers. It's innovative and collaborative. There's none of this. Oh, well, I didn't invent that. I'm not going to look at that. There's still pride of ownership, but it's collaborating to get to a better place faster. And people feel empowered to present new ideas to fail fast, and they're energized knowing that they're using the best technology and innovating at the pace that business requires. So data is democratized. And democratized, not just for power users or analysts, but really at the point of impact what we like to call the new decision-makers or really the frontline workers. So Harvard business review partnered with us to develop this study to say, just how important is this? We've been working at BI and analytics as an industry for more than 20 years. Why is it not at the front lines? Whether it's a doctor, a nurse, a coach, a supply chain manager, a warehouse manager, a financial services advisor. Everyone said that if our 87% said, they would be more successful if frontline workers were empowered with data driven insights, but they recognize they need new technology to be able to do that. It's not about learning hard tools. The sad reality, only 20% of organizations are actually doing this. These are the data-driven leaders. So this is the culture in technology. How did we get here? It's because state-of-the-art keeps changing. So the first-generation BI and analytics platforms were deployed on premises on small datasets, really just taking data out of ERP systems that were also on premises. And state-of-the-art was maybe getting a management report, an operational report. Over time visual-based data discovery vendors disrupted these traditional BI vendors, empowering now analysts to create visualizations with the flexibility on a desktop, sometimes larger data, sometimes coming from a data warehouse. The current state of the art though, Gartner calls it augmented analytics at ThoughtSpot, we call it search and AI driven analytics. And this was pioneered for large scale datasets, whether it's on premises or leveraging the cloud data warehouses. And I think this is an important point. Oftentimes you, the data and analytics leaders will look at these two components separately, but you have to look at the BI and analytics tier in lockstep with your data architectures to really get to the granular insights and to leverage the capabilities of AI. Now, if you've never seen ThoughtSpot, I'll just show you what this looks like. Instead of somebody hard coding, a report it's typing in search keywords and very robust keywords contains rank top bottom, getting to a visual visualization that then can be pinned to an existing Pin board that might also contain insights generated by an AI engine. So it's easy enough for that new decision maker, the business user, the non analyst to create themselves. Modernizing the data and analytics portfolio is hard because the pace of change has accelerated. You use to be able to create an investment place a bet for maybe 10 years, a few years ago, that time horizon was five years, now it's maybe three years and the time to maturity has also accelerated. So you have these different components, the search and AI tier, the data science tier, data preparation and virtualization. But I would also say equally important is the cloud data warehouse and pay attention to how well these analytics tools can unlock the value in these cloud data warehouses. So ThoughtSpot was the first to market with search and AI driven insights. Competitors have followed suit, but be careful if you look at products like power BI or SAP analytics cloud, they might demo well, but do they let you get to all the data without moving it in products like Snowflake, Amazon Redshift, or Azure synapse or Google big query, they do not. They require you to move it into a smaller in memory engine. So it's important how well these new products inter operate. the pace of change, its acceleration Gartner recently predicted that by 2022, 65% of analytical queries will be generated using search or NLP or even AI. And that is roughly three times the prediction they had just a couple years ago. So let's talk about the real world impact of culture. And if you read any of my books or used any of the maturity models out there, whether the Gartner IT score that I worked on, or the data warehousing Institute also has the money surety model. We talk about these five pillars to really become data-driven. As Michelle, I spoke about it's focusing on the business outcomes, leveraging all the data, including new data sources, it's the talent, the people, the technology, and also the processes. And often when I would talk about the people and the talent, I would lump the culture as part of that. But in the last year, as I've traveled the world and done these digital events for Thought leaders, you have told me now culture is absolutely so important. And so we've pulled it out as a separate pillar. And in fact, in polls that we've done in these events, look at how much more important culture is as a barrier to becoming data-driven it's three times as important as any of these other pillars. That's how critical it is. And let's take an example of where you can have great data, but if you don't have the right culture, there's devastating impacts. And I will say, I have been a loyal customer of Wells Fargo for more than 20 years. But look at what happened in the face of negative news with data, it said, "hey, we're not doing good cross selling, "customers do not have both a checking account "and a credit card and a savings account and a mortgage." They opened fake accounts facing billions in fines, change in leadership that even the CEO attributed to a toxic sales culture, and they're trying to fix this. But even recently there's been additional employee backlash saying the culture has not changed. Let's contrast that with some positive examples, Medtronic, a worldwide company in 150 countries around the world. They may not be a household name to you, but if you have a loved one or yourself, you have a pacemaker, spinal implant diabetes, you know this brand. And at the start of COVID when they knew their business would be slowing down, because hospitals would only be able to take care of COVID patients. They took the bold move of making their IP for ventilators publicly available. That is the power of a positive culture. Or Verizon, a major telecom organization looking at late payments of their customers. And even though the U.S federal government said, "well, you can't turn them off. They said, "we'll extend that even beyond "the mandated guidelines." And facing a slow down in the business because of the tough economy, they said, you know what? "We will spend the time up skilling our people, "giving them the time to learn more "about the future of work, the skills and data "and analytics," for 20,000 of their employees, rather than furloughing them. That is the power of a positive culture. So how can you transform your culture to the best in class? I'll give you three suggestions, bring in a change agent, identify the relevance, or I like to call it WIFM and organize for collaboration. So the CDO, whatever your title is, chief analytics officer, chief digital officer, you are the most important change agent. And this is where you will hear that oftentimes a change agent has to come from outside the organization. So this is where, for example, in Europe, you have the CDO of Just Eat a takeout food delivery organization coming from the airline industry or in Australia, National Australian bank, taking a CDO within the same sector from TD bank going to NAB. So these change agents come in disrupt. It's a hard job. As one of you said to me, it often feels like Sisyphus. I make one step forward and I get knocked down again. I get pushed back. It is not for the faint of heart, but it's the most important part of your job. The other thing I'll talk about is WIFM. What is in it for me? And this is really about understanding the motivation, the relevance that data has for everyone on the frontline, as well as those analysts, as well as the executives. So if we're talking about players in the NFL, they want to perform better and they want to stay safe. That is why data matters to them. If we're talking about financial services, this may be a wealth management advisor. Okay we could say commissions, but it's really helping people have their dreams come true, whether it's putting their children through college or being able to retire without having to work multiple jobs still into your 70s or 80s for the teachers, teachers, you ask them about data. They'll say we don't, we don't need that. I care about the student. So if you can use data to help a student perform better, that is WIFM. And sometimes we spend so much time talking the technology, we forget what is the value we're trying to deliver with it. And we forget the impact on the people that it does require change. In fact, the Harvard business review study found that 44% said lack of change management is the biggest barrier to leveraging both new technology, but also being empowered to act on those data-driven insights. The third point organize for collaboration. This does require diversity of thought, but also bringing the technology, the data and the business people together. Now there's not a single one size fits all model for data and analytics. At one point in time, even having a BICC, a BI competency center was considered state-of-the-art. Now for the biggest impact what I recommend is that you have a federated model centralized for economies of scale. That could be the common data, but then in bed, these evangelists, these analysts of the future within every business unit, every functional domain. And as you see this top bar, all models are possible, but the hybrid model has the most impact, the most leaders. So as we look ahead to the months ahead, to the year ahead an exciting time, because data is helping organizations better navigate a tough economy, lock in the customer loyalty. And I look forward to seeing how you foster that culture that's collaborative with empathy and bring the best of technology, leveraging the cloud, all your data. So thank you for joining us at Thought Leaders. And next I'm pleased to introduce our first change agent, Tom Mazzaferro chief data officer of Western union. And before joining Western union, Tom made his Mark at HSBC and JPMorgan Chase spearheading digital innovation in technology, operations, risk compliance, and retail banking. Tom, thank you so much for joining us today. (upbeat music) >> Very happy to be here and looking forward to talking to all of you today. So as we look to move organizations to a data-driven, capability into the future, there is a lot that needs to be done on the data side, but also how does data connect and enable different business teams and technology teams into the future. As you look across, our data ecosystems and our platforms and how we modernize that to the cloud in the future, it all needs to basically work together, right? To really be able to drive and over the shift from a data standpoint, into the future, that includes being able to have the right information with the right quality of data, at the right time to drive informed business decisions, to drive the business forward. As part of that, we actually have partnered with ThoughtSpot, to actually bring in the technology to help us drive that as part of that partnership. And it's how we've looked to integrate it into our overall business as a whole we've looked at how do we make sure that our business and our professional lives right, are enabled in the same ways as our personal lives. So for example, in your personal lives, when you want to go and find something out, what do you do? You go onto google.com or you go on to Bing we go onto Yahoo and you search for what you want search to find and answer. ThoughtSpot for us as the same thing, but in the business world. So using ThoughtSpot and other AI capability it's allowed us to actually, enable our overall business teams in our company to actually have our information at our fingertips. So rather than having to go and talk to someone or an engineer to go pull information or pull data, we actually can have the end-users or the business executives, right. Search for what they need, what they want at the exact time that action need it to go and drive the business forward. This is truly one of those transformational things that we've put in place. On top of that, we are on the journey to modernize our larger ecosystem as a whole. That includes modernizing our underlying data warehouses, our technology, or our Eloqua environments. And as we move that, we've actually picked two of our cloud providers going to AWS and GCP. We've also adopted Snowflake to really drive and to organize our information and our data then drive these new solutions and capabilities forward. So they portion of us though is culture. So how do we engage with the business teams and bring the IT teams together to really drive these holistic end to end solutions and capabilities to really support the actual business into the future? That's one of the keys here, as we look to modernize and to really enhance our organizations to become data-driven, this is the key. If you can really start to provide answers to business questions before they're even being asked and to predict based upon different economic trends or different trends in your business, what does this is maybe be made and actually provide those answers to the business teams before they're even asking for it, that is really becoming a data-driven organization. And as part of that, it's really then enables the business to act quickly and take advantage of opportunities as they come in based upon, industries based upon markets, based upon products, solutions, or partnerships into the future. These are really some of the keys that become crucial as you move forward, right, into this new age, especially with COVID. With COVID now taking place across the world, right? Many of these markets, many of these digital transformations are accelerating and are changing rapidly to accommodate and to support customers in these very difficult times, as part of that, you need to make sure you have the right underlying foundation ecosystems and solutions to really drive those capabilities and those solutions forward. As we go through this journey, both of my career, but also each of your careers into the future, right? It also needs to evolve, right? Technology has changed so drastically in the last 10 years, and that change is only accelerating. So as part of that, you have to make sure that you stay up to speed, up to date with new technology changes both on the platform standpoint tools, but also what do our customers want? What do our customers need and how do we then service them with our information, with our data, with our platform and with our products and our services to meet those needs and to really support and service those customers into the future. This is all around becoming a more data organization such as how do you use your data to support the current business lines, but how do you actually use your information, your data to actually put a better support your customers, better support your business, better support your employees, your operations teams, and so forth, and really creating that full integration in that ecosystem is really when you start to get large dividends from this investments into the future. But that being said, hope you enjoy the segment on how to become and how to drive it data driven organization. And, looking forward to talking to you again soon. Thank you. >> Tom that was great thanks so much. Now I'm going to have to brag on you for a second as a change agent you've come in disrupted and how long have you been at Western union? >> Only nine months, so just started this year, but, doing some great opportunities and great changes. And we have a lot more to go, but, we're really driving things forward in partnership with our business teams and our colleagues to support those customers going forward. >> Tom, thank you so much. That was wonderful. And now I'm excited to introduce you to Gustavo Canton, a change agent that I've had the pleasure of working with meeting in Europe, and he is a serial change agent, most recently with Schneider electric, but even going back to Sam's clubs, Gustavo welcome. (upbeat music) >> So, hey everyone, my name is Gustavo Canton and thank you so much, Cindi, for the intro, as you mentioned, doing transformations is high effort, high reward situation. I have empowered many transformations and I have led many transformations. And what I can tell you is that it's really hard to predict the future, but if you have a North star and where you're going, the one thing that I want you to take away from this discussion today is that you need to be bold to evolve. And so in today, I'm going to be talking about culture and data, and I'm going to break this down in four areas. How do we get started barriers or opportunities as I see it, the value of AI, and also, how do you communicate, especially now in the workforce of today with so many different generations, you need to make sure that you are communicating in ways that are non-traditional sometimes. And so how do we get started? So I think the answer to that is you have to start for you yourself as a leader and stay tuned. And by that, I mean, you need to understand not only what is happening in your function or your field, but you have to be varying into what is happening in society, socioeconomically speaking wellbeing. The common example is a great example. And for me personally, it's an opportunity because the one core value that I have is well-being, I believe that for human potential, for customers and communities to grow wellbeing should be at the center of every decision. And as somebody mentioned is great to be, stay in tune and have the skillset and the courage. But for me personally, to be honest, to have this courage is not about not being afraid. You're always afraid when you're making big changes when you're swimming upstream, but what gives me the courage is the empathy part. Like I think empathy is a huge component because every time I go into an organization or a function, I try to listen very attentively to the needs of the business and what the leaders are trying to do. What I do it thinking about the mission of how do I make change for the bigger, workforce? for the bigger good. Despite this fact that this might have a perhaps implication on my own self-interest in my career, right? Because you have to have that courage sometimes to make choices that I know we'll see in politically speaking, what are the right thing to do? And you have to push through it. And you have to push through it. So the bottom line for me is that I don't think they're transforming fast enough. And the reality is I speak with a lot of leaders and we have seen stories in the past. And what they show is that if you look at the four main barriers that are basically keeping us behind budget, inability to act cultural issues, politics, and lack of alignment, those are the top four. But the interesting thing is that as Cindi has mentioned, these topics culture is actually gaining, gaining more and more traction. And in 2018, there was a story from HBR and it was about 45%. I believe today it's about 55%, 60% of respondents say that this is the main area that we need to focus on. So again, for all those leaders and all the executives who understand and are aware that we need to transform, commit to the transformation and set a state, deadline to say, "hey, in two years, we're going to make this happen. "What do we need to do to empower and enable "this change engines to make it happen?" You need to make the tough choices. And so to me, when I speak about being bold is about making the right choices now. So I'll give you samples of some of the roadblocks that I went through as I think transformation most recently, as Cindi mentioned in Schneider. There are three main areas, legacy mindset. And what that means is that we've been doing this in a specific way for a long time and here is how we have been successful what was working the past is not going to work now. The opportunity there is that there is a lot of leaders who have a digital mindset and there're up and coming leaders that are not yet fully developed. We need to mentor those leaders and take bets on some of these talent, including young talent. We cannot be thinking in the past and just wait for people, three to five years for them to develop because the world is going to in a way that is super fast. The second area, and this is specifically to implementation of AI is very interesting to me because just example that I have with ThoughtSpot, right, we went to implementation and a lot of the way is the IT team function of the leaders look at technology, they look at it from the prism of the prior all success criteria for the traditional Bi's. And that's not going to work. Again the opportunity here is that you need to really find what successful look like. In my case, I want the user experience of our workforce to be the same as user experience you have at home is a very simple concept. And so we need to think about how do we gain the user experience with this augmented analytics tools and then work backwards to have the right talent processes and technology to enable that. And finally, with COVID a lot of pressuring organizations, and companies to do more with less. And the solution that most leaders I see are taking is to just minimize costs, sometimes in cut budget, we have to do the opposite. We have to actually invest some growth areas, but do it by business question. Don't do it by function. If you actually invest in these kind of solutions, if you actually invest on developing your talent, your leadership to see more digitally, if you actually invest on fixing your data platform, it's not just an incremental cost. It's actually this investment is going to offset all those hidden costs and inefficiencies that you have on your system, because people are doing a lot of work and working very hard, but it's not efficiency, and it's not working in the way that you might want to work. So there is a lot of opportunity there. And you just to put into some perspective, there have studies in the past about, how do we kind of measure the impact of data. And obviously this is going to vary by your organization maturity, is going to, there's going to be a lot of factors. I've been in companies who have very clean, good data to work with. And I think with companies that we have to start basically from scratch. So it all depends on your maturity level, but in this study, what I think is interesting is they try to put attack line or attack price to what is the cost of incomplete data. So in this case, it's about 10 times as much to complete a unit of work when you have data that is flawed as opposed to have perfect data. So let me put that just in perspective, just as an example, right? Imagine you are trying to do something and you have to do 100 things in a project, and each time you do something, it's going to cost you a dollar. So if you have perfect data, the total cost of that project might be $100. But now let's say you have any percent perfect data and 20% flawed data by using this assumption that flawed data is 10 times as costly as perfect data. Your total costs now becomes $280 as opposed to $100. This is just for you to really think about as a CIO CTO, CHRO CEO, are we really paying attention and really closing the gaps that we have on our data infrastructure. If we don't do that, it's hard sometimes to see the snowball effect or to measure the overall impact. But as you can tell the price that goes up very, very quickly. So now, if I were to say, how do I communicate this? Or how do I break through some of these challenges or some of these various, right. I think the key is I am in analytics. I know statistics obviously, and love modeling and data and optimization theory and all that stuff. That's what I came to analytics. But now as a leader and as a change agent, I need to speak about value. And in this case, for example, for Schneider, there was this tagline called free up your energy. So the number one thing that they were asking from the analytics team was actually efficiency, which to me was very interesting. But once I understood that I understood what kind of language to use, how to connect it to the overall strategy and basically how to bring in the, the right leaders, because you need to focus on the leaders that you're going to make the most progress. Again, low effort, high value. You need to make sure you centralize all the data as you can. You need to bring in some kind of augmented analytics solution. And finally you need to make it super simple for the, in this case, I was working with the HR teams in other areas, so they can have access to one portal. They don't have to be confused in looking for 10 different places to find information. I think if you can actually have those four foundational pillars, obviously under the guise of having a data-driven culture, that's when you can actually make the impact. So in our case, it was about three years total transformation, but it was two years for this component of augmented analytics. It took about two years to talk to IT get leadership support, find the budgeting, get everybody on board, make sure the safe criteria was correct. And we call this initiative, the people analytics portal, it was actually launched in July of this year. And we were very excited and the audience was very excited to do this. In this case, we did our pilot in North America for many, many manufacturers. But one thing that is really important is as you bring along your audience on this, you're going from Excel, in some cases or Tableau to other tools like, ThoughtSpot, you need to really explain them what is the difference and how these tools can truly replace, some of the spreadsheets or some of the views that you might have on these other kind of tools. Again, Tableau, I think it's a really good tool. There are other many tools that you might have in your toolkit. But in my case, personally, I feel that you need to have one portal going back to Cindi's point. I really truly enable the end user. And I feel that this is the right solution for us, right? And I will show you some of the findings that we had in the pilot in the last two months. So this was a huge victory, and I will tell you why, because it took a lot of effort for us to get to the station. Like I said, it's been years for us to kind of lay the foundation, get the leadership, and shaping culture so people can understand why you truly need to invest on (indistinct) analytics. And so what I'm showing here is an example of how do we use basically, a tool to capture in video the qualitative findings that we had, plus the quantitative insights that we have. So in this case, our preliminary results based on our ambition for three main metrics, hours saved user experience and adoption. So for hours saved or a mission was to have 10 hours per week per employee save on average user experience, or ambition was 4.5. And adoption, 80%. In just two months, two months and a half of the pilot, we were able to achieve five hours per week per employee savings. Our user experience for 4.3 out of five and adoption of 60%. Really, really amazing work. But again, it takes a lot of collaboration for us to get to the stage from IT, legal, communications, obviously the operations teams and the users in HR safety and other areas that might be, basically stakeholders in this whole process. So just to summarize this kind of effort takes a lot of energy. You are a change agent. You need to have a courage to make the decision and understand that I feel that in this day and age, with all this disruption happening, we don't have a choice. We have to take the risk, right? And in this case, I feel a lot of satisfaction in how we were able to gain all these very source for this organization. And that gave me the confidence to know that the work has been done and we are now in a different stage for the organization. And so for me, it to say, thank you for everybody who has believed, obviously in our vision, everybody who has believe in the word that we were trying to do and to make the life of four workforce or customers or in community better. As you can tell, there is a lot of effort. There is a lot of collaboration that is needed to do something like this. In the end, I feel very satisfied. With the accomplishments of this transformation, and I just want to tell for you, if you are going right now in a moment that you feel that you have to swim upstream what would mentors, what would people in this industry that can help you out and guide you on this kind of a transformation is not easy to do is high effort, but is well worth it. And with that said, I hope you are well, and it's been a pleasure talking to you. Talk to you soon, take care. >> Thank you, Gustavo, that was amazing. All right, let's go to the panel. (air whooshing) >> Okay, now we're going to go into the panel and bring Cindi, Michelle, Tom, and Gustavo back and have an open discussion. And I think we can all agree how valuable it is to hear from practitioners. And I want to thank the panel for sharing their knowledge with the community. And one common challenge that I heard you all talk about was bringing your leadership and your teams along on the journey with you. We talk about this all the time, and it is critical to have support from the top. Why? Because it directs the middle and then it enables bottoms up innovation effects from the cultural transformation that you guys all talked about. It seems like another common theme we heard is that you all prioritize database decision-making in your organizations and you combine two of your most valuable assets to do that and create leverage, employees on the front lines. And of course the data. And as you rightly pointed out, Tom, the pandemic has accelerated the need for really leaning into this. The old saying, if it ain't broke don't fix it. Well COVID is broken everything. And it's great to hear from our experts, how to move forward. So let's get right into it. So Gustavo, let's start with you if I'm an aspiring change agent and let's say I'm a budding data leader. What do I need to start doing? What habits do I need to create for long lasting success? >> I think curiosity is very important. You need to be, like I say, in tune to what is happening, not only in your specific field, like I have a passion for analytics, I can do this for 50 years plus, but I think you need to understand wellbeing other areas across not only a specific business, as you know I come from, Sam's club Walmart, retail, I mean energy management technology. So you have to try to push yourself and basically go out of your comfort zone. I mean, if you are staying in your comfort zone and you want to use lean continuous improvement, that's just going to take you so far. What you have to do is, and that's what I try to do is I try to go into areas, businesses, and transformation that make me stretch and develop as a leader. That's what I'm looking to do so I can help transform the functions organizations and do the change management, change of mindset required for these kinds of efforts. >> Michelle, you're at the intersection of tech and sports and what a great combination, but they're both typically male oriented fields. I mean, we've talked a little bit about how that's changing, but two questions. Tell us how you found your voice and talk about why diversity matters so much more than ever now. >> No, I found my voice really as a young girl, and I think I had such amazing support from men in my life. And I think the support and sponsorship as well as sort of mentorship along the way, I've had amazing male mentors who have helped me understand that my voice is just as important as anyone else's. I mean, I have often heard, and I think it's been written about that a woman has to believe they'll 100% master topic before they'll talk about it where a man can feel much less mastery and go on and on. So I was that way as well. And I learned just by watching and being open, to have my voice. And honestly at times demand a seat at the table, which can be very uncomfortable. And you really do need those types of, support networks within an organization. And diversity of course is important and it has always been. But I think if anything, we're seeing in this country right now is that diversity among all types of categories is front and center. And we're realizing that we don't all think alike. We've always known this, but we're now talking about things that we never really talked about before. And we can't let this moment go unchecked and on, and not change how we operate. So having diverse voices within your company and in the field of tech and sports, I am often the first and only I'm was the first, CIO at the NFL, the first female senior executive. It was fun to be the first, but it's also, very challenging. And my responsibility is to just make sure that, I don't leave anyone behind and make sure that I leave it good for the next generation. >> Well, thank you for that. That is inspiring. And Cindi, you love data and the data's pretty clear that diversity is a good business, but I wonder if you can add your perspectives to this conversation? >> Yeah, so Michelle has a new fan here because she has found her voice. I'm still working on finding mine. And it's interesting because I was raised by my dad, a single dad. So he did teach me how to work in a predominantly male environment, but why I think diversity matters more now than ever before. And this is by gender, by race, by age, by just different ways of working in thinking is because as we automate things with AI, if we do not have diverse teams looking at the data and the models and how they're applied, we risk having bias at scale. So this is why I think I don't care what type of minority you are finding your voice, having a seat at the table and just believing in the impact of your work has never been more important. And as Michelle said more possible. >> Great perspectives, thank you. Tom I want to go to you. I mean, I feel like everybody in our businesses in some way, shape or form become a COVID expert, but what's been the impact of the pandemic on your organization's digital transformation plans? >> We've seen a massive growth actually in a digital business over the last, 12 months, really, even in celebration, right? Once COVID hit, we really saw that in the 200 countries and territories that we operate in today and service our customers, today, that there's been a huge need, right? To send money, to support family, to support, friends and support loved ones across the world. And as part of that we are very, honored to get to support those customers that we, across all the centers today. But as part of that acceleration we need to make sure that we had the right architecture and the right platforms to basically scale, right, to basically support and provide the right kind of security for our customers going forward. So as part of that, we did do some pivots and we did accelerate some of our plans on digital to help support that overall growth coming in and to support our customers going forward, because there were these times during this pandemic, right? This is the most important time. And we need to support those that we love and those that we care about and doing that it's one of those ways is actually by sending money to them, support them financially. And that's where, really our part of that our services come into play that we really support those families. So it was really a great opportunity for us to really support and really bring some of our products to this level and supporting our business going forward. >> Awesome, thank you. Now I want to come back to Gustavo, Tom I'd love for you to chime in too. Did you guys ever think like you were, you were pushing the envelope too much in doing things with data or the technology that was just maybe too bold, maybe you felt like at some point it was failing or you're pushing your people too hard. Can you share that experience and how you got through it? >> Yeah, the way I look at it is, again, whenever I go to an organization, I ask the question, hey, how fast you would like transform. And, based on the agreements from the leadership and the vision that we want to take place, I take decisions. And I collaborate in a specific way now, in the case of COVID, for example, right. It forces us to remove silos and collaborate in a faster way. So to me, it was an opportunity to actually integrate with other areas and drive decisions faster, but make no mistake about it. When you are doing a transformation, you are obviously trying to do things faster than sometimes people are comfortable doing, and you need to be okay with that. Sometimes you need to be okay with tension, or you need to be okay debating points or making repetitive business cases until people connect with the decision because you understand, and you are seeing that, "hey, the CEO is making a one two year, efficiency goal. "The only way for us to really do more with less "is for us to continue this path. "We cannot just stay with the status quo. "We need to find a way to accelerate the transformation." That's the way I see it. >> How about you Tom, we were talking earlier with Sudheesh and Cindi, about that bungee jumping moment. What could you share? >> Yeah, I think you hit upon it, right now, the pace of change with the slowest pace that you see for the rest of your career. So as part of that, right, that's what I tell my team is that you need to be, you need to feel comfortable being uncomfortable. I mean, that we have to be able to basically scale, right, expand and support that the ever-changing needs in the marketplace and industry our customers today, and that pace of change that's happening, right. And what customers are asking for and the competition in the marketplace, it's only going to accelerate. So as part of that, as you look at what, how you're operating today in your current business model, right. Things are only going to get faster. So you have to plan into a line into drive the agile transformation so that you can scale even faster in the future. So as part of that, that's what we're putting in place here, right, is how do we create that underlying framework and foundation that allows the organization to basically continue to scale and evolve into the future? >> Yeah, we're definitely out of our comfort zones, but we're getting comfortable with it. So, Cindi, last question, you've worked with hundreds of organizations, and I got to believe that, some of the advice you gave when you were at Gartner, which is pre COVID, maybe sometimes clients didn't always act on it. They're not on my watch for whatever variety of reasons, but it's being forced on them now. But knowing what you know now that we're all in this isolation economy, how would you say that advice has changed? Has it changed? What's your number one action and recommendation today? >> Yeah, well, first off, Tom just freaked me out. What do you mean? This is the slowest ever even six months ago I was saying the pace of change in data and analytics is frenetic. So, but I think you're right, Tom, the business and the technology together is forcing this change. Now, Dave, to answer your question, I would say the one bit of advice, maybe I was a little more, very aware of the power and politics and how to bring people along in a way that they are comfortable. And now I think it's, you know what you can't get comfortable. In fact, we know that the organizations that were already in the cloud have been able to respond and pivot faster. So if you really want to survive as Tom and Gustavo said, get used to being uncomfortable, the power and politics are going to happen. Break the rules, get used to that and be bold. Do not be afraid to tell somebody they're wrong and they're not moving fast enough. I do think you have to do that with empathy, as Michelle said, and Gustavo, I think that's one of the key words today besides the bungee jumping. So I want to know where's the dish going to go bungee jumping. >> Guys fantastic discussion, really. Thanks again to all the panelists and the guests. It was really a pleasure speaking with you today. Really virtually all of the leaders that I've spoken to in the Cube program. Recently, they tell me that the pandemic is accelerating so many things, whether it's new ways to work, we heard about new security models and obviously the need for cloud. I mean, all of these things are driving true enterprise wide digital transformation, not just, as I said before, lip service. Sometimes we minimize the importance and the challenge of building culture and in making this transformation possible. But when it's done, right, the right culture is going to deliver tremendous results. Yeah, what does that mean getting it right? Everybody's trying to get it right. My biggest takeaway today is it means making data part of the DNA of your organization. And that means making it accessible to the people in your organization that are empowered to make decisions, decisions that can drive new revenue, cut costs, speed access to critical care, whatever the mission is of your organization. Data can create insights and informed decisions that drive value. Okay. Let's bring back Sudheesh and wrap things up. Sudheesh, please bring us home. >> Thank you. Thank you, Dave. Thank you, the Cube team, and thank goes to all of our customers and partners who joined us and thanks to all of you for spending the time with us. I want to do three quick things and then close it off. The first thing is I want to summarize the key takeaways that I had from all four of our distinguished speakers. First, Michelle, I will simply put it. She said it really well. That is be brave and drive. Don't go for a drive along. That is such an important point. Oftentimes, you know that I think that you have to do to make the positive change that you want to see happen but you wait for someone else to do it, not just, why not you? Why don't you be the one making that change happen? That's the thing that I've picked up from Michelle's talk. Cindi talked about finding the importance of finding your voice. Taking that chair, whether it's available or not, and making sure that your ideas, your voices are heard, and if it requires some force, then apply that force. Make sure your ideas are heard. Gustavo talked about the importance of building consensus, not going at things all alone sometimes building the importance of building the quorum. And that is critical because if you want the changes to last, you want to make sure that the organization is fully behind it. Tom, instead of a single takeaway, what I was inspired by is the fact that a company that is 170 years old, 170 years old, 200 companies and 200 countries they're operating in. And they were able to make the change that is necessary through this difficult time. So in a matter of months, if they could do it, anyone could. The second thing I want to do is to leave you with a takeaway that is I would like you to go to topspot.com/nfl because our team has made an app for NFL on Snowflake. I think you will find this interesting now that you are inspired and excited because of Michelle's talk. And the last thing is please go to thoughtspot.com/beyond our global user conference is happening in this December. We would love to have you join us. It's again, virtual, you can join from anywhere. We are expecting anywhere from five to 10,000 people, and we would love to have you join and see what we've been up to since last year. We have a lot of amazing things in store for you, our customers, our partners, our collaborators, they will be coming and sharing. We'll be sharing things that we've have been working to release something that will come out next year. And also some of the crazy ideas our engineers have been cooking up. All of those things will be available for you at the Thought Spot Beyond. Thank you. Thank you so much.

>>from around the globe. It's the Cube with digital coverage of VM World 2020 brought to you by VM Ware and its ecosystem partners. Hello and welcome back to the cubes. Virtual coverage of VM World 2020 Virtual I'm John for your host of the Cube, our 11th year covering V emeralds. Not in person. It's virtual. I'm with my coast, Dave. A lot, of course. Ah, guest has been on every year since the cubes existed. Sanjay Putin, who is now the chief operating officer for VM Ware Sanjay, Great to see you. It's our 11th years. Virtual. We're not in person. Usually high five are going around. But hey, virtual fist pump, >>virtual pissed bump to you, John and Dave, always a pleasure to talk to you. I give you more than a virtual pistol. Here's a virtual hug. >>Well, so >>great. Back at great. >>Great to have you on. First of all, a lot more people attending the emerald this year because it's virtual again, it doesn't have the face to face. It is a community and technical events, so people do value that face to face. Um, but it is virtually a ton of content, great guests. You guys have a great program here, Very customer centric. Kind of. The theme is, you know, unpredictable future eyes is really what it's all about. We've talked about covert you've been on before. What's going on in your perspective? What's the theme of your main talks? >>Ah, yeah. Thank you, John. It's always a pleasure to talk to you folks. We we felt as we thought, about how we could make this content dynamic. We always want to make it fresh. You know, a virtual show of this kind and program of this kind. We all are becoming experts at many Ted talks or ESPN. Whatever your favorite program is 60 minutes on becoming digital producers of content. So it has to be crisp, and everybody I think was doing this has found ways by which you reduce the content. You know, Pat and I would have normally given 90 minute keynotes on day one and then 90 minutes again on day two. So 180 minutes worth of content were reduced that now into something that is that entire 180 minutes in something that is but 60 minutes. You you get a chance to use as you've seen from the keynote an incredible, incredible, you know, packed array of both announcements from Pat myself. So we really thought about how we could organize this in a way where the content was clear, crisp and compelling. Thekla's piece of it needed also be concise, but then supplemented with hundreds of sessions that were as often as possible, made it a goal that if you're gonna do a break out session that has to be incorporate or lead with the customer, so you'll see not just that we have some incredible sea level speakers from customers that have featured in in our pattern, Mikey notes like John Donahoe, CEO of Nike or Lorry beer C I, a global sea of JPMorgan Chase partner Baba, who is CEO of Zuma Jensen Wang, who is CEO of video. Incredible people. Then we also had some luminaries. We're gonna be talking in our vision track people like in the annuity. I mean, one of the most powerful women the world many years ranked by Fortune magazine, chairman, CEO Pepsi or Bryan Stevenson, the person who start in just mercy. If you watch that movie, he's a really key fighter for social justice and criminal. You know, reform and jails and the incarceration systems. And Malala made an appearance. Do I asked her personally, I got to know her and her dad's and she spoke two years ago. I asked her toe making appearance with us. So it's a really, really exciting until we get to do some creative stuff in terms of digital content this year. >>So on the product side and the momentum side, you have great decisions you guys have made in the past. We covered that with Pat Gelsinger, but the business performance has been very strong with VM. Where, uh, props to you guys, Where does this all tie together for in your mind? Because you have the transformation going on in a highly accelerated rate. You know, cov were not in person, but Cove in 19 has proven, uh, customers that they have to move faster. It's a highly accelerated world, a lot. Lots changing. Multi cloud has been on the radar. You got security. All the things you guys are doing, you got the AI announcements that have been pumping. Thean video thing was pretty solid. That project Monterey. What does the customer walk away from this year and and with VM where? What is the main theme? What what's their call to action? What's what do they need to be doing? >>I think there's sort of three things we would encourage customers to really think about. Number one is, as they think about everything in infrastructure, serves APS as they think about their APS. We want them to really push the frontier of how they modernize their athletic applications. And we think that whole initiative off how you modernized applications driven by containers. You know, 20 years ago when I was a developer coming out of college C, C plus, plus Java and then emerge, these companies have worked on J two ee frameworks. Web Logic, Be Aware logic and IBM Web Street. It made the development off. Whatever is e commerce applications of portals? Whatever was in the late nineties, early two thousands much, much easier. That entire world has gotten even easier and much more Micro service based now with containers. We've been talking about kubernetes for a while, but now we've become the leading enterprise, contain a platform making some incredible investments, but we want to not just broaden this platform. We simplified. It is You've heard everything in the end. What works in threes, right? It's sort of like almost t shirt sizing small, medium, large. So we now have tens Ooh, in the standard. The advanced the enterprise editions with lots of packaging behind that. That makes it a very broad and deep platform. We also have a basic version of it. So in some sense it's sort of like an extra small. In addition to the small medium large so tends to and everything around at modernization, I think would be message number one number two alongside modernization. You're also thinking about migration of your workloads and the breadth and depth of, um, er Cloud Foundation now of being able to really solve, not just use cases, you are traditionally done, but also new ai use cases. Was the reason Jensen and us kind of partner that, and I mean what a great company and video has become. You know, the king maker of these ai driven applications? Why not run those AI applications on the best infrastructure on the planet? Remember, that's a coming together of both of our platforms to help customers. You know automotive banking fraud detection is a number of AI use cases that now get our best and we want it. And the same thing then applies to Project Monterey, which takes the B c f e m A Cloud Foundation proposition to smart Knicks on Dell, HP Lenovo are embracing the in video Intel's and Pen Sandoz in that smart make architectural, however, that so that entire world of multi cloud being operative Phobia Macleod Foundation on Prem and all of its extended use cases like AI or Smart Knicks or Edge, but then also into the AWS Azure, Google Multi Cloud world. We obviously had a preferred relationship with Amazon that's going incredibly well, but you also saw some announcements last week from, uh, Microsoft Azure about azure BMR solutions at their conference ignite. So we feel very good about the migration opportunity alongside of modernization on the third priority, gentlemen would be security. It's obviously a topic that I most recently taken uninterested in my day job is CEO of the company running the front office customer facing revenue functions by night job by Joe Coffin has been driving. The security strategy for the company has been incredibly enlightening to talk, to see SOS and drive this intrinsic security or zero trust from the network to end point and workload and cloud security. And we made some exciting announcements there around bringing together MAWR capabilities with NSX and Z scaler and a problem black and workload security. And of course, Lassiter wouldn't cover all of this. But I would say if I was a attendee of the conference those the three things I want them to take away what BMR is doing in the future of APS what you're doing, the future of a multi cloud world and how we're making security relevant for distributed workforce. >>I know David >>so much to talk about here, Sanjay. So, uh, talk about modern APS? That's one of the five franchise platforms VM Ware has a history of going from, you know, Challenger toe dominant player. You saw that with end user computing, and there's many, many other examples, so you are clearly one of the top, you know. Let's call it five or six platforms out there. We know what those are, uh, and but critical to that modern APS. Focus is developers, and I think it's fair to say that that's not your wheelhouse today, but you're making moves there. You agree that that is, that is a critical part of modern APS, and you update us on what you're doing for that community to really take a leadership position there. >>Yeah, no, I think it's a very good point, David. We way seek to constantly say humble and hungry. There's never any assumption from us that VM Ware is completely earned anyplace off rightful leadership until we get thousands, tens of thousands. You know, we have a half a million customers running on our virtualization sets of products that have made us successful for 20 years 70 million virtual machines. But we have toe earn that right and containers, and I think there will be probably 10 times as many containers is their virtual machines. So if it took us 20 years to not just become the leader in in virtual machines but have 70 million virtual machines, I don't think it will be 20 years before there's a billion containers and we seek to be the leader in that platform. Now, why, Why VM Where and why do you think we can win in their long term. What are we doing with developers Number one? We do think there is a container capability independent of virtual machine. And that's what you know, this entire world of what hefty on pivotal brought to us on. You know, many of the hundreds of customers that are using what was formerly pivotal and FDR now what's called Tan Xue have I mean the the case. Studies of what those customers are doing are absolutely incredible. When I listen to them, you take Dick's sporting goods. I mean, they are building curbside, pick up a lot of the world. Now the pandemic is doing e commerce and curbside pick up people are going to the store, That's all based on Tan Xue. We've had companies within this sort of world of pandemic working on contact, tracing app. Some of the diagnostic tools built without they were the lab services and on the 10 zoo platform banks. Large banks are increasingly standardizing on a lot of their consumer facing or wealth management type of applications, anything that they're building rapidly on this container platform. So it's incredible the use cases I'm hearing public sector. The U. S. Air Force was talking about how they've done this. Many of them are not public about how they're modernizing dams, and I tend to learn the best from these vertical use case studies. I mean, I spend a significant part of my life is you know, it s a P and increasingly I want to help the company become a lot more vertical. Use case in banking, public sector, telco manufacturing, CPG retail top four or five where we're seeing a lot of recurrence of these. The Tan Xue portfolio actually brings us closest to almost that s a P type of dialogue because we're having an apse dialogue in the in the speak of an industry as opposed to bits and bytes Notice I haven't talked at all about kubernetes or containers. I'm talking about the business problem being solved in a retailer or a bank or public sector or whatever have you now from a developer audience, which was the second part of your question? Dave, you know, we talked about this, I think a year or two ago. We have five million developers today that we've been able to, you know, as bringing these acquisitions earn some audience with about two or three million from from the spring community and two or three million from the economic community. So think of those five million people who don't know us because of two acquisitions we don't. Obviously spring was inside Vienna where went out of pivotal and then came back. So we really have spent a lot of time with that community. A few weeks ago, we had spring one. You guys are aware of that? That conference record number of attendees okay, Registered, I think of all 40 or 50,000, which is, you know, much bigger than the physical event. And then a substantial number of them attended live physical. So we saw a great momentum out of spring one, and we're really going to take care of that, That that community base of developers as they care about Java Manami also doing really, really well. But then I think the rial audience it now has to come from us becoming part of the conversation. That coupon at AWS re invent at ignite not just the world, I mean via world is not gonna be the only place where infrastructure and developers come to. We're gonna have to be at other events which are very prominent and then have a developer marketplace. So it's gonna be a multiyear effort. We're okay with that. To grow that group of about five million developers that we today Kate or two on then I think there will be three or four other companies that also play very prominently to developers AWS, Microsoft and Google. And if we're one among those three or four companies and remembers including that list, we feel very good about our ability to be in a place where this is a shared community, takes a village to approach and an appeal to those developers. I think there will be one of those four companies that's doing this for many years to >>come. Santa, I got to get your take on. I love your reference to the Web days and how the development environment change and how the simplicity came along very relevant to how we're seeing this digital transformation. But I want to get your thoughts on how you guys were doing pre and now during and Post Cove it. You already had a complicated thing coming on. You had multi cloud. You guys were expanding your into end you had acquisitions, you mentioned a few of them. And then cove it hit. Okay, so now you have Everything is changing you got. He's got more complex city. You have more solutions, and then the customer psychology is change. You got to spectrums of customers, people trying to save their business because it's changed, their customer behavior has changed. And you have other customers that are doubling down because they have a tailwind from Cove it, whether it's a modern app, you know, coming like Zoom and others are doing well because of the environment. So you got your customers air in this in this in this, in this storm, you know, they're trying to save down, modernized or or or go faster. How are you guys changing? Because it's impacted how you sell. People are selling differently, how you implement and how you support customers, because you already had kind of the whole multi cloud going on with the modern APS. I get that, but Cove, it has changed things. How are you guys adopting and changing to meet the customer needs who are just trying to save their business on re factor or double down and continue >>John. Great question. I think I also talked about some of this in one of your previous digital events that you and I talked about. I mean, you go back to the last week of February 1st week of March, actually back up, even in January, my last trip on a plane. Ah, major trip outside this country was the World Economic Forum in Davos. And, you know, there were thousands of us packed into the small digits in Switzerland. I was sitting having dinner with Andy Jassy in a restaurant one night that day. Little did we know. A month later, everything would change on DWhite. We began to do in late February. Early March was first. Take care of employees. You always wanna have the pulse, check employees and be in touch with them. Because the health and safety of employees is much more important than the profits of, um, where you know. So we took care of that. Make sure that folks were taking care of older parents were in good place. We fortunately not lost anyone to death. Covert. We had some covert cases, but they've recovered on. This is an incredible pandemic that connects all of us in the human fabric. It has no separation off skin color or ethnicity or gender, a little bit of difference in people who are older, who might be more affected or prone to it. But we just have to, and it's taught me to be a significantly more empathetic. I began to do certain things that I didn't do before, but I felt was the right thing to do. For example, I've begun to do 25 30 minute calls with every one of my key countries. You know, as I know you, I run customer operations, all of the go to market field teams reporting to me on. I felt it was important for me to be showing up, not just in the big company meetings. We do that and big town halls where you know, some fractions. 30,000 people of VM ware attend, but, you know, go on, do a town hall for everybody in a virtual zoom session in Japan. But in their time zone. So 10 o'clock my time in the night, uh, then do one in China and Australia kind of almost travel around the world virtually, and it's not long calls 25 30 minutes, where 1st 10 or 15 minutes I'm sharing with them what I'm seeing across other countries, the world encouraging them to focus on a few priorities, which I'll talk about in a second and then listening to them for 10 15 minutes and be, uh and then the call on time or maybe even a little earlier, because every one of us is going to resume button going from call to call the call. We're tired of T. There's also mental, you know, fatigue that we've gotta worry about. Mental well, being long term. So that's one that I personally began to change. I began to also get energy because in the past, you know, I would travel to Europe or Asia. You know, 40 50%. My life has travel. It takes a day out of your life on either end, your jet lag. And then even when you get to a Tokyo or Beijing or to Bangalore or the London, getting between sites of these customers is like a 45 minute, sometimes in our commute. Now I'm able to do many of these 25 30 minute call, so I set myself a goal to talk to 1000 chief security officers. I know a lot of CEOs and CFOs from my times at S A P and VM ware, but I didn't know many security officers who often either work for a CEO or report directly to the legal counsel on accountable to the audit committee of the board. And I got a list of these 1,002,000 people we called email them. Man, I gotta tell you, people willing to talk to me just coming, you know, into this I'm about 500 into that. And it was role modeling to my teams that the top of the company is willing to spend as much time as possible. And I have probably gotten a lot more productive in customer conversations now than ever before. And then the final piece of your question, which is what do we tell the customer in terms about portfolio? So these were just more the practices that I was able to adapt during this time that have given me energy on dial, kind of get scared of two things from the portfolio perspective. I think we began to don't notice two things. One is Theo entire move of migration and modernization around the cloud. I describe that as you know, for example, moving to Amazon is a migration opportunity to azure modernization. Is that whole Tan Xue Eminem? Migration of modernization is highly relevant right now. In fact, taking more speed data center spending might be on hold on freeze as people kind of holding till depend, emmick or the GDP recovers. But migration of modernization is accelerating, so we wanna accelerate that part of our portfolio. One of the products we have a cloud on Amazon or Cloud Health or Tan Xue and maybe the other offerings for the other public dog. The second part about portfolio that we're seeing acceleration around is distributed workforce security work from home work from anywhere. And that's that combination off workspace, one for both endpoint management, virtual desktops, common black envelope loud and the announcements we've now made with Z scaler for, uh, distributed work for security or what the analysts called secure access. So message. That's beautiful because everyone working from home, even if they come back to the office, needs a very different model of security and were now becoming a leader in that area. of security. So these two parts of the portfolio you take the five franchise pillars and put them into these two buckets. We began to see momentum. And the final thing, I would say, Guys, just on a soft note. You know, I've had to just think about ways in which I balance work and family. It's just really easy. You know what, 67 months into this pandemic to burn out? Ah, now I've encouraged my team. We've got to think about this as a marathon, not a sprint. Do the personal things that you wanna do that will make your life better through this pandemic. That in practice is that you keep after it. I'll give you one example. I began biking with my kids and during the summer months were able to bike later. Even now in the fall, we're able to do that often, and I hope that's a practice I'm able to do much more often, even after the pandemic. So develop some activities with your family or with the people that you love the most that are seeing you a lot more and hopefully enjoying that time with them that you will keep even after this pandemic ends. >>So, Sanjay, I love that you're spending all this time with CSOs. I mean, I have a Well, maybe not not 1000 but dozens. And they're such smart people. They're really, you know, in the thick of things you mentioned, you know, your partnership with the scale ahead. Scott Stricklin on who is the C. C so of Wyndham? He was talking about the security club. But since the pandemic, there's really three waves. There's the cloud security, the identity, access management and endpoint security. And one of the things that CSOs will tell you is the lack of talent is their biggest challenge. And they're drowning in all these products. And so how should we think about your approach to security and potentially simplifying their lives? >>Yeah. You know, Dave, we talked about this, I think last year, maybe the year before, and what we were trying to do in security was really simplified because the security industry is like 5000 vendors, and it's like, you know, going to a doctor and she tells you to stay healthy. You gotta have 5000 tablets. You just cannot eat that many tablets you take you days, weeks, maybe a month to eat that many tablets. So ah, grand simplification has to happen where that health becomes part of your diet. You eat your proteins and vegetables, you drink your water, do your exercise. And the analogy and security is we cannot deploy dozens of agents and hundreds of alerts and many, many consoles. Uh, infrastructure players like us that have control points. We have 70 million virtual machines. We have 75 million virtual switches. We have, you know, tens of million's off workspace, one of carbon black endpoints that we manage and secure its incumbent enough to take security and making a lot more part of the infrastructure. Reduce the need for dozens and dozens of point tools. And with that comes a grand simplification of both the labor involved in learning all these tools. Andi, eventually also the cost of ownership off those particular tool. So that's one other thing we're seeking to do is increasingly be apart off that education off security professionals were both investing in ah, lot of off, you know, kind of threat protection research on many of our folks you know who are in a threat. Behavioral analytics, you know, kind of thread research. And people have come out of deep hacking experience with the government and others give back to the community and teaching classes. Um, in universities, there are a couple of non profits that are really investing in security, transfer education off CSOs and their teams were contributing to that from the standpoint off the ways in which we can give back both in time talent and also a treasure. So I think is we think about this. You're going to see us making this a long term play. We have a billion dollar security business today. There's not many companies that have, you know, a billion dollar plus of security is probably just two or three, and some of them have hit a wall in terms of their progress sport. We want to be one of the leaders in cybersecurity, and we think we need to do this both in building great product satisfying customers. But then also investing in the learning, the training enable remember, one of the things of B M worlds bright is thes hands on labs and all the training enable that happened at this event. So we will use both our platform. We in world in a variety of about the virtual environments to ensure that we get the best education of security to professional. >>So >>that's gonna be exciting, Because if you look at some of the evaluations of some of the pure plays I mean, you're a cloud security business growing a triple digits and, you know, you see some of these guys with, you know, $30 billion valuations, But I wanted to ask you about the market, E v m. Where used to be so simple Right now, you guys have expanded your tam dramatically. How are you thinking about, you know, the market opportunity? You've got your five franchise platforms. I know you're very disciplined about identifying markets, and then, you know, saying, Okay, now we're gonna go compete. But how do you look at the market and the market data? Give us the update there. >>Yeah, I think. Dave, listen, you know, I like davinci statement. You know, simplicity is the greatest form of sophistication, and I think you've touched on something that which is cos we get bigger. You know, I've had the great privilege of working for two great companies. s a P and B M where the bulk of my last 15 plus years And if something I've learned, you know, it's very easy. Both companies was to throw these TLS three letter acronyms, okay? And I use an acronym and describing the three letter acronyms like er or s ex. I mean, they're all acronyms and a new employee who comes to this company. You know, Carol Property, for example. We just hired her from Google. Is our CMO her first comments like, My goodness, there is a lot of off acronyms here. I've gotta you need a glossary? I had the same reaction when I joined B. M or seven years ago and had the same reaction when I joined the S A. P 15 years ago. Now, of course, two or three years into it, you learn everything and it becomes part of your speed. We have toe constantly. It's like an accordion like you expanded by making it mawr of luminous and deep. But as you do that it gets complex, you then have to simplify it. And that's the job of all of us leaders and I this year, just exemplifying that I don't have it perfect. One of the gifts I do have this communication being able to simplify things. I recorded a five minute video off our five franchise pill. It's just so that the casual person didn't know VM where it could understand on. Then, when I'm on your shore and when on with Jim Cramer and CNBC, I try to simplify, simplify, simplify, simplify because the more you can talk and analogies and pictures, the more the casual user. I mean, of course, and some other audiences. I'm talking to investors. Get it on. Then, Of course, as you go deeper, it should be like progressive layers or feeling of an onion. You can get deeper. It's not like the entire discussion with Sanjay Putin on my team is like, you know, empty suit. It's a superficial discussion. We could go deeper, but you don't have to begin the discussion in the bowels off that, and that's really what we don't do. And then the other part of your question was, how do we think about new markets? You know, we always start with Listen, you sort of core in contact our borough come sort of Jeffrey Moore, Andi in the Jeffrey more context. You think about things that you do really well and then ask yourself outside of that what the Jason sees that are closest to you, that your customers are asking you to advance into on that, either organically to partnerships or through acquisitions. I think John and I talked about in the previous dialogue about the framework of build partner and by, and we always think about it in that order. Where do we advance and any of the moves we've made six years ago, seven years ago and I joined the I felt VM are needed to make a move into mobile to really cement opposition in end user computing. And it took me some time to convince my peers and then the board that we should by Air One, which at that time was the biggest acquisition we've ever done. Okay. Similarly, I'm sure prior to me about Joe Tucci, Pat Nelson. We're thinking about nice here, and I'm moving to networking. Those were too big, inorganic moves. +78 years of Raghu was very involved in that. The decisions we moved to the make the move in the public cloud myself. Rgu pack very involved in the decision. Their toe partner with Amazon, the change and divest be cloud air and then invested in organic effort around what's become the Claudia. That's an organic effort that was an acquisition fast forward to last year. It took me a while to really Are you internally convinced people and then make the move off the second biggest acquisition we made in carbon black and endpoint security cement the security story that we're talking about? Rgu did a similar piece of good work around ad monetization to justify that pivotal needed to come back in. So but you could see all these pieces being adjacent to the core, right? And then you ask yourself, Is that context meaning we could leave it to a partner like you don't see us get into the hardware game we're partnering with. Obviously, the players like Dell and HP, Lenovo and the smart Knick players like Intel in video. In Pensando, you see that as part of the Project Monterey announcement. But the adjacent seas, for example, last year into app modernization up the stack and into security, which I'd say Maura's adjacent horizontal to us. We're now made a lot more logical. And as we then convince ourselves that we could do it, convince our board, make the move, We then have to go and tell our customers. Right? And this entire effort of talking to CSOs What am I doing is doing the same thing that I did to my board last year, simplified to 15 minutes and get thousands of them to understand it. Received feedback, improve it, invest further. And actually, some of the moves were now making this year around our partnership in distributed Workforce Security and Cloud Security and Z scaler. What we're announcing an XDR and Security Analytics. All of the big announcements of security of this conference came from what we heard last year between the last 12 months of my last year. Well, you know, keynote around security, and now, and I predict next year it'll be even further. That's how you advance the puck every year. >>Sanjay, I want to get your thoughts. So now we have a couple minutes left. But we did pull the audience and the community to get some questions for you, since it's virtually wanted to get some representation there. So I got three questions for you. First question, what comes after Cloud and number two is VM Ware security company. And three. What company had you wish you had acquired? >>Oh, my goodness. Okay, the third one eyes gonna be the turkey is one, I think. Listen, because I'm gonna give you my personal opinion, and some of it was probably predates me, so I could probably safely So do that. And maybe put the blame on Joe Tucci or somebody else is no longer here. But let me kind of give you the first two. What comes after cloud? I think clouds gonna be with us for a long time. First off this multi cloud world, you just look at the moment, um, that AWS and azure and the other clouds all have. It's incredible on I think this that multi cloud from phenomenon. But if there's an adapt ation of it, it's gonna be three forms of cloud. People are really only focus today in private public cloud. You have to remember the edge and Telco Cloud and this pendulum off the right balance of workloads between the data center called it a private cloud. The public cloud on one end and the telco edge on the other end. I think we're in a really good position for workloads to really swing between all three of those locations. Three other part that I think comes as a sequel to Cloud is cloud native. All of the capabilities a serverless functions but also containers that you know. Obviously the one could think of that a sister topics to cloud but the entire world of containers. The other seat, uh, then cloud a cloud native will also be topics, but these were all fairly connected. That's how I'd answer the first question. A security company? Absolutely. We you know, we aspire to be one of the leading companies in cyber security. I don't think they will be only one. We have to show this by the wealth on breath of our customers. The revenue momentum we have Gartner ranking us or the analysts ranking us in top rights of magic quadrants being viewed as an innovator simplifying the stack. But listen, we weren't even on the radar. We weren't speaking of the security conferences years ago. Now we are. We have a billion dollar security business, 20,000 plus customers, really strong presences and network endpoint and workload and Cloud Security. The three Coppola's a lot more coming in Security analytics, Cloud Security distributed workforce Security. So we're here to stay. And if anything, BMR persist through this, we're planning for multi your five or 10 year timeframe. And in that course I mean, the competition is smaller. Companies that don't have the breadth and depth of the n words are Andy muscle and are going market. We just have to keep building great products and serving customer on the third man. There's so many. But I mean, I think Listen, when I was looking back, I always wondered this is before I joined so I could say the summit speculatively on. Don't you know, make this This is BMR. Sorry. This is Sanjay one's opinion. Not VM. I gotta make very, very clear. Well, listen, I would have if I was at BMO in 2012 or 2013. I would love to about service now then service. It was a great company. I don't even know maybe the company's talk, but then talk about a very successful company at that time now. Maybe their priorities were different. I wasn't at the company at the time, but I can speculate if that had happened, that would have been an interesting Now I think that was during the time of Paul Maritz here and and so on. So for them, maybe there were other priorities the company need to get done. But at that time, of course, today s so it's not as big of a even slightly bigger market cap than us. So that's not happening. But that's a great example of a good company that I think would have at that time fit very well with VM Ware. And then there's probably we don't look back and regret we move forward. I mean, I think about the acquisitions we have made the big ones. Okay, Nice era air watch pop in black. Pivotal. The big moves we've made in terms of partnership. Amazon. What? We're announcing this This, you know, this week within video and Z scaler. So you never look back and regret. You always look for >>follow up on that To follow up on that from a developer, entrepreneurial or partner Perspective. Can you share where the white spaces for people to innovate around vm Where where where can people partner and play. Whether I'm an entrepreneur in a garage or venture back, funded or say a partner pivoting and or resetting with Govind, where's the white spaces with them? >>I think that, you know, there's gonna be a number off places where the Tan Xue platform develops, as it kind of makes it relevant to developers. I mean, there's, I think the first way we think about this is to make ourselves relevant toe all of that ecosystem around the C I. C. D type apply platform. They're really good partners of ours. They're like, get lab, You know, all of the ways in which open source communities, you know will play alongside that Hash E Corp. Jay frog there number of these companies that are partnering with us and we're excited about all of their relevancy to tend to, and it's our job to go and make that marketplace better and better. You're going to hear more about that coming up from us on. Then there's the set of data companies, you know, con fluent. You know, of course, you've seen a big I p o of a snowflake. All of those data companies, we'll need a very natural synergy. If you think about the old days of middleware, middleware is always sort of separate from the database. I think that's starting to kind of coalesce. And Data and analytics placed on top of the modern day middleware, which is containers I think it's gonna be now does VM or play physically is a data company. We don't know today we're gonna partner very heavily. But picking the right set of partners been fluent is a good example of one on. There's many of the next generation database companies that you're going to see us partner with that will become part of that marketplace influence. And I think, as you see us certainly produce out the VM Ware marketplace for developers. I think this is gonna be a game changing opportunity for us to really take those five million developers and work with the leading companies. You know, I use the example of get Lab is an example get help there. Others that appeal to developers tie them into our developer framework. The one thing you learn about developers, you can't have a mindset. With that, you all come to just us. It's a very mingled village off multiple ecosystems and Venn diagrams that are coalescing. If you try to take over the world, the developer community just basically shuns you. You have to have a very vibrant way in which you are mingling, which is why I described. It's like, Listen, we want our developers to come to our conferences and reinvent and ignite and get the best experience of all those provide tools that coincide with everybody. You have to take a holistic view of this on if you do that over many years, just like the security topic. This is a multi year pursuit for us to be relevant. Developers. We feel good about the future being bright. >>David got five minutes e. >>I thought you were gonna say Zoom, Sanjay, that was That was my wildcard. >>Well, listen, you know, I think it was more recently and very fast catapult Thio success, and I don't know that that's clearly in the complete, you know, sweet spot of the anywhere. I mean, you know, unified collaboration would have probably put us in much more competition with teams and, well, back someone you always have to think about what's in the in the bailiwick of what's closest to us, but zooms a great partner. Uh, I mean, obviously you love to acquire anybody that's hot, but Eric's doing really well. I mean, Erica, I'm sure he had many people try to come to buy him. I'm just so proud of him as a friend of all that he was named to Time magazine Top 100. But what he's done is phenomenon. I think he could build a company that's just his important, his Facebook. So, you know, I encourage him. Don't sell, keep building the company and you'll build a company that's going to be, you know, the enterprise version of Facebook. And I think that's a tremendous opportunity to do this better than anybody else is doing. And you know, I'm as an immigrant. He's, you know, China. Born now American, I'm Indian born, American, assim immigrants. We both have a similar story. I learned a lot from him. I learned a lot from him, from on speed on speed and how to move fast, he tells me he learns a thing to do for me on scale. We teach each other. It's a beautiful friendship. >>We'll make sure you put in a good word for the Kiwi. One more zoom integration >>for a final word or the zoom that is the future Facebook of the enterprise. Whatever, Sanjay, Thank >>you for connecting with us. Virtually. It is a digital foundation. It is an unpredictable world. Um, it's gonna change. It could be software to find the operating models or changing you guys. We're changing how you serve customers with new chief up commercial customer officer you have in place, which is a new hire. Congratulations. And you guys were flexing with the market and you got a tailwind. So congratulations, >>John and Dave. Always a pleasure. We couldn't do this without the partnership. Also with you. Congratulations of Successful Cube. And in its new digital format, Thank you for being with us With VM world here on. Do you know all that you're doing to get the story out? The guests that you have on the show, they look forward, including the nonviable people like, Hey, can I get on the Cuban like, Absolutely. Because they look at your platform is away. I'm telling this story. Thanks for all you're doing. I wish you health and safety. >>I'm gonna bring more community. And Dave is, you know, and Sanjay, and it's easier without the travel. Get more interviews, tell more stories and tell the most important stories. And thank you for telling your story and VM World story here of the emerald 2020. Sanjay Poon in the chief operating officer here on the Cube I'm John for a day Volonte. Thanks for watching Cube Virtual. Thanks for watching.

>>from around the globe. It's the Cube >>with digital coverage of VM World 2020 brought to you by VM Ware and its Ecosystem partners. Welcome back to the Cube. Virtual 2020. Coverage of VM Ware, VM World 2020 Virtual. I'm Sean for your host of the Cube. Join with Dave Alonso. We got a great guest. Carol Carpenter, Who's the chief marketing officer of VM Ware Cube Alumni move from Google Cloud to VM Ware. Carol, great to see you. And thanks for coming on the Cube for VM World 2020. Virtual coverage. Thank you. >>Yeah. Thank you both for having me here. Delighted to be here. >>So we've talked about many times before, but you're very in the cloud. Native space. You know the market pretty well. I gotta ask you what attracted you to come to the end? Where what was the What was the reason? Now you're heading up marketing for VM. Where what was the driving force? >>Well, a few things, you know, Number one. I've always had a passion for this space. I love the cloud. I was involved in an early stage company prior to Google Cloud that really had the promise of helping people get enterprises, get to the cloud faster. Um, and when I, you know, look around and I Look which kind of which companies are shaping the future of technology? VM ware, Certainly one of those companies. Second reason goes without saying the people in the culture, incredible leadership and empowerment all throughout Vienna, where and it's it's quite exceptional. And the third is I really think customers are on a really tough journey. Um, and having been at a hyper scaler, having worked at places where you know, cos air in a more traditional legacy environment, it makes it made me realize like this is a tough journey. And I think the, um where is uniquely positioned to help enterprises with what is a complex journey, and it's a multi cloud world. I'm sure you know that our customers know it. And how do you make all these disparate systems and tools work together to deliver the business results? I believe the M where is uniquely positioned Thio. >>It's interesting. VM Ware is going to a whole nother level. We've been commenting on our analysis segments around the business performance, obviously, and the moves they've made over the years. This is our 11th VM world. Keep started 10 years. 11 years ago. Um, we've been seeing the moves so great. Technology moves, product moves, business performance. The relationship with the clouds is all in place. But then Cove, it hits, okay? And then all that gets accelerate even further because you've got, you know, companies that I have to use this downtime to re modernized. And some people get a tailwind with modern application opportunities. So it's interesting time to be, you know, on this trajectory with VM ware and the clouds, what's your thoughts? Because you join right in the middle of all this and you're in and I of the storm. What's your view on this? Because this is a, uh, forcing function for companies to not only accelerate the transformation, but to move faster. >>Yeah, for sure. You know, it's been an incredibly challenging time, I think for everyone, and I hope everyone who's watching and listening is safe. Um, you know, we talk about decades of progress being made in two weeks, and I guess that's the silver lining. If there is one, which is this ultimate work? Remote work from home that we've enabled and the work anywhere. It's been completely liberating in so many ways. Um, you know, it's an area where I look at, there's how we lead our teams and how do we maintain relationships with customers, which obviously requires a different type of interaction, of different type of outreach? And and then there's what are the solutions at scale And you know, im I pleased to say, like there were absolute big lifts in certain areas of our business, particularly around, you know, remote work and our digital workspace solutions, you know, really enabling companies to get thousands of workers up and running quickly. That, combined with our security solutions and our SD wan solution to really enable all of these remote homes to become thousands of remote offices. So there's all of that, which is incredibly positive. And at the same time, you know, I have to tell you, I joke, but I still haven't figured out where the bathroom is, you know, free three plus months. So that way I miss the human connection. I miss being able to just see people and give people a hug now and then when you want Thio >>e mean, VM. Where? Carol, It's amazing. Company. You mentioned the culture before. It really started as a workstation virtualization company, right? And then so many challenges, you know, and use a computing. You guys do an acquisition bringing Sanjay Poon in all of a sudden, you're the leader there cloud, you know, fumbled a little bit, but all of a sudden, the cloud strategy kicking on all cylinders, we see that, you know, growing like crazy. The networking piece, the storage piece you mentioned security, which is a amazing opportunity. Containers. They're gonna kill kill VM ware. Well, I guess. Guess what? We're embracing them. It seems like culturally vm where it just has this attitude of if there's a wave, you know, we're gonna ride it, we're gonna embrace it and figure out how to deliver value to our customers. What's your thinking on that? >>Yeah. I mean, it's such a VM ware, such an innovative company. And that is another reason that attracted me on disability to look at what customers need. Like, this is an incredibly were an incredibly customer centric company, listening to customers, understanding their needs and providing a bridge to where they need to go while also providing them the resiliency and needs they have today. That is what thrills me. And I think we have such an incredible opportunity to continue to drive that future innovation while also being that bridge. Um, I have to tell you, you know, I've known VM Ware for a long time, and what appealed to me is this broader portfolio and this opportunity to actually tell a broader business value story to be able to actually tell that story about not just digital transformation but business transformation. So that's what that's. That's the journey we're on and it's it's happening. It's really I mean, you look at all the customers, whether it's, you know, JPMorgan Chase to, um, a nonprofit like feeding America to, you know, large companies like Nike. It's really incredible the impact and value we could bring. And I feel that my job and the marketing team's job is, I tell them like they're all these diamonds in the backyard. It's just some of them are a little dirty, and some are they're just not fully revealed, and it's our job, todo and you know, dust them off and tell the story to help customers and prospects understand the value we could bring. >>That's how should we be thinking? How should we be thinking about that? That business value, transformation, business transformation? You you? Certainly when you think of an application's company that there's easily connect the dots. But how should we be thinking about VM Ware in that value chain? You an enabler for that transformation? Can you provide some color there? >>Yeah, let me give you some specific examples like Look at, um, so the addition of Tan Xue to the portfolio is what enables us to have these discussions that, let's face it, the only reason people need or want infrastructure is because they want to deploy an application. They want to write an application. They want to move an application. And Tan Xue, which is our container based, kubernetes based orchestration solution and lots more to it. That's what how it is in simple terms that gives us the ability to work with companies, lines of business as well as developers around riel. Business transformation. So two quick examples one. I can't say the name quite yet, but I think very large pharmaceutical company who wants to launch and have a mobile app to help patients. People who are taking Cove in 19 tests get the results, understand the results, ask questions about the results and have one place to go that's really powerful. And to be able to develop an app that is scale built for scale, built for enterprise, built to be resilient when patients are trying to get information. Um, in four weeks, I mean, that's pretty. That's quite incredible. Another example is, you know, very large e commerce company that, you know, you mentioned Cove it and some of the challenges we know retail has certainly been kind of, ah, tale of two cities, right? Some companies with lots of lift and others with real struggle in the physical world. But anyway, large retailer who had to within weeks flip to curbside pickup, Um, being able to look customers being able to look at inventory on demand, those kinds of capabilities required ah, wholesale rewrite of many of their e commerce applications. Again, that's a place where we can go in and we can talk to them about that. And by the way, as you know, the challenge is it's one thing to write and deploy an app, and then it's another to actually run it at scale, which then requires the networking, scalability and flexibility it requires. The virtual, um, storage. It requires all the other elements that we bring to the table. So I think that is the That's kind of the landing spot. But it's not the ending spot when we talk to customers. >>Carol talk about the challenge of VM World 2020 this year. It's not in person. It's one of them. It's an industry event. It's been one every year. It's a place where there's deep community, deep technical demos, beep deep discussions. Ah, lot of face to face hallway conversations. That's not happening. It's virtual. Um, you came right in the middle of all this. You guys pulled it together. Um, got a You got keynote sessions and thanks for including the Cube. We really appreciate that as well. But you have all this content. How did you handle that? And how's that going and and share some, uh, color on what it took to pull it off. And what's your expectation? >>Yeah, So you know. Yes. VM world is considered the gold standard when it comes to industry events. I mean, from the outside in this is the canonical I t event. And so I feel, really, you know, honored that this franchise is now in my hands and have an incredible team of people who obviously have been working on it for prior to my joining. So I just feel honored to be part of it. Um, this is going to be the world's largest VM world. And on the one hand, miss the energy in the room, Miss seeing people, everything you talked about, the serendipitous interactions that the food line or coffee bar. Um, but going virtual has so many benefits. Some of the things we were talking about earlier, the ability to reach many, many more people. This event is going to be 5 to 6 times larger than our physical event. And that's not even including the VM world that we're running in Asia in China. And the other thing that makes me super happy is that over 65% of our registrants and of the attendees here are actually first time VM world attendees. So this ability to broad in our tent and make it easier I mean, let's face it. You know, being able to fly, whether it was Vegas or San Francisco is originally planned. Stay in these expensive hotels and take that time it was. It's a big ask. So by going virtual, we actually have expanded our audience tremendously. Three other thing I am really excited about is we have 800 plus content sessions. We are following the sun. We have live Q and A after every session. We have really the best mobile app for any events, so I encourage you to take a look at that which does enable the chat interaction as well as you know, path funding through the many channels we have of contact. Its's Look, we're learning, and I'd love to follow up with you later to hear what you've learned because I know you've also been doing a lot. Virtually, I think the world is going to move to something that's more hybrid, some combination of virtual and small group, you know, in person, some local events of some sort. Um, but this one I'm super excited about, we we really have seen high engagement, and I just think, Well, I look forward to hearing everyone's feedback. E >>I think one of the things that we've been hearing is is that I can now go to the M world. I can participate now virtually it's it's kind of I would call First Generation writes me the Web early days. But you're right. I think it's gonna open up the eyes to a bigger community, access a bigger pool of data, bigger pool of interactions and community. And when they do come back face to face, people be ableto fly and meet people they met online. So we think this is gonna be a real trend where it's like the r A. Y of this virtual space is tremendous. You could do demos. You conserve yourselves, you could consume a demo, but then meet people face to face. >>And by the way, we have, you know, a tremendous number of fun activities. Hopefully you've taken part in some of them. Everything from puppy therapy Thio magic shows to yoga Thio Um you know John Legend legend performing. So I agree. I think the level personalization and ability to self serve is going to be out of this world. So yeah, it's just the best. >>Your event, just some key things that we can share with the audience. Cloud City has over 60 solution Demos Uh, there's a VM World challenge That's fun. There's also an ex Ask the expert section where you got Joe Beta and Ragu and other luminaries there to ask the questions of the That's the top talent in the company all online. And of course, you get the CTO Innovation keynote with Greg Lavender. So you know you're bringing the big guns out on display on it. Z free access. Um, it's awesome. Congratulations. We're looking forward Toa see, with the day that looks like after, So what's the story line for you? If you had to summarize out the VM World 2020 this year, what's coming out from the data? What are you hearing? Is the key themes, Actually, the tagline. You know, uh, you know, possible together, Digital foundation, unpredictable world. But what are you hearing, uh, in the virtual hallways? >>Well, a few things, but I'd say the top take away is that VM where has spread its wings, has embraced mawr of the different ICTY audiences and is driving business transformation for companies in new and pretty unique ways. What and then obviously like slew of announcements, new partnerships, new capabilities, everything around multi cloud we have. As you know, every single cloud provider is a partner on the security front, intrinsic security built in throughout the entire stack. The the other part that I I think it's super exciting are these partnerships were announcing everything from what we're doing with and video to make a i mawr accessible for enterprises in production to what we're doing around sassy, secure access Service Edge. Being able to provide a holistic, secure, distributed environment so that every worker, no matter where they are, every endpoint, every remote office could be fully secured. >>You know, in VM where is the gold standard of Of of the Ecosystem and VM world? Of course, they're all in the showcase and it was hard fought. I mean, it took a long time to get there, and you know, the challenges of building that. And now you mentioned in video. You see all these new tail winds coming in and and then I've seen companies launch at VM World. And so you know that ecosystem is, as I say, it is very difficult to build. But then becomes a huge asset because this just gives you so much leverage. A zone organization, your company's your partners, your customers. >>Thank you, Dave. Yeah, we're super excited. And I should say that like the partner and the ecosystem here is unparalleled. And our challenge is how do we provide? And you know, this Like, how do we provide the strategic vision and that practitioner level content? So we're gonna you know, that's what we're committed. Teoh is making sure that our practitioners get everything they need in every every area of expertise, as well as making sure we're conveying our business story. >>Carol, thanks so much for coming on. Really appreciate the inside one final question for you as we get through this crisis soon hybrid comes back for events, certainly. But as the CMO the next gen story, you now have a chief customer officer. We interviewed him. Well, the n words go to the next level. What's your goals? What are you trying to accomplish? And you've got a lot of things going on. Certainly a big story to tell. A lot of ingredients. Toe kinda cook a great, great story here. What's your goals? See him over the next year. >>You know, my goal is to help drive the business transformation and you've heard it from Submit. You've heard it from others at this point. But really, you know, the company is going We're going through a dramatic transformation from being, you know, ah, license on Prem Company to being a multi cloud, modern SAS company. So my goal is to support that. And that means modernizing the way we do marketing which, you know, you say, Well, what does that mean? It means customer focus, customer lifecycle marketing. It means agility, being able to actually use data to drive how we interact with customers and users so that they have those great experiences and they continue to use the product and Dr Adoption and Growth. And the other part of it is, um, b two b marketing, as you may or may not have noticed, is incredibly boring and dull. And I know I'm guilty of this, too. We get caught up in a lot of but jargon and the language, and I am on a mission that we're going to do great B two B marketing that helps customers understand what we do and where we express the value simply clearly and in in differentiated way. >>That's awesome. >>Yeah, Why should the consumer guys have all the fun? Right? >>Right, Well, and that's part of being, by the way a SAS or subscription company is. Everything we do needs to be consumer simple at scale and with the secure ability and the reliability of what an enterprise means. >>Well, I got to tell you that the irony of all this virtual ization of the world with Covic virtual events e one of the big surprise is we're gonna be looking back at is how much it's opened up Thio Mawr audiences and new ways of modernizing and taking advantage of that. Certainly with content in community, you guys are well positioned. Congratulations for a great event. Thank you for coming on and sharing your insights, and we'll keep in touch. We'll try. We'll try to make it exciting, Mister Cube. Thank you. Appreciate >>it. Thank you. Awesome. Thank you. Thank you, John. >>I'm Jennifer David. Lot Cube. Coverage of the M 2020 Virtual. This is the Virtual Cube. Have now virtual sets everywhere. All around the world. It's global. Thanks for watching

>> Live from San Francisco, California, it's the theCUBE, covering the IBM Chief Data Officer Summit, brought to you by IBM. >> Welcome back to San Francisco everybody. You're watching theCUBE, the leader in live tech coverage. We go out to the events, we extract the signal from the noise and we're here at the IBM Chief Data Officer Summit, 10th anniversary. Seth Dobrin is here, he's the Vice President and Chief Data Officer of the IBM Analytics Group. Seth, always a pleasure to have you on. Good to see you again. >> Yeah, thanks for having me back Dave. >> You're very welcome. So I love these events you get a chance to interact with chief data officers, guys like yourself. We've been talking a lot today about IBM's internal transformation, how IBM itself is operationalizing AI and maybe we can talk about that, but I'm most interested in how you're pointing that at customers. What have you learned from your internal experiences and what are you bringing to customers? >> Yeah, so, you know, I was hired at IBM to lead part of our internal transformation, so I spent a lot of time doing that. >> Right. >> I've also, you know, when I came over to IBM I had just left Monsanto where I led part of their transformation. So I spent the better part of the first year or so at IBM not only focusing on our internal efforts, but helping our clients transform. And out of that I found that many of our clients needed help and guidance on how to do this. And so I started a team we call, The Data Science an AI Elite Team, and really what we do is we sit down with clients, we share not only our experience, but the methodology that we use internally at IBM so leveraging things like design thinking, DevOps, Agile, and how you implement that in the context of data science and AI. >> I've got a question, so Monsanto, obviously completely different business than IBM-- >> Yeah. >> But when we talk about digital transformation and then talk about the difference between a business and a digital business, it comes down to the data. And you've seen a lot of examples where you see companies traversing industries which never used to happen before. You know, Apple getting into music, there are many, many examples, and the theory is, well, it's 'cause it's data. So when you think about your experiences of a completely different industry bringing now the expertise to IBM, were there similarities that you're able to draw upon, or was it a completely different experience? >> No, I think there's tons of similarities which is, which is part of why I was excited about this and I think IBM was excited to have me. >> Because the chances for success were quite high in your mind? >> Yeah, yeah, because the chance for success were quite high, and also, you know, if you think about it there's on the, how you implement, how you execute, the differences are really cultural more than they're anything to do with the business, right? So it's, the whole role of a Chief Data Officer, or Chief Digital Officer, or a Chief Analytics Officer, is to drive fundamental change in the business, right? So it's how do you manage that cultural change, how do you build bridges, how do you make people, how do you make people a little uncomfortable, but at the same time get them excited about how to leverage things like data, and analytics, and AI, to change how they do business. And really this concept of a digital transformation is about moving away from traditional products and services, more towards outcome-based services and not selling things, but selling, as a Service, right? And it's the same whether it's IBM, you know, moving away from fully transactional to Cloud and subscription-based offerings. Or it's a bank reimagining how they interact with their customers, or it's oil and gas company, or it's a company like Monsanto really thinking about how do we provide outcomes. >> But how do you make sure that every, as a Service, is not a snowflake and it can scale so that you can actually, you know, make it a business? >> So underneath the, as a Service, is a few things. One is, data, one is, machine learning and AI, the other is really understanding your customer, right, because truly digital companies do everything through the eyes of their customer and so every company has many, many versions of their customer until they go through an exercise of creating a single version, right, a customer or a Client 360, if you will, and we went through that exercise at IBM. And those are all very consistent things, right? They're all pieces that kind of happen the same way in every company regardless of the industry and then you get into understanding what the desires of your customer are to do business with you differently. >> So you were talking before about the Chief Digital Officer, a Chief Data Officer, Chief Analytics Officer, as a change agent making people feel a little bit uncomfortable, explore that a little bit what's that, asking them questions that intuitively they, they know they need to have the answer to, but they don't through data? What did you mean by that? >> Yeah so here's the conversations that usually happen, right? You go and you talk to you peers in the organization and you start having conversations with them about what decisions are they trying to make, right? And you're the Chief Data Officer, you're responsible for that, and inevitably the conversation goes something like this, and I'm going to paraphrase. Give me the data I need to support my preconceived notions. >> (laughing) Yeah. >> Right? >> Right. >> And that's what they want to (voice covers voice). >> Here's the answer give me the data that-- >> That's right. So I want a Dashboard that helps me support this. And the uncomfortableness comes in a couple of things in that. It's getting them to let go of that and allow the data to provide some inkling of things that they didn't know were going on, that's one piece. The other is, then you start leveraging machine learning, or AI, to actually help start driving some decisions, so limiting the scope from infinity down to two or three things and surfacing those two or three things and telling people in your business your choices are one of these three things, right? That starts to make people feel uncomfortable and really is a challenge for that cultural change getting people used to trusting the machine, or in some instances even, trusting the machine to make the decision for you, or part of the decision for you. >> That's got to be one of the biggest cultural challenges because you've got somebody who's, let's say they run a big business, it's a profitable business, it's the engine of cashflow at the company, and you're saying, well, that's not what the data says. And you're, say okay, here's a future path-- >> Yeah. >> For success, but it's going to be disruptive, there's going to be a change and I can see people not wanting to go there. >> Yeah, and if you look at, to the point about, even businesses that are making the most money, or parts of a business that are making the most money, if you look at what the business journals say you start leveraging data and AI, you get double-digit increases in your productivity, in your, you know, in differentiation from your competitors. That happens inside of businesses too. So the conversation even with the most profitable parts of the business, or highly, contributing the most revenue is really what we could do better, right? You could get better margins on this revenue you're driving, you could, you know, that's the whole point is to get better leveraging data and AI to increase your margins, increase your revenue, all through data and AI. And then things like moving to, as a Service, from single point to transaction, that's a whole different business model and that leads from once every two or three or five years, getting revenue, to you get revenue every month, right? That's highly profitable for companies because you don't have to go in and send your sales force in every time to sell something, they buy something once, and they continue to pay as long as you keep 'em happy. >> But I can see that scaring people because if the incentives don't shift to go from a, you know, pay all up front, right, there's so many parts of the organization that have to align with that in order for that culture to actually occur. So can you give some examples of how you've, I mean obviously you ran through that at IBM, you saw-- >> Yeah. >> I'm sure a lot of that, got a lot of learnings and then took that to clients. Maybe some examples of client successes that you've had, or even not so successes that you've learned from. >> Yeah, so in terms of client success, I think many of our clients are just beginning this journey, certainly the ones I work with are beginning their journey so it's hard for me to say, client X has successfully done this. But I can certainly talk about how we've gone in, and some of the use cases we've done-- >> Great. >> With certain clients to think about how they transformed their business. So maybe the biggest bang for the buck one is in the oil and gas industry. So ExxonMobile was on stage with me at, Think, talking about-- >> Great. >> Some of the work that we've done with them in their upstream business, right? So every time they drop a well it costs them not thousands of dollars, but hundreds of millions of dollars. And in the oil and gas industry you're talking massive data, right, tens or hundreds of petabytes of data that constantly changes. And no one in that industry really had a data platform that could handle this dynamically. And it takes them months to get, to even start to be able to make a decision. So they really want us to help them figure out, well, how do we build a data platform on this massive scale that enables us to be able to make decisions more rapidly? And so the aim was really to cut this down from 90 days to less than a month. And through leveraging some of our tools, as well as some open-source technology, and teaching them new ways of working, we were able to lay down this foundation. Now this is before, we haven't even started thinking about helping them with AI, oil and gas industry has been doing this type of thing for decades, but they really were struggling with this platform. So that's a big success where, at least for the pilot, which was a small subset of their fields, we were able to help them reduce that timeframe by a lot to be able to start making a decision. >> So an example of a decision might be where to drill next? >> That's exactly the decision they're trying to make. >> Because for years, in that industry, it was boop, oh, no oil, boop, oh, no oil. >> Yeah, well. >> And they got more sophisticated, they started to use data, but I think what you're saying is, the time it took for that analysis was quite long. >> So the time it took to even overlay things like seismic data, topography data, what's happened in wells, and core as they've drilled around that, was really protracted just to pull the data together, right? And then once they got the data together there were some really, really smart people looking at it going, well, my experience says here, and it was driven by the data, but it was not driven by an algorithm. >> A little bit of art. >> True, a lot of art, right, and it still is. So now they want some AI, or some machine learning, to help guide those geophysicists to help determine where, based on the data, they should be dropping wells. And these are hundred million and billion dollar decisions they're making so it's really about how do we help them. >> And that's just one example, I mean-- >> Yeah. >> Every industry has it's own use cases, or-- >> Yeah, and so that's on the front end, right, about the data foundation, and then if you go to a company that was really advanced in leveraging analytics, or machine learning, JPMorgan Chase, in their, they have a division, and also they were on stage with me at, Think, that they had, basically everything is driven by a model, so they give traders a series of models and they make decisions. And now they need to monitor those models, those hundreds of models they have for misuse of those models, right? And so they needed to build a series of models to manage, to monitor their models. >> Right. >> And this was a tremendous deep-learning use case and they had just bought a power AI box from us so they wanted to start leveraging GPUs. And we really helped them figure out how do you navigate and what's the difference between building a model leveraging GPUs, compared to CPUs? How do you use it to accelerate the output, and again, this was really a cost-avoidance play because if people misuse these models they can get in a lot of trouble. But they also need to make these decisions very quickly because a trader goes to make a trade they need to make a decision, was this used properly or not before that trade is kicked off and milliseconds make a difference in the stock market so they needed a model. And one of the things about, you know, when you start leveraging GPUs and deep learning is sometimes you need these GPUs to do training and sometimes you need 'em to do training and scoring. And this was a case where you need to also build a pipeline that can leverage the GPUs for scoring as well which is actually quite complicated and not as straight forward as you might think. In near real time, in real time. >> Pretty close to real time. >> You can't get much more real time then those things, potentially to stop a trade before it occurs to protect the firm. >> Yeah. >> Right, or RELug it. >> Yeah, and don't quote, I think this is right, I think they actually don't do trades until it's confirmed and so-- >> Right. >> Or that's the desire as to not (voice covers voice). >> Well, and then now you're in a competitive situation where, you know. >> Yeah, I mean people put these trading floors as close to the stock exchange as they can-- >> Physically. >> Physically to (voice covers voice)-- >> To the speed of light right? >> Right, so every millisecond counts. >> Yeah, read Flash Boys-- >> Right, yeah. >> So, what's the biggest challenge you're finding, both at IBM and in your clients, in terms of operationalizing AI. Is it technology? Is it culture? Is it process? Is it-- >> Yeah, so culture is always hard, but I think as we start getting to really think about integrating AI and data into our operations, right? As you look at what software development did with this whole concept of DevOps, right, and really rapidly iterating, but getting things into a production-ready pipeline, looking at continuous integration, continuous development, what does that mean for data and AI? And these concept of DataOps and AIOps, right? And I think DataOps is very similar to DevOps in that things don't change that rapidly, right? You build your data pipeline, you build your data assets, you integrate them. They may change on the weeks, or months timeframe, but they're not changing on the hours, or days timeframe. As you get into some of these AI models some of them need to be retrained within a day, right, because the data changes, they fall out of parameters, or the parameters are very narrow and you need to keep 'em in there, what does that mean? How do you integrate this for your, into your CI/CD pipeline? How do you know when you need to do regression testing on the whole thing again? Does your data science and AI pipeline even allow for you to integrate into your current CI/CD pipeline? So this is actually an IBM-wide effort that my team is leading to start thinking about, how do we incorporate what we're doing into people's CI/CD pipeline so we can enable AIOps, if you will, or MLOps, and really, really IBM is the only company that's positioned to do that for so many reasons. One is, we're the only one with an end-to-end toolchain. So we do everything from data, feature development, feature engineering, generating models, whether selecting models, whether it's auto AI, or hand coding or visual modeling into things like trust and transparency. And so we're the only one with that entire toolchain. Secondly, we've got IBM research, we've got decades of industry experience, we've got our IBM Services Organization, all of us have been tackling with this with large enterprises so we're uniquely positioned to really be able to tackle this in a very enterprised-grade manner. >> Well, and the leverage that you can get within IBM and for your customers. >> And leveraging our clients, right? >> It's off the charts. >> We have six clients that are our most advanced clients that are working with us on this so it's not just us in a box, it's us with our clients working on this. >> So what are you hoping to have happen today? We're just about to get started with the keynotes. >> Yeah. >> We're going to take a break and then come back after the keynotes and we've got some great guests, but what are you hoping to get out of today? >> Yeah, so I've been with IBM for 2 1/2 years and I, and this is my eighth CEO Summit, so I've been to many more of these than I've been at IBM. And I went to these religiously before I joined IBM really for two reasons. One, there's no sales pitch, right, it's not a trade show. The second is it's the only place where I get the opportunity to listen to my peers and really have open and candid conversations about the challenges they're facing and how they're addressing them and really giving me insights into what other industries are doing and being able to benchmark me and my organization against the leading edge of what's going on in this space. >> I love it and that's why I love coming to these events. It's practitioners talking to practitioners. Seth Dobrin thanks so much for coming to theCUBE. >> Yeah, thanks always, Dave. >> Always a pleasure. All right, keep it right there everybody we'll be right back right after this short break. You're watching, theCUBE, live from San Francisco. Be right back.

>> Live from San Francisco. It's theCUBE covering IBM Think 2019 brought to you by IBM. >> Welcome back everyone, this is the CUBE's live coverage in San Francisco at Moscone Center for IBM Think 2019. I'm John Furrier with Dave. Volante Dave it's been in AI, it's been cloud, it's been in data changing the game. We've got two great guests here Murali Nemani, CMO of ScienceLogic, your CEO has been on the CUBE before and Joe Damassa who is the VP of strategy and offerings for hybrid cloud service at IBM. Thanks for joining us. >> Welcome. >> Appreciate it. >> Thank you guys. >> Welcome to CUBE. So day four of four days coverage, yes, you can see the messaging settling the feedback settling, AI clearly front and center, role of data in that and then cloud scale across multiple capabilities. Obviously on premise multi cloud is existing already. Software's changing all this. >> Right. >> And so AI impacting operations is key. So how do you guys work together? What's the relationships in ScienceLogic and IBM? Could you just take a minute to explain that? >> I think I mean, clearly, as you talked about the hybrid nature of what we're dealing with, with the complexity of it, it's all going to be about the data. You know, software is great, but it's about software that collects the data, analyzes the data, and gives you the insights so you can actually automate and create value for our clients. So it's really this marriage, it's a technology but it's a technology that allows us to get access to the data so we can make change, it's all about the data. >> And so a lot of what IBM has been doing is building the analytics engines and Watson it's for them. Our partnership has been really building the data and the data lake and the real time aspects of collecting and preparing that data so that you can really get interesting outcomes out of it. So when you think about predictive models, when you think about the the way that data can be applied to doing things like anomaly detection that ultimately accelerate and automate operations. That's where the relationship really starts taking hold. >> So you guys are specialized in AIops and IT apparatus as that transforms with scale and data which you need machine running, you need a kind of gave it automation. >> Yes. >> And which is the devops use of operations is don't go down, right, up and running, high availability. >> Yeah. >> So on the cloud services side, talk about where the rubber is meeting the road from a customer standpoint, because the cultural shift from IT Service Management, IT operations has been this manual, some software here and there, but it's been a process. Older processes change a little bit, but this is a new game. Talk about how you guys are engaging the customers. >> Well, a part of it I mean, it's interesting when you step back and you stop breathing, you're on exhaust in terms of pushing what you're trying to sell and you listen to your customers what we're hearing is that they all understand the destination. They understand they're moving to the cloud, they understand the value that's going to bring, they're having a hard time getting started. It's how do I start the journey ? I've got all of this estate and traditional IT operations capabilities it's kind of move. How do I modernize it? How do I make it so it's portable across different environments. And so when you step back, you know, we basically said, hey, you need the portability of the platform. So what we're doing with Red Hat, what we're doing with IBM, cloud private, it creates that portable containerizing ability to take our existing workloads and start moving them, right. And then the other thing that the clients need are the services. Who's going to help me advise me on what workloads should move, which one shouldn't, most of the staff fails because you move the wrong things. How do you manage that? How do you build it? And then when you're done, and you've got this hybrid complex environment, how do we actually get insights to it and the data I need to operationalize it? How do I do IT apps, when I don't own everything within the four walls of my data set. >> Now, are you guys going to market together? You guys sell each other products, the relationship with ScienceLogic and IBM is it a partnership, is it a joint development? Can you explain a little bit more on how you guys work together? >> Well, we're one of the largest sort of services provider in the industry. So as we bring, our products, our technologies and our capabilities to market, we bring ScienceLogic into those deals, we use ScienceLogic in our services so that we can actually deliver the value to our clients. So it is sort of a co development, co joint partnership plus also our goal to market. >> So you use that as a tool to do discovery and identify the data that's in and the data that we're talking about is everything I need to know about my IT operations, my applications, the dependencies. Maybe you could describe a little bit more. >> Sure if you think about one of the things that Joe was mentioning is, today, the workloads are shifting, you're going from, let's say management performance monitoring and management platforms that you need to evolve from, to incorporate new technologies like containers and microservices and server-less architectures. That's one area of how did the tool sets fundamentally evolve to support the latest technologies that are being deployed? So think about that. Second is, how do you consolidate those set of tools now you're managing? Because you're adopting cloud based technologies or new capabilities, and so get consolidation there. And the third is, these workloads that are now migrating out of your private cloud or private data center into public clouds, right? And then that workload migration, I think it is Forrester level saying, about 20% of the total workloads are currently in some sort of a public cloud environments. So there's a lot of work to do in terms of getting to that tipping point of where workloads are now truly in a multi cloud hybrid cloud. So as IBM accelerates that transition and their core competencies in helping these large enterprises make that transition, you need a common manageable environment, that the common visibility across those workloads. So that's at the heart of what we're pulling, and then the data sets happened to be data sets that are coming either from the application layer, data coming from the log management systems, it could be data coming from a service desk in terms of the kind of CMDB based data sets, and we're building a data lake that ultimately allows you to see across these heterogeneous system. >> It could be service request to get that really touches the business process so you can now start to sort of map the value and how change is going to affect that value, right? >> Yeah, exactly. >> Yeah. >> I mean, what's interesting about ScienceLogic as a partner, it's the breadth of their platform in terms of the different things they can monitor, the depth, the ability to go into containers, and kind of understand what the applications are doing in them and the scale in terms of the types of devices. So when you think about, the types of devices, we're going to have to manage everything from, sensors in an Internet of Things, environment to routers, to sophisticated servers and applications that can be running anywhere, you need the flexibility of the platform that they have in order to be able to deliver that. >> And I think that's a key point when you talking about containers and Kubernetes, we heard your CEO Jeannie remitting mentioned Kubernetes, onstage like, that's great, good time(mumbles) I know no one like Kubernetes now it's mainstream. >> Yeah. >> So this is showing them what's going on the industry which is the on premise decomposition of on premise with cloud private, you guys have. >> Yes. >> Is giving them the ability to use containers to manage their existing stuff and do that work and then have the extension to cloud, public cloud or whatever public cloud. This gives them more mount modern capabilities. So the question is, this change the game we know that but how has it changed AIOps and what does it mean? So I guess the first question is, what is AIOps? And what is this new on premise with cloud private and full public cloud architecture look like in AIOps 2.0? >> So for me, it's a very simple definition. It's really using algorithmic mechanisms, right? Towards automating operations, right? It's a very simple way, simplistic way of looking at it. But ultimately, the end game is to automate operations because you need to move at the pace of business and machine speed. And if you want to go, move in machine speed, you can have, I mean, you can't throw enough humans at this problems, right? Because of the pace of change, the familiarity of the workloads spinning up and sitting down. We have a bank as a customer who turns up containers for every 90 seconds and then turn them down. Just can't keep that in that real time state of change and being able to understand the topological relationships between the application layer and the underlying infrastructure so that you can truly understand the service health because when an application degrades in performance, the biggest issue is a war room's scenario where everyone's saying, it's not me, it's not me and because everyone's green on their front, but it's now how do you get that connective tissue all the way running-- >> Well it's also not only the change, it's also the velocity of data coming off that exhaust or the changes and services is thrown off tons of data that you need machines now I mean, that's kind of the thing. >> Exactly, yeah. And I would add to that, I think part of the definition of AIOps is evolving. We know where we're coming from is more fit for purpose analytics, right? I have this problem, I'm the collect this data, I'm going to put these automations in place too address it. We need to kind of take it data Model approach that says, how do I ingest all of this data? You know, even at the start, when you're looking at which workloads and you're doing discovery and assessment of workloads, that data should go into a data lake that can be used later when you're actually doing the operations and management of those workloads. So what data do we collect at every stage of the migration and the transformation of it, and including the operational data? And then how do we put a form analytics on it, and then get the true insights? I think we're just scratching the surface of applying to AI, because it's all been very narrow cast, narrow focus, I have this problem, I collect this data, I can automate this server, it needs to move much beyond that to it... >> And services are turning up and on and off so fast as a non deterministic angle here, and you got state, non deterministic, I mean, those are hard technical computer science problems to solve >> Yeah. >> That's you don't just put a processor around say, oh, yeah. >> Well, let's back to the the scalability of the platform, the ability in real time to be monitoring and looking at that data and then doing something right. >> All right now, humans aren't completely removed from the equation, right? And so I'm interested in how the humans are digesting and visualizing all this data, especially at this speed there a visualization component? How does that all evolving? >> Yeah, I think that to me I mean, that's part of the biggest challenges. You humans are a, they have to be the ones that kind of analyze what's coming and say, what does this mean when you haven't already algorithmically built it into your automation technology, right? And then they also don't have to be the one to train, the system is doing to actually do it. So one of the things that were are that struggling with not struggling with, we're experimenting with is, how best to visualize this, right? We do some things now, we've got a hybrid cloud management platform, we're teaming with the product guys, and it's the ability to have four consoles. One from a consumption, how do I consume services from Amazon, IBM Cloud on premise, how do I deploy it? So in a Dev apps model, how do I fulfill that very quickly and operational councils, right, and then cost on asset management so you can actually have at glance say, oh, you know, I've got a big Hadoop cluster which been spun up, I'm paying $100,000 for it and it has zero utilization. So how do you visualize that so you can say oh, I'm need to put a rule in that if somebody's spinning something up on, you know, IBM Cloud and they're not using it, I either shut it down, or I sent messages out, right, for governance in top of it. So it's putting business rules and logic in terms, in addition to visualization to help automate. >> And Jeannie talked about this at our keynote efficiency versus innovation around how to manage and this is where the scale comes in. Because if you know that something's working, you want to to double down on it, you can then, kind of automate that away and then you just move someone, the humans to something else. This is where the AIOps I think it's going to be, I think, going to change the category. I mean, it's a Gartner Magic Quadrant for the IT operations. >> Right. >> AI potentially decimates that, I mean... >> Yeah, there's this argument that you know, you have these nice quadrants or let's say nicely defined market segments. You have the NPMD, the ITSM, the ITOM, you know, you have APM and so what's happening is in this world of AIOps, none of those D marks really fit anymore because you're seeing the convergence of that. And then the other transition that's happening is this movement from, you know, classic ops or Dev and a dev to Ops, Dev Ops and now dev sec Ops, you know, you're trying to get worlds to converge. And so when we talk about the data and being able to build data models, those data models need to converge across those domains. So a lot of the work we do is collect data sets from log management, from service desk and service management, from APM etc, and then build that data model in real time. So you can.... >> It kind of building an Uber or CMDB or I mean, right? (loud laughter) I mean, do most of your clients have a single CMDB? Probably not, right? >> Yeah. So this is sort of a new guidepost, isn't it? >> Yeah, a part of it is. There are these data puddles if you will, all right data exist in a lot of different places How do you bring them together so you can federate different data sources, different catalogs into a common platform because if a user is trying to decide, okay, should I spin this up on, you know, this environment or that one, you want the full catalog of capabilities that are on premise in your CMDB system with the legacy environment out of the catalogs that may exist on Amazon or Azure, etc and you want data across all that. >> It seems that everything's a data problem now. And datas are being embedded into the applications which are then the workflows are defining infrastructure, architecture, or are sole cloud, multi cloud, whatever the resource is, so we had JPMorgan Chase on top data geek on and she was talking about, we have models for the models and IBM has been talking about this concept of reasoning around the data. This is why I always like the cognition kind of angle of cognitive, because that's not just math, math is math, you do math on, you know, supervised machine learning and knowing processes to be efficient, but the cognition and the reasoning really helps get at that data set, right. So can you guys react to that? I mean, is everything a data problem? Is that how you should look at it and how does reasoning fit into all this? >> Well, I mean, that's back to your point about what is the humans role in this, right. So we're moving in a services business from primarily labor base with tools to make them more efficient to the technology doing the work. But the humans have to then say, when the technology get stumped, what does that mean? So should I build a new, how do I train it better? How do I, you know, take my domain expertise? How do I do the deep analytics to tell me all right, how do I solve those problems in the future? So the role changes I think Jenny talks about in terms of new collar workers. I mean, these are data scientists, these are people that understand the dynamics of the inner relationship of the different data, the data models that need to get built and they are guiding in effect the automation. >> I thought your CTO was on theCUBE talking about, Paul was talking about, you know, take the heavy and Rob Thomas was also on, the GM of the data plus AI team. I think he really nailed it. If you guys to take away the heavy lifting of the setup work then the data science who're actually there to do the reasoning or help assist in managing what's going on and putting guard rails around whatever business policy is. >> Today, I mean, we talked to in this about 79 percent I think it's a gardener stat of 79 percent of the data scientists. And these are these PhDs, they're highly valuable, spend their time collecting, preparing, cleansing those data models, right? So, you're now really applying that PhD level knowledge base towards solving a problem, you're just trying to make sense of the data. So one, do you have a holistic and a few? Two, is there a way to automate those things so you can then apply the human aspects towards the things that Joe was talking about. So that's a big part of what we're trying to come together in terms of the market for. >> Well guys thanks for the insight, thanks for coming on, great job. I think we talked for you know, an hour and on cultural shift because you mentioned the sets in here Ops and devs. It's a melting pot and it's a cultural shifts. I think that topic is worth following up on. But I'll let you guys just get a quick plug for you. I know you going to an event coming up and you got some work. You can talk about what you guys are doing. You got an event coming up, what your pitch, give a quick flag. >> Yeah, so we've got our symposium, which is our big user conference. It's in April. It's right in, it's on April 22 to 23rd to the 25th. It's in downtown Washington DC, Cherry Blossom festival season at the Ritz Carlton. And so a lot of that, we'll have theCUBE there as well. >> Yeah of course. >> So, we're looking forward to it. A lot of great energy to be carried over. >> We love going to the District. (laughs loudly) >> What don't we say, you guys are great, great to visit. So give the plugs with a service you're doing. Just give an update on what you guys are up to. >> Yeah, I think I mean, we're also we're investing the technology when we're full on board with the containerization, as we talked about, we're putting together a services portfolio. I think Jenny mentioned that we're taking a whole bunch of capability across IBM Global Technology Services, Global Business Services, and really coalescing into about, you know, 23 offerings to help customers advise on cloud, move to cloud build for cloud and manage on cloud and then you've seen the announcements here about what we're doing around the multi cloud management system. Those four console I talked about how do we help, you know, put a gearbox in place to manage the complexity of the hybrid nature that our customers are dealing with. >> It seems IBM got clear visibility on what's happening with cloud, cloud private, I think a really big announcement. I think it's not talked about in the show and I'll always kind of mentioned the key linchpin but you see cloud, multi cloud, hybrid cloud, you got AI and you got partnerships, ecosystem now its execution time, right? >> Yeah, exactly and, and frankly, that's the challenge, right? So we used to be able to manage it all on the four runs, right? Your SAP instances was in the data center, your servers were in the data center, your middleware is in the data center. Now I got my applications running in Salesforce.com often software as a service. I've got three or four different infrastructures of service providers. But I still have the legacy that I got to deal with. I mean the integration problems are just tremendous. >> Chairman VP of strategy at IBM hybrid cloud and Murali Nemani, CMO ScienceLogic, AI operations, bringing in hybrid clouds to theCUBE bringing all the coverage day four. I'm with Dave Volante, it's all about cloud AI developers all happening here in San Francisco this week. Stay with us from this short break. (upbeat music)