>> 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. >> A better than expected earnings report in late August got people excited about Snowflake again, but the negative sentiment in the market is weighed heavily on virtually all growth tech stocks and Snowflake is no exception. As we've stressed many times the company's management is on a long term mission to dramatically simplify the way organizations use data. Snowflake is tapping into a multi hundred billion dollar total available market and continues to grow at a rapid pace. In our view, Snowflake is embarking on its third major wave of innovation data apps, while its first and second waves are still bearing significant fruit. Now for short term traders focused on the next 90 or 180 days, that probably doesn't matter. But those taking a longer view are asking, "Should we still be optimistic about the future of this high flyer or is it just another over hyped tech play?" Hello and welcome to this week's Wiki Bond Cube Insights powered by ETR. Snowflake's Quarter just ended. And in this breaking analysis we take a look at the most recent survey data from ETR to see what clues and nuggets we can extract to predict the near term future in the long term outlook for Snowflake which is going to announce its earnings at the end of this month. Okay, so you know the story. If you've been investor in Snowflake this year, it's been painful. We said at IPO, "If you really want to own this stock on day one, just hold your nose and buy it." But like most IPOs we said there will be likely a better entry point in the future, and not surprisingly that's been the case. Snowflake IPOed a price of 120, which you couldn't touch on day one unless you got into a friends and family Delio. And if you did, you're still up 5% or so. So congratulations. But at one point last year you were up well over 200%. That's been the nature of this volatile stock, and I certainly can't help you with the timing of the market. But longer term Snowflake is targeting 10 billion in revenue for fiscal year 2028. A big number. Is it achievable? Is it big enough? Tell you what, let's come back to that. Now shorter term, our expert trader and breaking analysis contributor Chip Simonton said he got out of the stock a while ago after having taken a shot at what turned out to be a bear market rally. He pointed out that the stock had been bouncing around the 150 level for the last few months and broke that to the downside last Friday. So he'd expect 150 is where the stock is going to find resistance on the way back up, but there's no sign of support right now. He said maybe at 120, which was the July low and of course the IPO price that we just talked about. Now, perhaps earnings will be a catalyst, when Snowflake announces on November 30th, but until the mentality toward growth tech changes, nothing's likely to change dramatically according to Simonton. So now that we have that out of the way, let's take a look at the spending data for Snowflake in the ETR survey. Here's a chart that shows the time series breakdown of snowflake's net score going back to the October, 2021 survey. Now at that time, Snowflake's net score stood at a robust 77%. And remember, net score is a measure of spending velocity. It's a proprietary network, and ETR derives it from a quarterly survey of IT buyers and asks the respondents, "Are you adopting the platform new? Are you spending 6% or more? Is you're spending flat? Is you're spending down 6% or worse? Or are you leaving the platform decommissioning?" You subtract the percent of customers that are spending less or churning from those that are spending more and adopting or adopting and you get a net score. And that's expressed as a percentage of customers responding. In this chart we show Snowflake's in out of the total survey which ranges... The total survey ranges between 1,200 and 1,400 each quarter. And the very last column... Oh sorry, very last row, we show the number of Snowflake respondents that are coming in the survey from the Fortune 500 and the Global 2000. Those are two very important Snowflake constituencies. Now what this data tells us is that Snowflake exited 2021 with very strong momentum in a net score of 82%, which is off the charts and it was actually accelerating from the previous survey. Now by April that sentiment had flipped and Snowflake came down to earth with a 68% net score. Still highly elevated relative to its peers, but meaningfully down. Why was that? Because we saw a drop in new ads and an increase in flat spend. Then into the July and most recent October surveys, you saw a significant drop in the percentage of customers that were spending more. Now, notably, the percentage of customers who are contemplating adding the platform is actually staying pretty strong, but it is off a bit this past survey. And combined with a slight uptick in planned churn, net score is now down to 60%. That uptick from 0% and 1% and then 3%, it's still small, but that net score at 60% is still 20 percentage points higher than our highly elevated benchmark of 40% as you recall from listening to earlier breaking analysis. That 40% range is we consider a milestone. Anything above that is actually quite strong. But again, Snowflake is down and coming back to churn, while 3% churn is very low, in previous quarters we've seen Snowflake 0% or 1% decommissions. Now the last thing to note in this chart is the meaningful uptick in survey respondents that are citing, they're using the Snowflake platform. That's up to 212 in the survey. So look, it's hard to imagine that Snowflake doesn't feel the softening in the market like everyone else. Snowflake is guiding for around 60% growth in product revenue against the tough compare from a year ago with a 2% operating margin. So like every company, the reaction of the street is going to come down to how accurate or conservative the guide is from their CFO. Now, earlier this year, Snowflake acquired a company called Streamlit for around $800 million. Streamlit is an open source Python library and it makes it easier to build data apps with machine learning, obviously a huge trend. And like Snowflake, generally its focus is on simplifying the complex, in this case making data science easier to integrate into data apps that business people can use. So we were excited this summer in the July ETR survey to see that they added some nice data and pick on Streamlit, which we're showing here in comparison to Snowflake's core business on the left hand side. That's the data warehousing, the Streamlit pieces on the right hand side. And we show again net score over time from the previous survey for Snowflake's core database and data warehouse offering again on the left as compared to a Streamlit on the right. Snowflake's core product had 194 responses in the October, 22 survey, Streamlit had an end of 73, which is up from 52 in the July survey. So significant uptick of people responding that they're doing business in adopting Streamlit. That was pretty impressive to us. And it's hard to see, but the net scores stayed pretty constant for Streamlit at 51%. It was 52% I think in the previous quarter, well over that magic 40% mark. But when you blend it with Snowflake, it does sort of bring things down a little bit. Now there are two key points here. One is that the acquisition seems to have gained exposure right out of the gate as evidenced by the large number of responses. And two, the spending momentum. Again while it's lower than Snowflake overall, and when you blend it with Snowflake it does pull it down, it's very healthy and steady. Now let's do a little pure comparison with some of our favorite names in this space. This chart shows net score or spending velocity in the Y-axis, an overlap or presence, pervasiveness if you will, in the data set on the X-axis. That red dotted line again is that 40% highly elevated net score that we like to talk about. And that table inserted informs us as to how the companies are plotted, where the dots set up, the net score, the ins. And we're comparing a number of database players, although just a caution, Oracle includes all of Oracle including its apps. But we just put it in there for reference because it is the leader in database. Right off the bat, Snowflake jumps out with a net score of 64%. The 60% from the earlier chart, again included Streamlit. So you can see its core database, data warehouse business actually is higher than the total company average that we showed you before 'cause the Streamlit is blended in. So when you separate it out, Streamlit is right on top of data bricks. Isn't that ironic? Only Snowflake and Databricks in this selection of names are above the 40% level. You see Mongo and Couchbase, they know they're solid and Teradata cloud actually showing pretty well compared to some of the earlier survey results. Now let's isolate on the database data platform sector and see how that shapes up. And for this analysis, same XY dimensions, we've added the big giants, AWS and Microsoft and Google. And notice that those three plus Snowflake are just at or above the 40% line. Snowflake continues to lead by a significant margin in spending momentum and it keeps creeping to the right. That's that end that we talked about earlier. Now here's an interesting tidbit. Snowflake is often asked, and I've asked them myself many times, "How are you faring relative to AWS, Microsoft and Google, these big whales with Redshift and Synapse and Big Query?" And Snowflake has been telling folks that 80% of its business comes from AWS. And when Microsoft heard that, they said, "Whoa, wait a minute, Snowflake, let's partner up." 'Cause Microsoft is smart, and they understand that the market is enormous. And if they could do better with Snowflake, one, they may steal some business from AWS. And two, even if Snowflake is winning against some of the Microsoft database products, if it wins on Azure, Microsoft is going to sell more compute and more storage, more AI tools, more other stuff to these customers. Now AWS is really aggressive from a partnering standpoint with Snowflake. They're openly negotiating, not openly, but they're negotiating better prices. They're realizing that when it comes to data, the cheaper that you make the offering, the more people are going to consume. At scale economies and operating leverage are really powerful things at volume that kick in. Now Microsoft, they're coming along, they obviously get it, but Google is seemingly resistant to that type of go to market partnership. Rather than lean into Snowflake as a great partner Google's field force is kind of fighting fashion. Google itself at Cloud next heavily messaged what they call the open data cloud, which is a direct rip off of Snowflake. So what can we say about Google? They continue to be kind of behind the curve when it comes to go to market. Now just a brief aside on the competitive posture. I've seen Slootman, Frank Slootman, CEO of Snowflake in action with his prior companies and how he depositioned the competition. At Data Domain, he eviscerated a company called Avamar with their, what he called their expensive and slow post process architecture. I think he actually called it garbage, if I recall at one conference I heard him speak at. And that sort of destroyed BMC when he was at ServiceNow, kind of positioning them as the equivalent of the department of motor vehicles. And so it's interesting to hear how Snowflake openly talks about the data platforms of AWS, Microsoft, Google, and data bricks. I'll give you this sort of short bumper sticker. Redshift is just an on-prem database that AWS morphed to the cloud, which by the way is kind of true. They actually did a brilliant job of it, but it's basically a fact. Microsoft Excel, a collection of legacy databases, which also kind of morphed to run in the cloud. And even Big Query, which is considered cloud native by many if not most, is being positioned by Snowflake as originally an on-prem database to support Google's ad business, maybe. And data bricks is for those people smart enough to get it to Berkeley that love complexity. And now Snowflake doesn't, they don't mention Berkeley as far as I know. That's my addition. But you get the point. And the interesting thing about Databricks and Snowflake is a while ago in the cube I said that there was a new workload type emerging around data where you have AWS cloud, Snowflake obviously for the cloud database and Databricks data for the data science and EML, you bring those things together and there's this new workload emerging that's going to be very powerful in the future. And it's interesting to see now the aspirations of all three of these platforms are colliding. That's quite a dynamic, especially when you see both Snowflake and Databricks putting venture money and getting their hooks into the loyalties of the same companies like DBT labs and Calibra. Anyway, Snowflake's posture is that we are the pioneer in cloud native data warehouse, data sharing and now data apps. And our platform is designed for business people that want simplicity. The other guys, yes, they're formidable, but we Snowflake have an architectural lead and of course we run in multiple clouds. So it's pretty strong positioning or depositioning, you have to admit. Now I'm not sure I agree with the big query knockoffs completely. I think that's a bit of a stretch, but snowflake, as we see in the ETR survey data is winning. So in thinking about the longer term future, let's talk about what's different with Snowflake, where it's headed and what the opportunities are for the company. Snowflake put itself on the map by focusing on simplifying data analytics. What's interesting about that is the company's founders are as you probably know from Oracle. And rather than focusing on transactional data, which is Oracle's sweet spot, the stuff they worked on when they were at Oracle, the founder said, "We're going to go somewhere else. We're going to attack the data warehousing problem and the data analytics problem." And they completely re-imagined the database and how it could be applied to solve those challenges and reimagine what was possible if you had virtually unlimited compute and storage capacity. And of course Snowflake became famous for separating the compute from storage and being able to completely shut down compute so you didn't have to pay for it when you're not using it. And the ability to have multiple clusters hit the same data without making endless copies and a consumption/cloud pricing model. And then of course everyone on the planet realized, "Wow, that's a pretty good idea." Every venture capitalist in Silicon Valley has been funding companies to copy that move. And that today has pretty much become mainstream in table stakes. But I would argue that Snowflake not only had the lead, but when you look at how others are approaching this problem, it's not necessarily as clean and as elegant. Some of the startups, the early startups I think get it and maybe had an advantage of starting later, which can be a disadvantage too. But AWS is a good example of what I'm saying here. Is its version of separating compute from storage was an afterthought and it's good, it's... Given what they had it was actually quite clever and customers like it, but it's more of a, "Okay, we're going to tier to storage to lower cost, we're going to sort of dial down the compute not completely, we're not going to shut it off, we're going to minimize the compute required." It's really not true as separation is like for instance Snowflake has. But having said that, we're talking about competitors with lots of resources and cohort offerings. And so I don't want to make this necessarily all about the product, but all things being equal architecture matters, okay? So that's the cloud S-curve, the first one we're showing. Snowflake's still on that S-curve, and in and of itself it's got legs, but it's not what's going to power the company to 10 billion. The next S-curve we denote is the multi-cloud in the middle. And now while 80% of Snowflake's revenue is AWS, Microsoft is ramping up and Google, well, we'll see. But the interesting part of that curve is data sharing, and this idea of data clean rooms. I mean it really should be called the data sharing curve, but I have my reasons for calling it multi-cloud. And this is all about network effects and data gravity, and you're seeing this play out today, especially in industries like financial services and healthcare and government that are highly regulated verticals where folks are super paranoid about compliance. There not going to share data if they're going to get sued for it, if they're going to be in the front page of the Wall Street Journal for some kind of privacy breach. And what Snowflake has done is said, "Put all the data in our cloud." Now, of course now that triggers a lot of people because it's a walled garden, okay? It is. That's the trade off. It's not the Wild West, it's not Windows, it's Mac, it's more controlled. But the idea is that as different parts of the organization or even partners begin to share data that they need, it's got to be governed, it's got to be secure, it's got to be compliant, it's got to be trusted. So Snowflake introduced the idea of, they call these things stable edges. I think that's the term that they use. And they track a metric around stable edges. And so a stable edge, or think of it as a persistent edge is an ongoing relationship between two parties that last for some period of time, more than a month. It's not just a one shot deal, one a done type of, "Oh guys shared it for a day, done." It sent you an FTP, it's done. No, it's got to have trajectory over time. Four weeks or six weeks or some period of time that's meaningful. And that metric is growing. Now I think sort of a different metric that they track. I think around 20% of Snowflake customers are actively sharing data today and then they track the number of those edge relationships that exist. So that's something that's unique. Because again, most data sharing is all about making copies of data. That's great for storage companies, it's bad for auditors, and it's bad for compliance officers. And that trend is just starting out, that middle S-curve, it's going to kind of hit the base of that steep part of the S-curve and it's going to have legs through this decade we think. And then finally the third wave that we show here is what we call super cloud. That's why I called it multi-cloud before, so it could invoke super cloud. The idea that you've built a PAS layer that is purpose built for a specific objective, and in this case it's building data apps that are cloud native, shareable and governed. And is a long-term trend that's going to take some time to develop. I mean, application development platforms can take five to 10 years to mature and gain significant adoption, but this one's unique. This is a critical play for Snowflake. If it's going to compete with the big cloud players, it has to have an app development framework like Snowpark. It has to accommodate new data types like transactional data. That's why it announced this thing called UniStore last June, Snowflake a summit. And the pattern that's forming here is Snowflake is building layer upon layer with its architecture at the core. It's not currently anyway, it's not going out and saying, "All right, we're going to buy a company that's got to another billion dollars in revenue and that's how we're going to get to 10 billion." So it's not buying its way into new markets through revenue. It's actually buying smaller companies that can complement Snowflake and that it can turn into revenue for growth that fit in to the data cloud. Now as to the 10 billion by fiscal year 28, is that achievable? That's the question. Yeah, I think so. Would the momentum resources go to market product and management prowess that Snowflake has? Yes, it's definitely achievable. And one could argue to $10 billion is too conservative. Indeed, Snowflake CFO, Mike Scarpelli will fully admit his forecaster built on existing offerings. He's not including revenue as I understand it from all the new stuff that's in the pipeline because he doesn't know what it's going to look like. He doesn't know what the adoption is going to look like. He doesn't have data on that adoption, not just yet anyway. And now of course things can change quite dramatically. It's possible that is forecast for existing businesses don't materialize or competition picks them off or a company like Databricks actually is able in the longer term replicate the functionality of Snowflake with open source technologies, which would be a very competitive source of innovation. But in our view, there's plenty of room for growth, the market is enormous and the real key is, can and will Snowflake deliver on the promises of simplifying data? Of course we've heard this before from data warehouse, the data mars and data legs and master data management and ETLs and data movers and data copiers and Hadoop and a raft of technologies that have not lived up to expectations. And we've also, by the way, seen some tremendous successes in the software business with the likes of ServiceNow and Salesforce. So will Snowflake be the next great software name and hit that 10 billion magic mark? I think so. Let's reconnect in 2028 and see. Okay, we'll leave it there today. I want to thank Chip Simonton for his input to today's episode. Thanks to Alex Myerson who's on production and manages the podcast. Ken Schiffman as well. Kristin Martin and Cheryl Knight help get the word out on social media and in our newsletters. And Rob Hove is our Editor in Chief over at Silicon Angle. He does some great editing for us. Check it out for all the news. Remember all these episodes are available as podcasts. Wherever you listen, just search Breaking Analysis podcast. I publish each week on wikibon.com and siliconangle.com. Or you can email me to get in touch David.vallante@siliconangle.com. DM me @dvellante or comment on our LinkedIn post. And please do check out etr.ai, they've got the best survey data in the enterprise tech business. This is Dave Vellante for the CUBE Insights, powered by ETR. Thanks for watching, thanks for listening and we'll see you next time on breaking analysis. (upbeat music)

>> From theCUBE studios in Palo Alto in Boston, bringing you data-driven insights from the cube and ETR, this is Breaking Analysis with Dave Vellante. >> Organizations have considerable room to improve their performance without making expensive changes to their talent, their structure, or their fundamental business model. You don't need a slew of consultants to tell you what to do. You already know. What you need is to immediately ratchet up expectations, energy, urgency, and intensity. You have to fight mediocrity every step of the way. Amp it up and the results will follow. This is the fundamental premise of a hard-hitting new book written by Frank Slootman, CEO of Snowflake, and published earlier this year. It's called "Amp It Up, Leading for Hypergrowth "by Raising Expectations, Increasing Urgency, "and Elevating Intensity." Hello and welcome to this week's Wikibon CUBE Insights, powered by ETR. At Snowflake Summit last month, I was asked to interview Frank on stage about his new book. I've read it several times. And if you haven't read it, you should. Even if you have read it, in this Breaking Analysis, we'll dig deeper into the book and share some clarifying insights and nuances directly from Slootman himself from my one-on-one conversation with him. My first question to Slootman was why do you write this book? Okay, it's kind of a common throwaway question. And how the heck did you find time to do it? It's fairly well-known that a few years ago, Slootman put up a post on LinkedIn with the title Amp It Up. It generated so much buzz and so many requests for Frank's time that he decided that the best way to efficiently scale and share his thoughts on how to create high-performing companies and organizations was to publish a book. Now, he wrote the book during the pandemic. And I joked that they must not have Netflix in Montana where he resides. In a pretty funny moment, he said that writing the book was easier than promoting it. Take a listen. >> Denise, our CMO, you know, she just made sure that this process wasn't going to. It was more work for me to promote this book with all these damn podcasts and other crap, than actually writing the book, you know. And after a while, I was like I'm not doing another podcast. >> Now, the book gives a lot of interesting background information on Slootman's career and what he learned at various companies that he led and participated in. Now, I'm not going to go into most of that today, which is why you should read the book yourself. But Slootman, he's become somewhat of a business hero to many people, myself included. Leaders like Frank, Scott McNealy, Jayshree Ullal, and my old boss, Pat McGovern at IDG, have inspired me over the years. And each has applied his or her own approach to building cultures and companies. Now, when Slootman first took over the reins at Snowflake, I published a Breaking Analysis talking about Snowflake and what we could expect from the company now that Slootman and CFO Mike Scarpelli were back together. In that post, buried toward the end, I referenced the playbook that Frank used at Data Domain and ServiceNow, two companies that I followed quite closely as an analyst, and how it would be applied at Snowflake, that playbook if you will. Frank reached out to me afterwards and said something to the effect of, "I don't use playbooks. "I am a situational leader. "Playbooks, you know, they work in football games. "But in the military, they teach you "situational leadership." Pretty interesting learning moment for me. So I asked Frank on the stage about this. Here's what he said. >> The older you get, the more experience that you have, the more you become a prisoner of your own background because you sort of think in terms of what you know as opposed to, you know, getting outside of what you know and trying to sort of look at things like a five-year-old that has never seen this before. And then how would you, you know, deal with it? And I really try to force myself into I've never seen this before and how do I think about it? Because at least they're very different, you know, interpretations. And be open-minded, just really avoid that rinse and repeat mentality. And you know, I've brought people in from who have worked with me before. Some of them come with me from company to company. And they were falling prey to, you know, rinse and repeat. I would just literally go like that's not what we want. >> So think about that for a moment. I mean, imagine coming in to lead a new company and forcing yourself and your people to forget what they know that works and has worked in the past, put that aside and assess the current situation with an open mind, essentially start over. Now, that doesn't mean you don't apply what has worked in the past. Slootman talked to me about bringing back Scarpelli and the synergistic relationship that they have and how they build cultures and the no BS and hard truth mentality they bring to companies. But he bristles when people ask him, "What type of CEO are you?" He says, "Do we have to put a label on it? "It really depends on the situation." Now, one of the other really hard-hitting parts of the book was the way Frank deals with who to keep and who to let go. He uses the Volkswagen tagline of drivers wanted. He says in his book, in companies there are passengers and there are drivers, and we want drivers. He said, "You have to figure out really quickly "who the drivers are and basically throw the wrong people "off the bus, keep the right people, bring in new people "that fit the culture and put them "in the right seats on the bus." Now, these are not easy decisions to make. But as it pertains to getting rid of people, I'm reminded of the movie "Moneyball." Art Howe, the manager of the Oakland As, he refused to play Scott Hatteberg at first base. So the GM, Billy Bean played by Brad Pitt says to Peter Brand who was played by Jonah Hill, "You have to fire Carlos Pena." Don't learn how to fire people. Billy Bean says, "Just keep it quick. "Tell him he's been traded and that's it." So I asked Frank, "Okay, I get it. "Like the movie, when you have the wrong person "on the bus, you just have to make the decision, "be straightforward, and do it." But I asked him, "What if you're on the fence? "What if you're not completely sure if this person "is a driver or a passenger, if he or she "should be on the bus or not on the bus? "How do you handle that?" Listen to what he said. >> I have a very simple way to break ties. And when there's doubt, there's no doubt, okay? >> When there's doubt, there's no doubt. Slootman's philosophy is you have to be emphatic and have high conviction. You know, back to the baseball analogy, if you're thinking about taking the pitcher out of the game, take 'em out. Confrontation is the single hardest thing in business according to Slootman but you have to be intellectually honest and do what's best for the organization, period. Okay, so wow, that may sound harsh but that's how Slootman approaches it, very Belichickian if you will. But how can you amp it up on a daily basis? What's the approach that Slootman takes? We got into this conversation with a discussion about MBOs, management by objective. Slootman in his book says he's killed MBOs at every company he's led. And I asked him to explain why. His rationale was that individual MBOs invariably end up in a discussion about relief of the MBO if the person is not hitting his or her targets. And that detracts from the organizational alignment. He said at Snowflake everyone gets paid the same way, from the execs on down. It's a key way he creates focus and energy in an organization, by creating alignment, urgency, and putting more resources into the most important things. This is especially hard, Slootman says, as the organization gets bigger. But if you do approach it this way, everything gets easier. The cadence changes, the tempo accelerates, and it works. Now, and to emphasize that point, he said the following. Play the clip. >> Every meeting that you have, every email, every encounter in the hallway, whatever it is, is an opportunity to amp things up. That's why I use that title. But do you take that opportunity? >> And according to Slootman, if you don't take that opportunity, if you're not in the moment, amping it up, then you're thinking about your golf game or the tennis match that's going on this weekend or being out on your boat. And to the point, this approach is not for everyone. You're either built for it or you're not. But if you can bring people into the organization that can handle this type of dynamic, it creates energy. It becomes fun. Everything moves faster. The conversations are exciting. They're inspiring. And it becomes addictive. Now let's talk about priorities. I said to Frank that for me anyway, his book was an uncomfortable read. And he was somewhat surprised by that. "Really," he said. I said, "Yeah. "I mean, it was an easy read but uncomfortable "because over my career, I've managed thousands of people, "not tens of thousands but thousands, "enough to have to take this stuff very seriously." And I found myself throughout the book, oh, you know, on the one hand saying to myself, "Oh, I got that right, good job, Dave." And then other times, I was thinking to myself, "Oh wow, I probably need to rethink that. "I need to amp it up on that front." And the point is to Frank's leadership philosophy, there's no one correct way to approach all situations. You have to figure it out for yourself. But the one thing in the book that I found the hardest was Slootman challenged the reader. If you had to drop everything and focus on one thing, just one thing, for the rest of the year, what would that one thing be? Think about that for a moment. Were you able to come up with that one thing? What would happen to all the other things on your priority list? Are they all necessary? If so, how would you delegate those? Do you have someone in your organization who can take those off your plate? What would happen if you only focused on that one thing? These are hard questions. But Slootman really forces you to think about them and do that mental exercise. Look at Frank's body language in this screenshot. Imagine going into a management meeting with Frank and being prepared to share all the things you're working on that you're so proud of and all the priorities you have for the coming year. Listen to Frank in this clip and tell me it doesn't really make you think. >> I've been in, you know, on other boards and stuff. And I got a PowerPoint back from the CEO and there's like 15 things. They're our priorities for the year. I'm like you got 15, you got none, right? It's like you just can't decide, you know, what's important. So I'll tell you everything because I just can't figure out. And the thing is it's very hard to just say one thing. But it's really the mental exercise that matters. >> Going through that mental exercise is really important according to Slootman. Let's have a conversation about what really matters at this point in time. Why does it need to happen? And does it take priority over other things? Slootman says you have to pull apart the hairball and drive extraordinary clarity. You could be wrong, he says. And he admits he's been wrong on many things before. He, like everyone, is fearful of being wrong. But if you don't have the conversation according to Slootman, you're already defeated. And one of the most important things Slootman emphasizes in the book is execution. He said that's one of the reasons he wrote "Amp It Up." In our discussion, he referenced Pat Gelsinger, his former boss, who bought Data Domain when he was working for Joe Tucci at EMC. Listen to Frank describe the interaction with Gelsinger. >> Well, one of my prior bosses, you know, Pat Gelsinger, when they acquired Data Domain through EMC, Pat was CEO of Intel. And he quoted Andy Grove as saying, 'cause he was Intel for a long time when he was younger man. And he said no strategy is better than its execution, which if I find one of the most brilliant things. >> Now, before you go changing your strategy, says Slootman, you have to eliminate execution as a potential point of failure. All too often, he says, Silicon Valley wants to change strategy without really understanding whether the execution is right. All too often companies don't consider that maybe the product isn't that great. They will frequently, for example, make a change to sales leadership without questioning whether or not there's a product fit. According to Slootman, you have to drive hardcore intellectual honesty. And as uncomfortable as that may be, it's incredibly important and powerful. Okay, one of the other contrarian points in the book was whether or not to have a customer success department. Slootman says this became really fashionable in Silicon Valley with the SaaS craze. Everyone was following and pattern matching the lead of salesforce.com. He says he's eliminated the customer service department at every company he's led which had a customer success department. Listen to Frank Slootman in his own words talk about the customer success department. >> I view the whole company as a customer success function. Okay, I'm customer success, you know. I said it in my presentation yesterday. We're a customer-first organization. I don't need a department. >> Now, he went on to say that sales owns the commercial relationship with the customer. Engineering owns the technical relationship. And oh, by the way, he always puts support inside of the engineering department because engineering has to back up support. And rather than having a separate department for customer success, he focuses on making sure that the existing departments are functioning properly. Slootman also has always been big on net promoter score, NPS. And Snowflake's is very high at 72. And according to Slootman, it's not just the product. It's the people that drive that type of loyalty. Now, Slootman stresses amping up the big things and even the little things too. He told a story about someone who came into his office to ask his opinion about a tee shirt. And he turned it around on her and said, "Well, what do you think?" And she said, "Well, it's okay." So Frank made the point by flipping the situation. Why are you coming to me with something that's just okay? If we're going to do something, let's do it. Let's do it all out. Let's do it right and get excited about it, not just check the box and get something off your desk. Amp it up, all aspects of our business. Listen to Slootman talk about Steve Jobs and the relevance of demanding excellence and shunning mediocrity. >> He was incredibly intolerant of anything that he didn't think of as great. You know, he was immediately done with it and with the person. You know, I'm not that aggressive, you know, in that way. I'm a little bit nicer, you know, about it. But I still, you know, I don't want to give into expediency and mediocrity. I just don't, I'm just going to fight it, you know, every step of the way. >> Now, that story was about a little thing like some swag. But Slootman talked about some big things too. And one of the major ways Snowflake was making big, sweeping changes to amp up its business was reorganizing its go-to-market around industries like financial services, media, and healthcare. Here's some ETR data that shows Snowflake's net score or spending momentum for key industry segments over time. The red dotted line at 40% is an indicator of highly elevated spending momentum. And you can see for the key areas shown, Snowflake is well above that level. And we cut this data where responses were greater, the response numbers were greater than 15. So not huge ends but large enough to have meaning. Most were in the 20s. Now, it's relatively uncommon to see a company that's having the success of Snowflake make this kind of non-trivial change in the middle of steep S-curve growth. Why did they make this move? Well, I think it's because Snowflake realizes that its data cloud is going to increasingly have industry diversity and unique value by industry, that ecosystems and data marketplaces are forming around industries. So the more industry affinity Snowflake can create, the stronger its moat will be. It also aligns with how the largest and most prominent global system integrators, global SIs, go to market. This is important because as companies are transforming, they are radically changing their data architecture, how they think about data, how they approach data as a competitive advantage, and they're looking at data as specifically a monetization opportunity. So having industry expertise and knowledge and aligning with those customer objectives is going to serve Snowflake and its ecosystems well in my view. Slootman even said he joined the board of Instacart not because he needed another board seat but because he wanted to get out of his comfort zone and expose himself to other industries as a way to learn. So look, we're just barely scratching the surface of Slootman's book and I've pulled some highlights from our conversation. There's so much more that I can share just even from our conversation. And I will as the opportunity arises. But for now, I'll just give you the kind of bumper sticker of "Amp It Up." Raise your standards by taking every opportunity, every interaction, to increase your intensity. Get your people aligned and moving in the same direction. If it's the wrong direction, figure it out and course correct quickly. Prioritize and sharpen your focus on things that will really make a difference. If you do these things and increase the urgency in your organization, you'll naturally pick up the pace and accelerate your company. Do these things and you'll be able to transform, better identify adjacent opportunities and go attack them, and create a lasting and meaningful experience for your employees, customers, and partners. Okay, that's it for today. Thanks for watching. And thank you to Alex Myerson who's on production and he manages the podcast for Breaking Analysis. Kristin Martin and Cheryl Knight help get the word out on social and in our newsletters. And Rob Hove is our EIC over at Silicon Angle who does some wonderful and tremendous editing. Thank you all. Remember, all these episodes are available as podcasts. Wherever you listen, just search Breaking Analysis podcast. I publish each week on wikibon.com and siliconangle.com. And you can email me at david.vellante@siliconangle.com or DM me @dvellante or comment on my LinkedIn posts. And please do check out etr.ai for the best survey data in enterprise tech. This is Dave Vellante for theCUBE Insights, powered by ETR. Thanks for watching. Be well. And we'll see you next time on Breaking Analysis. (upbeat music)

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 snowflake they love the stock at 400 and hated at 165 that's the nature of the business i guess especially in this crazy cycle over the last two years of lockdowns free money exploding demand and now rising inflation and rates but with the fed providing some clarity on its actions the time has come to really dig into the fundamentals of companies and there's no tech company that's more fun to analyze than snowflake hello and welcome to this week's wikibon cube insights powered by etr in this breaking analysis we look at the action of snowflake stock since its ipo why it's behaved the way it has how some sharp traders are looking at the stock and most importantly what customer demand looks like the stock has really provided some great theater since its ipo i know people who got in at 120 before the open and i know lots of people who kind of held their noses and bought the stock on day one at over 300 a day when it closed at around 240 that first day of trading snowflake hit 164 this week it's all-time low as a public company as my college roommate chip simonton a long time trader told me when great companies trade at all times time lows because of panic it's worth taking a shot he did now of course the stock could go lower there's geopolitical risk and the stock with a 64 billion market cap is expensive for a company that's forecast to do around 2 billion in product revenue this year and remember i don't recommend stocks you shouldn't take my advice and my comments you got to do your own research but i have lots of data and i have opinions and i'm willing to share that with you stocks like snowflake crowdstrike z-scaler octa and companies like this are highly volatile when markets are moving up they're going to move up faster than the mean when they're declining they're going to drop more severely and that's clearly what's happened to snowflake so with a company like this you when you see panic selling you'll also see panic buying sometimes like we we've seen with this name it went from 220 to 320 in a very short period earlier snowflake put in a short-term bottom this week and many traders feel the issue was oversold so they bought okay but not everyone felt this way and you can see this in the headlines snowflake hits low but cloud stocks rise and we're going to come back to that is it a buy don't buy the dip buy the dip and what snowflake investors can learn from microsoft and from the street.com snow stock is sliding on the back of ill-conceived guidance and to that i would say that conservative guidance these days is anything but ill-conceived now let's unpack all this a bit and to do so i reached out to ivana delevska who has been on this program before she's with spear invest a female-led etf that goes deep into understanding supply chains she came on breaking analysis and laid out her thesis to buy the dip on snowflake this is a while ago she told me currently spear still likes snowflake and has doubled its position let me share her analysis she called out two drivers for the downside interest rates you know rising of course in snowflakes guidance which my own publication called weak in that previous chart that i just showed you so let's dig into that a bit snowflake guided for product revenues of 67 year on year which was below buy side expectations but i believe within sell side consensus regardless the guide was nuanced and driven by snowflake's decision to pass along price efficiencies to customers from optimizing processor price performance predominantly from aws's graviton too this is going to hit snowflakes revenue a net of about a hundred million dollars this year but the timing's not precise because it's going to hit 165 million but they're going to make up 65 million in increased demand frank slootman on the earnings call made this very clear he said quote this is not philanthropy this stimulates demand classic slootman the point is spear and other bulls believe that this will result in a gain for snowflake over the medium term and we would agree price goes down roi gets better you throw more projects at snowflakes customers going to buy more snowflake and when that happens and it gives the company an advantage as they continue to build their moat it's a longer term bet on cloud and data which are good bets now some of this could also be competitive pressures there have been you know studies that are out there from competitors attacking snowflakes pricing and price performance and they make comparisons oracle's been pretty aggressive as have others but so far the company's customers continue to consume now at a very fast rate now on on this front what can we learn from microsoft that applies to snowflake that's the headline here from benzinga so the article quoted a wealth manager named josh brown talking about what happened to microsoft after the dot-com bubble burst and how they quadrupled earnings over the next decade and the stock went sideways suggesting the same thing could happen to snowflake now i'd like to make a couple of comments here first at the time microsoft was a 23 billion dollar company and it had a monopoly and was already highly profitable steve ballmer became the ceo of microsoft right after the dot-com bubble burst and he hugged onto windows for dear life and lived off of microsoft's pc software monopoly microsoft became an extremely profitable and remarkably uninteresting caretaker of a pc in on-prem software estate during balmer's tenure so i just don't see the comparison as relevant snowflake you know they're going to make struggle for other reasons but that one didn't really resonate with me what's interesting is this chart it poses the question do cloud and data markets behave differently it's a chart that shows aws growth rates over time and superimposes the revenue in the red in q1 2018 aws generated 5.4 billion dollars in revenue and that was growing at the time at nearly a 50 rate now that rate as you can see decelerated quite significantly as aws grew to a 50 billion dollar run rate company that down below where you see it bottoms now it makes sense right law of large numbers you can't keep growing that fast when you get that big well oops look what happened in 2021 aws's growth rate bottoms in the high 20s and then rockets back up to 40 this past quarter as aws surpasses a 70 billion dollar run rate so you have to ask is cloud different is data different is cloud data different or data cloud different let's put it in the snowflake parlance can cloud because of its consumption model and the speed of innovation and ecosystem depth and breadth enable snowflake to exhibit lots of variability in its growth rates versus a say progressive and somewhat linear decline as the company grows revenue which is what you would expect historically and part of the answer relates to its market size here's a chart we've shared before with some additions it's our version of snowflake's total available market they're tam which snowflake's version that that blue data cloud thing superimposed on the right it shows the various layers of market opportunity that we came up with that that snowflake and others we think have in front of them emerging from the disruption of legacy data lakes and data warehouses to what snowflake refers to as its data cloud we think about the data mesh concept and decentralized data architectures with domain ownership and data product and service builders as consistent with snowflake's data cloud vision where snowflake data stores are nodes they're just simply discoverable nodes on the mesh you could have you know data bricks data lakes you know s3 buckets on that mesh it doesn't matter they can be discovered they can be shared and of course they're governed in a federated model now in snowflake's model it's all inside the snowflake data cloud that's fine then you'll go to the out years it gets a little fuzzy you know from edge locations and ai inference it becomes massive and decision making occurs in real time where machines and machine data take over the world instead of you know clicks and keystrokes sounds out there but it's real and how exactly snowflake plays there at this point is unclear but one thing's for sure there'll be a lot of data and it's going to find its way into snowflake you know snowflake's not a real-time engine it's an analytical system it's moving into the realm of data science and you know we've talked about the need for you know semantic layer between those those two worlds of analytics and data science but expanding the scope further out we think that snowflake is a big role to play in this future and the future is massive okay check you got the big tam now as someone that looks at companies through a fundamentals prism you've got to look obviously at the markets in the tan which we just did but you also want to understand customers and it's not hard to find snowflake customers capital one disney micron alliance sainsbury sonos and hundreds of other companies i've talked to snowflake customers who have also been customers of oracle teradata ibm neteza vertica serious database practitioners and they tell me it's consistent soulflake is different they say it's simpler it's more agile it's less complicated to secure and it's disruptive to their traditional ways of doing data management now of course there are naysayers i've spoken to a number of analysts that feel snowflake is deficient in areas like workload management and course complex joins and it's too specialized in a world where we're seeing the convergence of analytics and transactional workloads our own david floyer believes that what oracle is doing with mysql heatwave is radically disruptive to many of the database architectures and blows away anything out there and he believes that snowflake and the likes of aws are going to have to respond now this the other criticism here is that snowflake is not architected for real-time inference where a lot of that edge activity is is going to happen it's a multi-hundred billion dollar market and so look snowflake has a ton of competition that's the other thing all the major cloud players have very capable and competitive database platforms even though they all partner with snowflake except oracle of course but companies like databricks and have garnered tons of vc other vc funded companies have raised billions of dollars to do this kind of elastic consumption based separate compute from storage stuff so you have to always keep an open mind and be aware of potential blind spots for these companies but to the criticisms i would say look snowflake they got there first and watch their ecosystem it's a real key to its continued success snowflake's not going to go it alone and it's going to use its ecosystem partners to expand its reach and accelerate the network effects and fill those gaps and it will acquire its stock is valuable so it should be doing that just as it did with streamlit a zero revenue company that it bought for 800 million dollars in stock and cash just recently streamlit is an open source python library that gets snowflake further deeper into that data science space that data brick space and look watch what snowflake is doing with snowpark it's an api library for processing data and building data intensive applications we've talked about snowflake essentially being becoming the super cloud and building this sort of path-like layer across clouds rather than trying to do it all themselves it seems snowflake is really staring at the api economy and building its ecosystem to plug those holes so let's come back to the customers here's a chart that shows snowflakes customer spending momentum or net score on the the top line that's the vertical axis and pervasiveness in the data or market share and that bottom brown line snowflake has unprecedented net scores and held them up for many many quarters as you can see here going back you know a couple years all leading to its expanded market penetration and measured as pervasiveness of so-called market share within the etr survey it's not like idc market share it's pervasiveness in the data set now i'll say this i don't see how this is sustainable i've been waiting for this to moderate i wouldn't be surprised to see snowflake come back to earth a little bit i think they'll clearly still be highly elevated based on the data that i've seen but but i could see in in one or more of the etr surveys this year this starting to moderate as they get they get big it's just it has to happen um but i would again expect them to have a high spending velocity score but i think we're going to see snowflake you know maybe porpoise a bit here meaning you know it moderates it comes back up it's just really hard to sustain this piece of momentum and higher train retain and scale without absorbing some some friction and some head woods that's going to slow you down but back to the aws growth example it's entirely possible that we could see a similar dynamic with snowflake that you saw with aws and you kind of see it with salesforce and servicenow very successful large entrenched entrenched companies and it's very possible that snowflake could pull back moderate and then accelerate that growth even though people are concerned about the moderated guidance of 80 percent growth yeah that's that's the new definition of tepid i guess i look i like to look at other some other metrics the one that really called you know my my my attention was the remaining performance obligations this last quarter rpo snowflakes is up to something like 2.6 billion and that is a forward-looking indicator of of future revenues so i want to i'd like to see that growing and it's growing at a fast pace so you're going to see some ups and downs with snowflake i have no doubt but i think things are still looking pretty solid for the company growth companies like snowflake and octa and z scalar those other ones that i mentioned earlier have probably been repriced and refactored by investors while there's always going to be market and of course geopolitical risk especially in these times fundamentals matter you've got huge market well capitalized you got a leadership position great products and strong customer adoption you also have a great team team is something else that we look for we haven't touched on that but i'll leave you with this thought everyone knows about frank slootman mike scarpelli and what they've accomplished in their years of working together that's why the stock you know in ipo was was so overvalued they had seen these guys do it before slootman just documented in all this in his book amp it up which gives great insight into the history of of that though you know that pair and and the teams that they've built the companies that they've built how he thinks about building companies and markets and and how you know total available markets super important but the whole philosophy and culture that that he's building in his management style but you got to wonder right how long is this guy going to keep going what keeps him motivated you know i asked him that one time here's what he said why i mean are you in this for the sport what's the story here uh actually that that's not a bad way of characterizing it i think i am in it uh you know for the sport uh you know the only way to become the best version of yourself is to be uh to be under the gun and uh you know every single day and that's that's certainly uh what we are it sort of has its own rewards building great products building great companies uh you know regardless of you know uh what the spoils may be uh it has its own rewards and i i it's hard for people like us to get off the field and uh you know hang it up so here we are so there you have it he's in it for the sport how great is that he loves building companies and that my opinion that's how frank slootman thinks about success it's not about money money's the byproduct of success as earl nightingale would say success is the progressive realization of a worthy ideal i love that quote building great companies building products that change the world changing people's lives with data and insights creating jobs creating life-altering wealth opportunities not for himself but for thousands of employees and partners i'd say that's a pretty worthy ideal and i hope frank slootman sticks with it for a while okay that's it for today thanks to stephanie chan for the background research she does for breaking analysis alex meyerson on production kristen martin and cheryl knight on social with rob hoff on siliconangle and thanks to ivana delevska of spear invest and my friend chip symington for the angles from the money side of things remember all these episodes are available as podcasts just search breaking analysis podcast i publish weekly on wikibon.com and siliconangle.com and don't forget to check out etr.plus for all the survey data you can reach me at devolante or david.velante siliconangle.com and this is dave vellante for cube insights powered by etrbsafe stay well and we'll see you next time [Music] you

(upbeat music) >> Hi, everyone, welcome back to theCUBE's coverage of AWS re:Invent 2021. We're wrapping up four days of coverage, two sets. Two remote sets, one in Boston, one in Palo Alto. And really, it's a pleasure to introduce Benoit Dageville. He's the Press Co-founder of Snowflake and President of Products. Benoit, thanks for taking some time out and coming to theCUBE. >> Yeah, thank you for having me, Dave. >> You know, it's really a pleasure. We've been watching Snowflake since, maybe not 2012, but mid last decade you hit our radar. We said, "Wow, this company is going to go places." And yeah, we made that call correctly. But it's been a pleasure to sort of follow you. We've talked a little bit remotely. I kind of want to go back to some of the fundamentals. First of all, I wanted mention your earnings last night. If you guys didn't see it, again, triple digit growth, $1.8 billion RPO, cashflow actually looking pretty good. So, pretty amazing. Oh, and 173% NRR, you know, wow. And Mike Scarpelli is kind of bummed that you did so well. And I know why, right? Because it's going to be at some point, and he dials it down for the expectations and Wall Street says, "Oh, he's sandbagging." And then at some point you're actually going to meet expectations and people are going to go, "Oh, they met expectations." But anyway, he's a smart guy, he know what he's doing. (Benoit laughing) I loved it, it was so funny listening to him last night. But anyway, I want to go back to, when I talked to practitioners about data warehousing pre-cloud, they would say sound bites like, it's like a snake swallowing a basketball, they would tell me. And the other thing they said, "We just chased the chips. Every time a new Intel chip comes out, we have to bring in new servers, and we're struggling." The cloud changed all that. Your vision and Terry's vision changed all that. Maybe go back to the fundamentals of what you saw. >> Yeah, we really wanted to address what we call the data challenges. And if you remember at that time, data challenge was first of the volume of data, machine-generated data. So it was way more than just structured data, right? Machine-generated data is weblogs, and it's at petabyte scale. And there was no good solution for that type of data. Big data was not a great solution, Hadoop was really bad. And there was no good solution for that. So we thought we should do something for big data. The other aspect was concurrency, right? Everyone wants to use these data analytic platform in an enterprise, right? And you have more and more workload running against the same data, and the systems that were built were not scaling for these workloads. So you had to silo data, right? That's the only way big enterprise could deal with that, is to create many different silos, Oracle, Teradata, data mass, you would hear data mass. All of it was to afloat, right, this data? And then there was the, what do we call, data sharing. How to get access to data which is not born inside the enterprise, right? So with Terry, we wanted to solve all these challenges and we thought the only way to solve it was the cloud. And the cloud has really two free aspects. One is the elasticity, for all of a sudden, you can run every workload that you want concurrently, in parallel, on different computer resources, and you can run them against the same data. So this is kind of the data lake model, if you want. At the same time, you can, in the cloud, create a service. So you can remove complexity from users and make it really easy for new workloads to be added to the system, because you can manage, you can create a managed service, where all the sudden our customers, they don't need to manage infrastructure, they don't need to patch, they don't need to tune. Everything is done by Snowflake, the service, and they can just load in and run their query. And the third aspect is really collaboration. Is how to connect data sets together. And that's almost a new product for Snowflake, this data sharing. So we really at Snowflake was all about combining big data and data warehouse in one system in the cloud, and have only one single system where you can put all your data and all your workload. >> So you weren't necessarily trying to solve the data warehouse problem, you were trying to solve a data problem. And then it just so happened data warehouse was a logical entry point for you. >> It's really not that. Yes, we wanted to solve the data problem. And for us big data was a really important problem to solve. So from day one, Snowflake was all about machine generated data, petabyte scale, but we wanted to do it right. And for us, right was not compromising on data warehouse principle, which is a CDT of transaction, which is really fast response time, and which is also simplicity. So as I said, we wanted to solve kind of all the problems at the time of volume of data, concurrency, and these sharing aspects. >> This was 2012. You knew at that time that Hadoop wasn't going to be the answer. >> No, I mean, we were really, I mean, everyone knew that. Everyone knew Hadoop was really bad. You know, complex to manage, really slow. It had good aspects, right? This was the only system that could manage petabyte scale data sets. That's the only thing- >> Cheaply. >> Yeah, and cheaply which was good. And we wanted really to do that, plus have all the good attributes of data warehouse system. And at the same time, we wanted to build a system where if you are data warehouse customer, if you are coming from Teradata, you can migrate to Snowflake and you will get to a system which is faster than what you had on-premise, right. That's why it's pretty cool. So we wanted to do big data without compromising on data warehouse. >> So several years ago we looked at the hyperscalers and said, "Wow, last year they spent $100 billion in CapEx." And so, we started to think about this abstraction layer. And then we saw what you guys announced with the data cloud. We call it super clouds. And we see that as exactly what you're building. So that's clearly not just a data warehouse or database, it's technology that really hides the underlying complexity of all those clouds, and it allows you to have federated governance and data sharing, all those things. Can you talk about sort of how you think about that architecture? >> So for me, what I say is that really Snowflake is the worldwide web of data. And we are indeed a super cloud, or we are super-posed to the infrastructure cloud, which is our friends at Amazon, and of course, Azure, I mean, Microsoft and Google. And as any cloud, we have regions, Snowflake regions all over the world, and located on different cloud providers. At the same time, our platform is global in the sense that every region interconnects with all the other regions, this is our snow grid and data mesh, if you want. So that as an organization you can have your presence on several Snowflake region. It doesn't matter which cloud provider, so you can mix AWS with Azure. You can use our cloud like that. And indeed you can, this is a cloud where you can store your data, that's the thing that really matters, and data is structured, but it's machine structure, as I say, machine generated, petabyte scale, but there's also unstructured, right? We have added support for images, text, videos, where you can process this data in our system, and that's the workload spout. And workload, what is very important is that you can run this workload, any number of workloads. So the number of workloads is effectively unlimited with Snowflake because each workload can have its dedicated set of compute resources all operating on the same data set. And the type of workloads is also very important. It's not only about dashboards and data warehouse, it's data engineering, it's data science, it's building application. We have many of our customers who are building full-scale cloud applications on top of Snowflake. >> Yeah so the other thing, if you're not familiar with Snowflake, I don't know, maybe your head has been in the sand for a while, but separating compute and storage, I don't know if you were the first, but you were certainly the first to popularize it. And that allowed you to solve that chasing the chips problem and the swallowing the basketball, right? Because you have virtually infinite resources now at your disposal. >> Yeah, this is really the concurrency challenge that I was mentioning. Everyone wants to access the data. And of course, if everyone runs on the same set of compute resources, you have a bottleneck. So Snowflake was really about this multi-workload. We call it Multi-Cluster Shared Data Architecture. But it's not difficult to run multiple cluster if you don't have consistency of data. So how to do that while maintaining transactional property of data as CDT, right? You cannot modify data from different clusters. And when you commit, every other cluster will immediately see the change, right, as if everyone was running on the same cluster. So that was the challenge that we solve when we started Snowflake. >> Used the term data mesh. What is data mesh to Snowflake? Is it a concept, is it fabric? >> No, it's a very interesting point. As much as we like to centralize data, this becomes a bottleneck, right? When you are a large organization with different independent units, everyone wants to manage their own data and they have domain-specific expertise about that data. So having it centralized in IT is not practical. At the same time, you really want to be able to connect these different data sets together and join different data together, right? So that's the data mesh architecture. Each data set is managed independently by business owners, and then there is a contract which is exposed to others, and you can combine. And Snowflake architectures with data sharing, right. Data sharing that can happen within an organization, or across organization, allows you to connect any data with any other data on our platform. >> Yeah, so when I first heard that term, you guys using the term data mesh, I got very excited because it was kind of the data mesh is, my view, anyway, is going to be the fundamental architecture of this decade and beyond. And the principles, if I understand it correctly, you're applying the principles of Jim Octagon's data mesh within Snowflake. So decentralized data doesn't have to be physically in one place. Logically it's in the data cloud. >> It's logically decentralized, right? It's independently managed, and the reason, right, is the data that you need to use is not produced by your, even if in your company you want to centralize the data and having only one organization, let's say IT managing that, let's say, pretend. Yet you need to connect with other datasets, which is managed by other organizations. So by nature, the data that you use cannot be centralized, right? So now that you have this principle, if you have a platform where you can store all the data, wherever it is, and you can connect these data very seamlessly, then we can use that platform for your enterprise, right? To have different business units independently manage their data sets, connects these together so that as a company you have a 360 view of your customers, for example. But you can expand that outside of your enterprise and connect with data sets, which are from your vertical, for example, financial data set that you don't have in your company, or any public data set. >> And the other key principles, I think, that you've touched on really is the line of business now. Increasingly they're building data products that are creating value, and then also there's a self-service component. Assuming there's the fourth principle, governance. You got to have federated governance. And it seems like you've kind of ticked the boxes, more than tick the boxes, but engineered a solution to solve for those. >> No, it's very true. So Snowflake was really built to be really simple to use. And you're right. Our vision was, it would be more than IT, right? Who is going to use Snowflake is going now to be business unit, because you do not have to manage infrastructure. You do not have to patch. You do not have to do these things that business cannot do. You just have to load your data and run your queries, and run your applications. So now business can directly use Snowflake and create value from that. And yes, you're right, then connect that data with other data sets and to get maximum insights. >> Can you please talk about some of the things you do with AWS here at the event. I'm interested in what you're doing with your machine learning initiatives that you've recently announced, the AI piece. >> Yes, so one key aspects is data is not only about SQL, right? We started with SQL, but we expanded our platform to what we call data programmability, which is really about running program at scale across a large volume of data. And this was made popular with a programming model which was introduced by Pendal, DataFrames. Later taken by Spark, and now we have DataFrames in Snowflake, Where we are different than other systems, is that these DataFrame programs, which are in Python, or Java, or Scala, you program with data. These DataFrames are compiled to our single execution platforms. So we have one single execution platform, which is a data flow execution platform, which can run both SQL very efficiently, as I said, data warehouse speed, and also these very complex programs running Python and Java against this data. And this is a single platform. You don't need to use two different systems. >> Now so, you kind of really attack the traditional analytics base. People said, "Wow, Snowflake's really easy." Now you're injecting AI and machine intelligence. I see Databricks coming at it from the other angle. They started with machine learning, now they're sort of going after the analytics. Does there need to be a semantic layer to connect, 'cause it's the same raw data. Does there need to be a semantic layer to connect those two worlds? >> Yes, and that's what we are doing in our platform. And that's very novel to Snowflake. As I said, you interact with data in different program. You pick your program. You are a SQL programmer, use SQL. You are a Python programmer, use DataFrames with Python. It doesn't really matter. And then the semantic layer is our compiler and our processing engine, is going to translate both your program and my program in Python, your program in SQL, to the same execution platform and to the same programming language that Snowflake internally, we don't expose our programming language, but it's a data flow programming language that our execution platform executes. So at the end, we might execute exactly the same program, potentially. And that's very important because we spent all our IP and all our time, engineering time to optimize this platform, to make it the fastest platform. And we want to use that platform for any type of workloads, whether it's data programs or SQL. >> Now, you and Terry were at Oracle, so you know a lot about bench marketing. As Larry would stand up and say, "We killed the competition." You guys are probably behind it, right. So you know all about that. >> We are very behind it. >> So you know a lot about that. I've had some experience, I'm not a technologist, but I'm an observer and analyst. You have to take benchmarking with a very big grain of salt. So you guys have generally stayed away from that. Databricks came out and they came up with all these benchmarks. So you had to respond, because otherwise it's out there. Now you reran the benchmarks, you took out the materialized views and all the expensive stuff that they included in your cost, your price performance, but then you wrote, I thought, a very cogent blog. Maybe you could talk about sort of why you did that and your general philosophy around bench marketing. >> Yeah, from day one, with Terry we say never again we will participate in this really stupid benchmark war, because it's really not in the interest of customers. And we have been really at the frontline of that war with Terry, both of us, really doing special tricks, right? And optimizing this query to death, this query that no one runs apart from the synthetic benchmark. We optimize them to death to have the best number when we were at Oracle. And we decided that this is really not helping customers in the end. So we said, with Snowflake, we'll not do that. And actually, we are not the only one not to do that. If you look at who has published TPC-DS, you will see no one, none of the big vendors. It's not because they cannot run TPC-DS, Oracle can run it, I know that. And all the other big data warehouse vendor can, but it's something of a little bit of past. And TPC was really important at some point, and is not really relevant now. So we are not going to compete. And that's what we said is basically now our blog. We are not interesting in participating in this war. We want to invest our engineering effort and our IP in solving real world issues and performance issues that we have. And we want to improve our engine for these real world customers. And the nice thing with Snowflake, because it's a service, we see exactly all the queries that our customers are executing. So we know where we are struggling as a system, and that's where we want to invest and we want to improve. And if you look at many announcements that we made, it's all about under-the-cover improving Snowflake and getting the benefit of this improvement to our customer. So that was the message of that blog. And yes, the message was okay. Mr. Databricks, it's nice, and it's perfect that, I mean, everyone makes a decision, right? We made the decision not to participate. Databricks made another decision, which is very fine, and that's fine that they publish their number on their system. Where it is not fine is that they published number using Snowflake and misrepresenting our performance. And that's what we wanted also to correct. >> Yeah, well, thank you for going into that. I know it's, look, leaders don't necessarily have to get involved in that mudslide. (crosstalk) Enough said about that, so that's cool. I want to ask you, I interviewed Frank last spring, right after the lockdown, he was kind enough to come on virtually, and I asked him about on-prem. And he was, you know Frank, he doesn't mix words, He said, "We're not getting into a halfway house. That's not going to happen." And of course, you really can't do what you do on-prem. You can't separate compute, some have tried, but it's not the same. But at the same time that you see like Andreessen comes out with this blog that says a huge portion of your cost of goods sold is going to be the cloud, so you're going to have to repatriate. Help me square that circle. Is it cloud forever? Is it will you never say never? What can you share of that? >> I will never say never, it's not my style. I always say you can always change your mind, and maybe different factors can change your mind. What was true at some point might not be true at a later point. But as of now, I don't see any reason for us to go on-premise. As you mentioned at the beginning, right, Snowflake is growing like crazy. The world is moving to the cloud. I think maybe it goes both ways, but I would say 90% or 99% of the world is moving to the cloud. Maybe 1% is coming back for some very specific reasons. I don't think that the world is going to move back on-premise. So in the end we might miss a small percentage of the workload that will stay on-premise and that's okay. >> And as well, if you dig into some of the financial statements you'll see, read the notes where you've renegotiated, right? We're talking big numbers. Hundreds and hundreds of millions of dollars of cost reduction, actually more, over a 10 year period. Billions of your cloud bills. So the cloud suppliers, they don't want to lose you as a customer, right? You're one of their biggest customer. So it's awesome. Last question is kind of, your work now is to really drive the data cloud, get adoption up, build that supercloud, we call it. Maybe you could talk a little bit about how you see the future. >> The future is really broadened, the scope of Snowflake, and really, I would say the marketplace, and data sharing, and services, which are directly built natively on Snowflake and are shared through our platform, and can operate, it can mix data on provider-side with data on consumer-side, and creating this collaboration within the Snowflake data cloud, I think is really the future. And we are really only scratching the surface of that. And you can see the enthusiasm of Snowflake data cloud and vertical industry We have nuanced the final show data cloud. Industry, complete vertical industry, latching on that concept and collaborating via Snowflake, which was not possible before. And I think you talked about machine learning, for example. Machine learning, collaboration through machine learning, the ones who are building this advanced model might not be the same as the one who are consuming this model, right? It might be this collaboration between expertise and consumer of that expertise. So we are really at the beginning of this interconnected world. And to me the world wide web of data that we are creating is really going to be amazing. And it's all about connecting. >> And I'm glad you mentioned the ecosystem. I didn't give enough attention to that. Because as a cloud provider, which essentially you are, you've got to have a strong ecosystem. That's a hallmark of cloud. And then the other, vertical, that we didn't touch on, is media and entertainment. A lot of direct-to-consumer. I think healthcare is going to be a huge vertical for you guys. All right we got to go, Terry. Thanks so much for coming on "theCUBE." I really appreciate you. >> Thanks, Dave. >> And thank you for watching. This a wrap from AWS re:Invent 2021. "theCUBE," the leader in global tech coverage. We'll see you next time. (upbeat music)

Upbeat Music >> From the Bellagio Hotel in Las Vegas, it's theCUBE. Covering UiPath FORWARD IV. Brought to you by UiPath. >> Live, from Las Vegas, it's theCUBE at UiPath Forward IV. Lisa Martin here with Dave Vellante. Day 2 of our coverage. We've been getting a lot of really great perspectives on automation and how it is impacting, significantly, every industry. We're pleased to have, from the keynote stage, Junaid Amed, the corporate Vice President of Finance at Applied Materials. He's going to talk us through why you have a why-can't-we-automate-it-all attitude. Junaid, welcome to the program. >> Thank you so much. Pleasure to be here. >> So you have a really aggressive strategy for digital transformation automation led digital transformation. Your keynote this morning was great. It was, I just thought, strategically, it was so well thought out. And then, when you got up here before we went live, you started talking about how fast the time frame was. >> Yes. >> Give the audience an overview of the strategy, what you're aiming to do and how quickly you're expecting to see change. >> Yeah, absolutely. So when we set out, when we launched about two and a half years ago, the company had doubled in size the prior five years. We were looking for it to double again. We were honest with ourselves, with the CFO and the finance leadership team, could we support the new wave of growth? And the answer is no. Okay, what do we do? We knew we had to do something, not just more things but take a complete new view on things. That's how this whole initiative got incubated. And we took a bold approach. We said, we don't want just to cover the next five years, let's cover the next 20 years. Set ourselves up to make sure we do this right for the company and for our people. So, we basically set some very ambitious goals. Which is, the key KPI that we set at our true north is, we're going to get 50 % of finance work effort, all oriented around decision support. That's what helps move the needle for the company. Sure, we have our responsibilities to close the books, to do all the transactional stuff, to do all the reporting stuff. We will do that. But that can't be the mainstay anymore. That's just table stakes. And the business is screaming for this. It's just that we didn't have the levers and the tools to be able to do it. To pivot. But given the technological advancements, we said, "This is possible now." And that's- >> I think we have to set the table here with your industry. Because you started your journey to PA automation in 2019. >> Yes. >> You participate in one of the most challenging, if not the most challenging, industry on the planet. >> Junaid: Hundred percent. >> Everybody, I don't know, maybe not the insiders but everybody else missed, absolutely no, the insiders missed it too. What was the impact of the pandemic, right? And now, chips are every part of our lives. We've got this massive chip shortage. And you know, Wall Street missed it. They said, "Oh, sell Applied Materials. Sell every semiconductor company." And then they realized, "Oh wow," kind of late into the cycle, that this is like a multi-year, perhaps a decade long transition to, maybe this never ending demand, who knows? So that's the backdrop of your business. That was driving it. What was it like inside your company? >> So Dave, you know, what we could see, obviously we couldn't predict the pandemic. We could see long term growth, right? Really tangible market inflection on the back of AI big data. If you want to say where we made a big bet as a company? We went all in on AI. Right? We believed in that growth, at a time when I think not everyone was so convinced. Okay, is this going to be- How strong is this going to hit us? So, we had the benefit of going all in on AI and saying this is another big computing wave. The next big wave of computing. Coming off of mobile and social media. And Gary Dickerson, our CEO, bet the company that we're going to enable this growth. This is real. This is going to touch the whole global economy. So yes, that's a bet, a successful bet, the company made. No one could foresee what would the pandemic do but we had the good fortune of saying we were reacting to the growth, that we were committed to service. And we knew we had to get ahead of it. So we quickly organized and got finance, our organization well positioned to successfully support the company. Now, we got hit with the pandemic. Luckily for us, we're proactive and then, you know what we did? We accelerated. >> So your move to automation was an offensive move- >> Junaid: Hundred percent. >> Not a panic move to respond to a pandemic. >> Hundred percent. What do investors want? Operating leverage. Operating leverage. >> Yeah. >> Okay. And then, right now all the models have a certain baseline. Size of company, complexity. Okay, you need a certain amount of leverage coming out of this model. The models are going to change. Those that don't change ahead of the models, they're going to play catch up. It's not a fun ride. We wanted to be ahead. >> Well, I mean, talk about operating leverage. You're a company with what? 120+ Billion dollar market cap. You've got a 20+ Billion dollar revenue and you sell extremely expensive equipment. >> Extremely. >> And then a 5X revenue multiple. That's a trailing revenue multiple. I mean that's, that's impressive. That's operating leverage. >> Yes and but the bar keeps moving. You've got to stay ahead, right? You've got to be a leader. We're a leader. We've been a leader for five decades. It's the leadership mindset, I would say, in the company and our leadership team, that really propelled us towards this. The leadership of our CFO, Dan Durn, who invested. He made a bet. No one, you know, now we're sitting here, over almost 300,000 hours automated. We didn't have the playbook when we did it. >> You created the playbook. >> We created the playbook. >> Talk to me about the appetite, because obviously aggressive leadership, bold leadership, talk to me about the appetite to be able to be able to transform so quickly. Such that when, as Dave said, you're on the offensive, such that when the pandemic came, you leveraged that as an accelerator of what you've already been doing. Because culturally, that's challenging for folks to get on board to. How did you do that? >> I have to say, it is challenging. And it's at time's it feels counter-intuitive. We were going through the pandemic. We were having a large M&A integration happening, okay and we're transforming finance. And we're a resource constrained organization. Then you tell your people, "We've got more work to do. Transformation." And you're like, "Is that the right thing to do? Isn't everyone going to leave?" But when you dig deep, you say, "How do you get mind share?" How do you, first of all, you have to get people to see the value and then you have to make sure you do it fast enough, where they want to stick around. It's counter-intuitive. "Hey, we're going to launch this new platform. It's going to take three and half years. All right everyone, we're going to do this." What happens? People are like, in-out. Okay yeah, it'll come, we'll deal with it. Then instead, you say, "Hey, we're going to transform the way we plan. Completely. Top to bottom. 10 months. We're going to do it. Here's what you're going to be at your hands- Here's what you're going to have at your disposal in 10 months, all right? Oh, by the way, we're just showing you the high level. You get to really design. What do you want?" Now, when you have credibility, street cred with your organization, and you come out and say, "I'm going to give you top to bottom agility around forecasting and you get to have input on what you really want." Now people get excited. Like, "Oh, I'm going to work 25% more but wait a second, I'm really excited about what I get at the end of 10 months." >> So, the world was betting several years ago on the consolidation of fabs. "Oh, that's bad for Applied Materials." The exact opposite happened. You know, ARM changed the model, WAYFA volume's going through the roof. Now Intel is basically following that playbook, which is wonderful, they're breaking ground in Arizona. Which is, you have these massive tailwinds behind you. So I'm interested in how you forecast that and what role automation plays in that forecasting. >> Well, if you think about it, the fundamental demand isn't changing. Capacity has to go in. People think, wait a second, so and so is going to build less or whatever, The capacity, maybe geographically, is going to get dispersed out but it still has to go in. So I think it doesn't change the fundamental demand statement. Then, how does automation play into- I just thing that the fundamental nature and pace of business is changing. For us. And our customers are going through the same. So we have to be more reactive, we have to be able to respond to their needs. That whole thing cascades down into the organization. All the way deep into finance analyst forecasting, right? So, if everyone has to work off a weekly, monthly, quarterly cadence, you're too slow. Too late. Doesn't matter how good your plan is. It's old. It's stale. We're moving into a time and era where everything happens realtime. It always happened realtime but we just never had the tools to react realtime. Now, we have realtime business performance, enterprise grade dashboards. Any minute of the day you can see what the revenue forecast is, what the margin associated with that is. Yes, when we get into the official commit cycle everything firms up but it's not the big crank, right? You're fine tuning the knobs now. Which is great. What do you want in a plan? You want greater optionality. Is there a perfect plan? Of course there isn't. What is the North Star of forecasting? Give me as much options as- viable options and then let me decide. Because there's trade-offs. There's no one perfect plan. But you were limited. It just took too long to put a plan together. So you had very small degrees of freedom around it. Viable plans. We're changing all of that. >> This might be out of your swim lane but you had a slide up today and it had the IT in the middle- >> Yes. >> So technology's fundamental. And then, you had the elephant. The Hadoop elephant in the room. So I have to ask you, you guys announced this thing earlier this year called AI to the power of X, actionable insights. I remember reading about it, it's like you're collecting data across all the estate. So I'm like, wow this is a data company. Becoming a data company. So we've been talking a lot and of course the CFO purview is the reporting and I get that. The close, daily close, virtual close, all that. But then there's this whole line-of-business data play. >> Yes. >> And I'm wondering how automation fits there. I mean, that's got to be part of the vision. >> Yeah. Now, I can't speak to the capabilities you're talking to but we are leveraging some of that infrastructure, right? We have amazing IT organization. I have to say, we within Applied, we're a latecomer. From a product, customer product standpoint, already there is so much AI work being done. So we had the benefit of leveraging some of their capabilities for finance, when we launched Agile Finance. There is a lot going on over there. I think we actually enhanced that by introducing these RPA capabilities. And we did so from partnering with, I wouldn't say partnering, IT co-piloted this with us. Fundamentally co-piloted this, okay. And now, IT is taking it to other organizations. And they're taking it to product, they're taking it to operation, they're taking it to sales. So it will have a role. Hundred percent. But they're obviously starting, over the past three to six months is when they got started. So the answer is yes, for sure but I can't speak to exactly how it plays into that specific technology. >> But you addressed the dynamic. Which is, it started in a quick wind part of the company, finance. >> Yes. >> Which is logical. That's where I first introduced RPA a decade ago. A CFO conference, right? Then that now applies to the rest of the business. They're talking about operating leverage- >> Fundamental. Yeah. Hundred percent. >> How do you get that buy-in? How do you get finance and how do you get IT to work with finance, such that IT becomes a catalyst in all these downstream reactions to get this going across the company? >> Important question. >> Well they work for you. >> They don't. >> Oh they don't. >> They don't work for us. They work for me. I'm a customer of theirs. >> Okay. >> The first person that I needed to convince that we were serious and we're going to do it is the CIO. Okay, so you ask how do you get IT bought in? Well first thing, you have to get them in the tent. This is not about, "Oh, can you go do this for me? I need this from you. Can you do that?" Too slow, okay? This RPA, especially RPA, fundamentally, is such a, it's a technology that really needs to get embedded throughout the IT operating model. So you really need IT co-piloting this with you. This is how we did it. We said we're going to learn together. This is a must have for finance. We believe strongly this is going to become a must have for the enterprise but we're going to make the investment. In that must have for the enterprise, IT has to play the roll, right? So we started this together and we learned together and they've been fundamental in our being able to get to scale in 12 months. >> How do you federate governance? Who in the organization, what part of the organization owns governance, if you will? >> Yeah. So we created, established an RPA COE. They own the governance, the policies, the processes. Then, obviously there's a role to play for the business side. So we finance a business organization to them and there's roles to play. We actually, like I showed today in the presentation, there's multiple other players across the enterprise that have to vet these automations, right? Especially in finance. We have to be SOX compliant, we have to be data privacy compliant. We set all of those processes up. So, multiple parties have to engage but engage in an efficient way. >> We're seeing the CFO role emerge. I think of you as a CFO. I mean, I just use that umbrella, emerge as an innovator. I see this all of the place now, especially in Silicon Valley. You look at a company like Snowflake, I don't know if you know Mike Scarpelli but he kind of changed the world of software in some ways. So you're seeing very innovative CFOs emerge, that are technology savvy, they understand the operating leverage, we've used that term several times today, that you can get out of technology. It just reminds me, I don't know how long ago it was when Nick Carr wrote the book Does IT Matter. It seems like technology has never been more important. Along with people and process, of course, but in terms of creating that operating leverage, it's really a key part of the equation, the playbook going forward. >> I think it is a mindset change. We're trying to drive mindset change, right? But it's also, I think, come about because I think technology has become more friendly to non IT people. I think that's a fundamental driver. All these SaaS platforms in the market place, right? What did they design for? Business users. Of course IT has a very prominent role in that whole process and supporting it and implementing it. But the target audience is business users. What was the target audience for ERP? IT. Okay. Fundamental, the technology is changing by design and you're seeing now the impact of that. Where, "Hey wait, I can do this. I can do this by myself." Okay. IT always has been and will be a very important partner. They will service your data needs. This is how we're setting up the collaboration, right? But we really want the finance users to be able to iterate, model, analyze on the fly, in the moment. And they need to do it alone. >> Self serve, yeah. >> That's it. >> Self serve in realtime. I think one of the things, you mentioned it this morning, you mentioned it on our program and one of the things we've learned in the pandemic, that realtime and access to realtime data is no longer a nice-to-have. >> Yes. >> It's really a business critical element of any industry. >> Hundred percent. >> When do you think you'll put crypto on your balance sheet? I ask all the CFOs. >> He's been asking everyone that. >> There's an easy answer. I'm not authorized to answer. Above my pay grade. >> That's a good answer. >> That's good. >> Junaid, thank you so much for joining us. Talking to us about the transformation at Applied Materials, how you're partnering with UiPath to achieve that and the aggressive strategy that you've set out and congratulations on the success of it. We'll look forward to see what's going on in the next couple years. >> Great story. >> Of course. Thank you very much. Thank you for having me. >> Our pleasure. For Dave Vellante in Las Vegas, I'm Lisa Martin. You're watching theCUBE at UiPath Forward IV. Day two of our coverage. Stick around, we'll be right back with our next guest. (upbeat music)

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 the dip has been been an effective strategy since the market bottomed in early march last year the approach has been especially successful in tech and even more so for those tech names that one were well positioned for the forced march to digital i sometimes call it i.e remote work online commerce data centric platforms and certain cyber security plays and two already had the cloud figured out the question on investors minds is where to go from here should you avoid some of the high flyers that are richly valued with eye-popping multiples or should you continue to buy the dip and if so which companies that capitalized on the trends from last year will see permanent shifts in spending patterns that make them a solid long-term play hello and welcome to this week's wikibon cube insights powered by etr in this breaking analysis we shine the spotlight on three companies that may be candidates for a buy the dip strategy and it's our pleasure to welcome in ivana delevco who's the chief investment officer and founder of spear alpha a new research-centric etf focused on industrial technology ivana is a long-time equity analyst with a background in both long and short investing ivana welcome to the program thanks so much for coming on thanks for having me david yeah it's really our pleasure i i want to start with your etf and give the folks a bit more background about you first you know we gotta let people know i'm not an investment pro i'm not an advisor i don't make stock recommendations i don't sell investments so you got to do your own research i have a lot of data so happy to share it but you got to understand your own risks you of course yvonne on the other hand you do offer investment services and so people before investing got to carefully review all the available available investment docs understand what you're getting into before you invest now with that out of the way ivana i have some stats up here on this slide your spear you're a newly launched female lead firm that does deep research into the supply chain we're going to talk about that you try to uncover as i understand it under-appreciated industrial tech firms and some really pretty cool areas that we list here but tell us a little bit more about your background and your etf so thanks for having me david my background is in industrial research and industrial technology investments i've spent the past 15 years covering this space and what we've seen over the past five years is technology changes that are really driving fundamental shifts in industrial manufacturing processes so whether this is 5g connectivity innovation in the software stack increasing compute speeds all of these are major technological advancements that are impacting uh traditional manufacturers so what we try to do is assess speak to these firms and assess who is at the leading and who is at the lagging end of this digital transformation and we're trying to assess what vendors they're using what processes they're implementing and that is how we generate most of our investment ideas okay great and and we show on the bottom of of this sort of intro slide if you will uh so one of the processes that you use and one of the things that that is notable a lot of people compare you uh to kathy woods are investments when you came out uh i think you use a different process i mean maybe there are some similarities in terms of disruption but at the bottom of this slide it shows a mckinsey sort of graphic that that i think informs people as to how you really dig into the supply chain from a research standpoint is that right absolutely so for us it's all about understanding the supply chain going deep in the supply chain and gather data points from primary sources that we can then translate into investment opportunities so if you look at this mckinsey graph uh you will see that there is a lot of opportunity to for these companies to transform themselves both on the front end which means better revenue better products and on their operation side which means lower cost whether it's through better operations or through better processes on the the back end so what we do is we will speak to a traditional manufacturing company and ask them okay well what do you use for better product development and they will give us the name of the firms and give us an assessment of what's the differences between the competitors why they like one versus the other so then we're gonna take the data and we will put it into our financial model and we'll understand the broader market for it um the addressable market the market share that the company has and will project the growth so for these higher growth stocks that that you cover the main alpha generation uh potential here is to understand what the amount of growth these companies will generate over the next 10 to 20 years so it's really all about projecting growth in the next three years in the next five years and where will growth ultimately settle in in the next 10 to 20 years love it we're gonna have a fun conversation because today we're going to get into your thesis for cooper snowflake and z scalar we're going to bring in some of our own data some of our data from etr and and why you think these companies may be candidates for long-term growth and and be buy the dip stock so to do that i hacked up this little comparison slide we're showing here i do this for context our audience knows i'm not a cfa or a valuation expert but we like to do simple comparisons just to give people context and a sense of relative size growth and valuation and so this chart attempts to do that so what i did is i took the most recent quarterly revenue for cooper snowflake and z scalar multiplied it by four to get a run rate we included servicenow in the table just for baseline reference because bill mcdermott as we've reported aspires to make service now the next great enterprise software company alongside with salesforce and oracle and some of the others and and all these companies that we list here that through the three here they aspire to do so in their own domain so we're displaying the market cap from friday morning september 10th we calculated a revenue run rate multiple and we show the quarterly revenue growth and what this data does is gives you a sense of the three companies they're well on their way to a billion dollars in revenue it underscores the relationship between revenue growth and valuation snowflake being the poster child for that dynamic savannah i know you do much more detailed financial analysis but let's talk about these companies in order maybe start with koopa they just crushed their quarter i mean they blew away consensus on the top line what else about the company do you like and why is it on your by the dip list so just to back up david on valuation these companies investors either directly or indirectly value on a dcf basis and what happened at the beginning of the year as interest rates started increasing people started freaking out and once you plug in 100 basis points higher interest rate in your dcf model you get significant price downside so that really drove a lot of the pullback at the beginning of the year right now where we stand today interest rates haven't really moved all that significantly off the bot of the bottom they're still around the same levels maybe a little bit higher but those are not the types of moves that are going to drive significant downside in this stock so as things have stabilized here a lot of these opportunities look pretty attractive on that basis so koopa specifically came out of our um if you go back to that uh the chart of like where the opportunities lie in um in across the manufacturing uh um enterprise koopa is really focused on business pen management so they're really trying to help companies reduce their cost uh and they're a leader in the space uh they're unique uh unique in that they're cloud-based so the feedback we've been hearing from from our companies that use it jetblue uses it train technologies uses it the feedback we've been hearing is that they love the ease of implementation so it's very easy to implement and it drives real savings um savings for these companies so we see in our dcf model we see multiple years of this 30 40 percent growth and that's really driving our price target yeah and we can i can confirm that i mean i mean just anecdotally you know you know we serve a lot of the technology community and many of our clients are saying hey okay you know when you go to do invoicing or whatever you work with procurement it's koopa you know this is some ariba that's kind of the legacy which is sap we'll talk about that a little later but let's talk about snowflake um you know snowflake we've been tracking them very closely we know the management there we've watched them through their last two companies now here and have been following that company early on since since really 2015. tell us why you like snowflake um and and maybe why you think it can continue its rapid growth thanks david so first of all i need to compliment you on your research on the company on the technology side so where we come in is more from understanding where our companies can use soft snowflake and where snowflake can add value so what we've been hearing from our companies is the challenge that they're facing is that everybody's moving to the cloud but it's not as simple as just send your data to the cloud and call aws and they're gonna generate more revenue for your solve your cost problem so what we've been hearing is that companies need to find tools that are easy to use where they can use their own domain expertise and just plug and play so um ansys is one of the companies we covered the dust simulation they've found snowflake to be an extremely useful tool in sales lead generation and within sales crm systems have been around for a while and they're they've really been implemented but analyzing sales numbers is something that is new to this company some some of our companies don't even know what their sales are even when they look back after the quarter is closed so tools like this help um companies do easy analytics and therefore drive revenue and cost savings growth so we see really big runway for for this company and i think the most misunderstood part about it is that people view it as a warehousing data warehousing play while this is all about compute and the company does a good job separating the two and what our their customers like or like the companies that we cover like about it is that it can lower their compute costs um and make it much easier much more easily manageable for them great and we're going to talk about more about each of these companies but let's talk about z-scaler a bit i mean z-scaler is a company we've been very excited about and identified them kind of early on they've definitely benefited from the move to cloud generally and specifically the remote work uh situation with the cyber threats etc but tell us why you like z-scaler so interestingly z-scaler um we like the broader security space um the broader cyber security space and interestingly our companies are not yet spending to the level that is commensurate with the increase in attack rate so we think this is a trend that is really going to accelerate as we go forward um my own board 20 of the time on the last board meeting was spent on cyber security what we're doing and this is a pretty simple operation that that we're running here so you can imagine for a large enterprise with thousands of people all around the world um needing to be on a single simple system z-scaler really fits well here very easy to implement several of our industrial companies use it siemens uses it ge uses it and they've had great great experience with it excellent i just want to take a quick look at how some of these names have performed over the last year and and what if anything this data tells us this is a chart comparing the past 12 months performance of of those four companies uh that we just talked about and we added in you know servicenow z scalar as you can see has outperformed the other despite your commentary on discounted cash flow snowflake is underperformed really precisely for the reasons that you mentioned not to mention the fact that it was pretty highly valued and you can see relative to the nas but it's creeping back lately after very strong earnings even though the stock dropped after it beat earnings because the street wants the cfo to say to guide even higher than maybe as mike scarpelli feels is prudent and you can see cooper has also underperformed relatively speaking i mean it absolutely destroyed consensus this week the stock went up but it's been off with the the weaker market this week i know you like to take a longer term view but but anything you would add here yeah so interestingly both z-scaler and koopa were in the camp of as we went into earnings expectations were already pretty high because few of their competitors reported very strong results so this scalar yesterday their revenue growth was was pretty strong the stock is down today uh and the reason is because people were kind of caught up a little bit in the noise of this quarter growth is 57 last quarter it was 60 like is this a deceleration we don't see it as that at all and the company brought up one point that i thought was extremely interesting which is as their deal sizes are getting larger it takes a little longer time for them to see the revenue come through so it takes a little bit of time to for you to see it into from billings into into revenue same thing with cooper very strong earnings report but i think expectations were already pretty high going into it uh given the service now and um and anna plan as well reported strong results so i think it's all about positioning so we love these setups where you can buy the deep in on this opportunity where like people get caught up in um short-term noise and and it creates good entry points excellent i i want to bring in some data from our partner etr and see if you have any comments ivana so what we're showing here is a two-dimensional chart we like to show this uh very frequently it's based on a survey of between a thousand and fifteen hundred chief information officers and technology buyers every quarter this is from their most recent july survey the vertical axis shows net score which is a measure of spending momentum i mean this it measures the net percentage of customers in the survey that are spending more on a particular product or platform in other words it essentially subtracts the percentage of customers spending less from those spending more which yields a net score it's more granular than that but basically that's what it does the horizontal axis is market share or pervasiveness in the data set it's not revenue market share like you get from idc it's it's a mention market share and now that red dotted line at the 40 percent mark on the vertical represents an elevated level in other words anything above 40 percent we consider notable and we've plotted our three by the dip companies and included some of their competitors for context and you can see we added salesforce servicenow and oracle and that orange ellipse because they're some of the bigger names in the software business so let's take these in alphabetical order ivana starting with koopa in the blue you can see we plotted them next to sap's ariba and you can see cooper has stronger spending momentum but not as much presence in the market so to me my influence is oh that's an opportunity for them to steal share more modern technology you know more facile and of course oracle has products in this space but the oracle dot includes all oracle products not just the procurement stuff but uh maybe your thoughts on this absolutely i love this chart i think that's your spot on this would be the same way i would interpret the chart where um increased spending momentum is is a sign of the company providing products that people like and we we expect to see cooper's share grow market share grow over time as well so let's come back to the chart and i want to i want to really point out the green ellipse this is the data zone if you will uh and we're like a broken record on this program with snowflake has performed unbelievably well in net score and spending momentum every quarter the dtr has captured enough end sample in its survey holding near or above 80 percent its net score consistently is has been up there and we've plotted data bricks in that zone it's been expected right that data bricks is going to do an ipo this year late last month company raised 1.6 billion in a private round so i guess that was either a strategy to delay the ipo or raise a bunch more cash and give late investors a low risk bite at the apple you know pre-ipo as we saw with snowflake last year what we didn't plot here are some of snowflake's biggest competitors ivana who also happen to be their partners most notably the big cloud players all who have their own database offerings aws microsoft and google now you've said snowflake is much more than a database company i wonder if you could add some color here yeah that's a very good point david uh basically the the driver of the thesis in snowflake is all about acceleration and spending and what we are seeing is the customers that are signed up on their platform today they're not even spending they're probably spending less than five percent of what they can ultimately spend on this product and the reason is because they don't yet know what the ultimate applications are for this right so you're gonna start with putting the data in a format you can use and you need to come up with use cases or how are you actually going to use this data so back to the example that i gave with answers the first use case that they found was trying to optimize leads there could be like 100 other use cases and they're coming up with with those on a daily basis so i would expect um this score to keep keep uh keep up pretty high or or go even higher as we as people figure out how they can use this product you know the buy-the-dip thesis on snowflake was great last quarter because the stock pulled back after they announced earnings and when we reported we said you know mike the the company see well cleveland research came out remember they got the dip on that and we looked at the data and we said mike scarpelli said that you know we're going to probably as a percentage of overall customers decelerate the net net new logos but we're going deeper into the customer base and that's exactly what's happening with with snowflake but okay let's bring up the slide again last but not least the z scaler we love z scalar we named z scaler in 2019 as an emerging four-star security company along with crowdstrike and octa and we said these three should be on your radar and as you see we've plotted z scalar with octa who with its it's its recent move into to converging identity and governance uh it gets kind of interesting uh we plotted them with palo alto as well another cyber security player that we've covered extensively we love octa in addition to z-scaler we great respect for palo alto and you'll note all of them are over that 40 percent line these are disruptors they're benefiting well not so much palo alto they're more legacy but the the other two are benefiting from that shift to work from home cloud security modern tech stack uh the acquisition that octa-made of of of auth0 and again z scalar cloud security getting rid of a lot of hardware uh really has a huge tailwind at its back if on a zscaler you know they've benefited from the huge my cloud migration trend what are your thoughts on the company so i actually love all three companies that are there right and the point is people are just going to spend more money whether you are on the cloud of the cloud the data centers need more security as well so i think there is a strong case to be made for all three with this scaler the upside is that it's just very easy to use very easy to implement and if you're somebody that is just setting up infrastructure on the cloud there is no reason for you to call any other competitor right with palo alto the case there is that if you have an established um security platfor if you're on their security platform the databa on the data center side uh they they did introduce through several acquisitions a pretty attractive cloud offering as well so they've been gaining share as well in the space and and the company does look pretty attractive on valiation basis so for us cyber security is really all about rising tide lifts all boats here right so you can have a pure play like this scaler uh that benefits from the cloud but even somebody like palo alto is pretty well positioned um to benefit yeah we think so too over a year ago we reported on the valuation divergence between palo alto and fortinet fortinet was doing a better job moving to the cloud and obviously serves more of a mid-market space palo alto had some go-to-market execution challenges we said at the time they're going to get through those and when we talk to chief information security officers palo alto is like the gold standard they're the thought leader they want to work with them but at the same time they also want to participate in some of these you know modern cloud stacks so i we agree there's plenty of room for all three um just to add a bit more color and drill into the spending data a little bit more this slide here takes that net score and shows the progression since january 2019 and you can see a snowflake just incredible in terms of its ability to maintain that elevated net score as we talked about and the table on the insert it shows you the number of responses and all three of these companies have been getting more mentions over time but snowflake and z scale are now both well over 100 n in the survey each quarter and the other notable piece here and this is really important you can see all three are coming out of the isolation economy with the spending uptick nice upticks shown in the most recent survey so that's again another positive but i want to close ivana with kind of making the bull and bear case and have you address really the risks to the buy the dip scenario so look there are a lot of reasons to like these companies we talked about them cooper they've got earnings momentum you know management on the call side had very strong end market demand this the stock you know has underperformed the nasdaq you know this year snowflake and zscaler they also have momentum snowflake get this enormous tam uh although they were punished for not putting a hard number on it which is ridiculous in my opinion i mean the thing is it's huge um the investors were just kind of you know wanting a little binky baby blanket but they all have modern tech in the cloud and really importantly this shows in the etr surveys you know the momentum that they have so very high retention is the other point i wanted to make the very very low churn of these companies however cooper's management despite the blowout quarter they gave kind of underwhelming guidance they've cited headwinds uh they've with the the the lamisoft uh migration to their cloud platform snowflake is kind of like price to perfection so maybe that's an advantage because every every little negative news is going to going to cause the company to dip but it's you know it's pretty high value because salutman and scarpelli everybody expects them to surpass what happened at servicenow which was a rocket ship and it could be all argued that all three are richly priced and overvalued so but ivana you're looking out as you said a couple of years three years maybe even five years how do you think about the potential downside risks in in your by the dip scenario you buy every dip you looking for bigger dips or what's your framework there so what we try to do is really look every quarter the company reports is there something that's driving fundamental change to the story or is it a one-off situation where people are just misunderstanding what the company is reporting so in the case we kind of addressed some of the earnings that that were reported but with koopa we think the man that management is guiding conservatively as they should so we're not very concerned about their ability to execute on on the guidance and and to exceed the guidance with snowflake price to perfection that's never a good idea to avoid a stock uh because it just shows that there is the company is doing a great job executing right so um we are looking for reports like the cleveland report where they would be like negative on the stock and that would be an entry point uh for us so broadly we apply by the deep philosophy but not not if something fundamentally changes in the story and none of these three are showing any signs of fundamental change okay we're going to leave it right there thanks to my guest today ivana tremendous having you would love to have you back great to see you thank you david and def you definitely want to check out sprx and the spear etf now remember i publish each week on wikibon.com and siliconangle.com these episodes they're all available as podcasts all you do is search breaking analysis podcasts you can always connect with me on twitter i'm at d vallante or email me at david.vellante at siliconangle.com love the comments on linkedin 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

(upbeat music) >> From theCUBE studios in Palo Alto, in Boston bringing you data-driven insights from theCUBE and ETR. This is braking analysis with Dave Vellante. >> Database is the heart of enterprise computing. The market is both exploding and it's evolving. The major force is transforming the space include Cloud and data, of course, but also new workloads, advanced memory and IO capabilities, new processor types, a massive push towards simplicity, new data sharing and governance models, and a spate of venture investment. Snowflake stands out as the gold standard for operational excellence and go to market execution. The company has attracted the attention of customers, investors, and competitors and everyone from entrenched players to upstarts once in the act. Hello everyone and welcome to this week's Wikibon CUBE Insights powered by ETR. In this breaking analysis, we'll share our most current thinking on the database marketplace and dig into Snowflake's execution. Some of its challenges and we'll take a look at how others are making moves to solve customer problems and try to get a piece of the growing database pie. Let's look at some of the factors that are driving market momentum. First, customers want lower license costs. They want simplicity. They want to avoid database sprawl. They want to run anywhere and manage new data types. These needs often are divergent and they pull vendors and technologies in different direction. It's really hard for any one platform to accommodate every customer need. The market is large and it's growing. Gardner has it at around 60 to 65 billion with a CAGR of somewhere around 20% over the next five years. But the market, as we know it is being redefined. Traditionally, databases have served two broad use cases, OLTP or transactions and reporting like data warehouses. But a diversity of workloads and new architectures and innovations have given rise to a number of new types of databases to accommodate all these diverse customer needs. Many billions have been spent over the last several years in venture money and it continues to pour in. Let me just give you some examples. Snowflake prior to its IPO, raised around 1.4 billion. Redis Labs has raised more than 1/2 billion dollars so far, Cockroach Labs, more than 350 million, Couchbase, 250 million, SingleStore formerly MemSQL, 238 million, Yellowbrick Data, 173 million. And if you stretch the definition of database a little bit to including low-code or no-code, Airtable has raised more than 600 million. And that's by no means a complete list. Now, why is all this investment happening? Well, in a large part, it's due to the TAM. The TAM is huge and it's growing and it's being redefined. Just how big is this market? Let's take a look at a chart that we've shown previously. We use this chart to Snowflakes TAM, and it focuses mainly on the analytics piece, but we'll use it here to really underscore the market potential. So the actual database TAM is larger than this, we think. Cloud and Cloud-native technologies have changed the way we think about databases. Virtually 100% of the database players that they're are in the market have pivoted to a Cloud first strategy. And many like Snowflake, they're pretty dogmatic and have a Cloud only strategy. Databases has historically been very difficult to manage, they're really sensitive to latency. So that means they require a lot of tuning. Cloud allows you to throw virtually infinite resources on demand and attack performance problems and scale very quickly, minimizing the complexity and tuning nuances. This idea, this layer of data as a service we think of it as a staple of digital transformation. Is this layer that's forming to support things like data sharing across ecosystems and the ability to build data products or data services. It's a fundamental value proposition of Snowflake and one of the most important aspects of its offering. Snowflake tracks a metric called edges, which are external connections in its data Cloud. And it claims that 15% of its total shared connections are edges and that's growing at 33% quarter on quarter. This notion of data sharing is changing the way people think about data. We use terms like data as an asset. This is the language of the 2010s. We don't share our assets with others, do we? No, we protect them, we secure or them, we even hide them. But we absolutely don't want to share those assets but we do want to share our data. I had a conversation recently with Forrester analyst, Michelle Goetz. And we both agreed we're going to scrub data as an asset from our phrasiology. Increasingly, people are looking at sharing as a way to create, as I said, data products or data services, which can be monetized. This is an underpinning of Zhamak Dehghani's concept of a data mesh, make data discoverable, shareable and securely governed so that we can build data products and data services that can be monetized. This is where the TAM just explodes and the market is redefining. And we think is in the hundreds of billions of dollars. Let's talk a little bit about the diversity of offerings in the marketplace. Again, databases used to be either transactional or analytic. The bottom lines and top lines. And this chart here describe those two but the types of databases, you can see the middle of mushrooms, just looking at this list, blockchain is of course a specialized type of database and it's also finding its way into other database platforms. Oracle is notable here. Document databases that support JSON and graph data stores that assist in visualizing data, inference from multiple different sources. That's is one of the ways in which adtech has taken off and been so effective. Key Value stores, log databases that are purpose-built, machine learning to enhance insights, spatial databases to help build the next generation of products, the next automobile, streaming databases to manage real time data flows and time series databases. We might've missed a few, let us know if you think we have, but this is a kind of pretty comprehensive list that is somewhat mind boggling when you think about it. And these unique requirements, they've spawned tons of innovation and companies. Here's a small subset on this logo slide. And this is by no means an exhaustive list, but you have these companies here which have been around forever like Oracle and IBM and Teradata and Microsoft, these are the kind of the tier one relational databases that have matured over the years. And they've got properties like atomicity, consistency, isolation, durability, what's known as ACID properties, ACID compliance. Some others that you may or may not be familiar with, Yellowbrick Data, we talked about them earlier. It's going after the best price, performance and analytics and optimizing to take advantage of both hybrid installations and the latest hardware innovations. SingleStore, as I said, formerly known as MemSQL is a very high end analytics and transaction database, supports mixed workloads, extremely high speeds. We're talking about trillions of rows per second that could be ingested in query. Couchbase with hybrid transactions and analytics, Redis Labs, open source, no SQL doing very well, as is Cockroach with distributed SQL, MariaDB with its managed MySQL, Mongo and document database has a lot of momentum, EDB, which supports open source Postgres. And if you stretch the definition a bit, Splunk, for log database, why not? ChaosSearch, really interesting startup that leaves data in S-3 and is going after simplifying the ELK stack, New Relic, they have a purpose-built database for application performance management and we probably could have even put Workday in the mix as it developed a specialized database for its apps. Of course, we can't forget about SAP with how not trying to pry customers off of Oracle. And then the big three Cloud players, AWS, Microsoft and Google with extremely large portfolios of database offerings. The spectrum of products in this space is very wide, with you've got AWS, which I think we're up to like 16 database offerings, all the way to Oracle, which has like one database to do everything not withstanding MySQL because it owns MySQL got that through the Sun Acquisition. And it recently, it made some innovations there around the heat wave announcement. But essentially Oracle is investing to make its database, Oracle database run any workload. While AWS takes the approach of the right tool for the right job and really focuses on the primitives for each database. A lot of ways to skin a cat in this enormous and strategic market. So let's take a look at the spending data for the names that make it into the ETR survey. Not everybody we just mentioned will be represented because they may not have quite the market presence of the ends in the survey, but ETR that capture a pretty nice mix of players. So this chart here, it's one of the favorite views that we like to share quite often. It shows the database players across the 1500 respondents in the ETR survey this past quarter and it measures their net score. That's spending momentum and is shown on the vertical axis and market share, which is the pervasiveness in the data set is on the horizontal axis. The Snowflake is notable because it's been hovering around 80% net score since the survey started picking them up. Anything above 40%, that red line there, is considered by us to be elevated. Microsoft and AWS, they also stand out because they have both market presence and they have spending velocity with their platforms. Oracle is very large but it doesn't have the spending momentum in the survey because nearly 30% of Oracle installations are spending less, whereas only 22% are spending more. Now as a caution, this survey doesn't measure dollar spent and Oracle will be skewed toward the big customers with big budgets. So you got to consider that caveat when evaluating this data. IBM is in a similar position although its market share is not keeping up with Oracle's. Google, they've got great tech especially with BigQuery and it has elevated momentum. So not a bad spot to be in although I'm sure it would like to be closer to AWS and Microsoft on the horizontal axis, so it's got some work to do there. And some of the others we mentioned earlier, like MemSQL, Couchbase. As shown MemSQL here, they're now SingleStore. Couchbase, Reddis, Mongo, MariaDB, all very solid scores on the vertical axis. Cloudera just announced that it was selling to private equity and that will hopefully give it some time to invest in this platform and get off the quarterly shot clock. MapR was acquired by HPE and it's part of HPE's Ezmeral platform, their data platform which doesn't yet have the market presence in the survey. Now, something that is interesting in looking at in Snowflakes earnings last quarter, is this laser focused on large customers. This is a hallmark of Frank Slootman and Mike Scarpelli who I know they don't have a playbook but they certainly know how to go whale hunting. So this chart isolates the data that we just showed you to the global 1000. Note that both AWS and Snowflake go up higher on the X-axis meaning large customers are spending at a faster rate for these two companies. The previous chart had an end of 161 for Snowflake, and a 77% net score. This chart shows the global 1000, in the end there for Snowflake is 48 accounts and the net score jumps to 85%. We're not going to show it here but when you isolate the ETR data, nice you can just cut it, when you isolate it on the fortune 1000, the end for Snowflake goes to 59 accounts in the data set and Snowflake jumps another 100 basis points in net score. When you cut the data by the fortune 500, the Snowflake N goes to 40 accounts and the net score jumps another 200 basis points to 88%. And when you isolate on the fortune 100 accounts is only 18 there but it's still 18, their net score jumps to 89%, almost 90%. So it's very strong confirmation that there's a proportional relationship between larger accounts and spending momentum in the ETR data set. So Snowflakes large account strategy appears to be working. And because we think Snowflake is sticky, this probably is a good sign for the future. Now we've been talking about net score, it's a key measure in the ETR data set, so we'd like to just quickly remind you what that is and use Snowflake as an example. This wheel chart shows the components of net score, that lime green is new adoptions. 29% of the customers in the ETR dataset that are new to Snowflake. That's pretty impressive. 50% of the customers are spending more, that's the forest green, 20% are flat, that's the gray, and only 1%, the pink, are spending less. And 0% zero or replacing Snowflake, no defections. What you do here to get net scores, you subtract the red from the green and you get a net score of 78%. Which is pretty sick and has been sick as in good sick and has been steady for many, many quarters. So that's how the net score methodology works. And remember, it typically takes Snowflake customers many months like six to nine months to start consuming it's services at the contracted rate. So those 29% new adoptions, they're not going to kick into high gear until next year, so that bodes well for future revenue. Now, it's worth taking a quick snapshot at Snowflakes most recent quarter, there's plenty of stuff out there that you can you can google and get a summary but let's just do a quick rundown. The company's product revenue run rate is now at 856 million they'll surpass $1 billion on a run rate basis this year. The growth is off the charts very high net revenue retention. We've explained that before with Snowflakes consumption pricing model, they have to account for retention differently than what a SaaS company. Snowflake added 27 net new $1 million accounts in the quarter and claims to have more than a hundred now. It also is just getting its act together overseas. Slootman says he's personally going to spend more time in Europe, given his belief, that the market is huge and they can disrupt it and of course he's from the continent. He was born there and lived there and gross margins expanded, do in a large part to renegotiation of its Cloud costs. Welcome back to that in a moment. Snowflake it's also moving from a product led growth company to one that's more focused on core industries. Interestingly media and entertainment is one of the largest along with financial services and it's several others. To me, this is really interesting because Disney's example that Snowflake often puts in front of its customers as a reference. And it seems to me to be a perfect example of using data and analytics to both target customers and also build so-called data products through data sharing. Snowflake has to grow its ecosystem to live up to its lofty expectations and indications are that large SIS are leaning in big time. Deloitte cross the $100 million in deal flow in the quarter. And the balance sheet's looking good. Thank you very much with $5 billion in cash. The snarks are going to focus on the losses, but this is all about growth. This is a growth story. It's about customer acquisition, it's about adoption, it's about loyalty and it's about lifetime value. Now, as I said at the IPO, and I always say this to young people, don't buy a stock at the IPO. There's probably almost always going to be better buying opportunities ahead. I'm not always right about that, but I often am. Here's a chart of Snowflake's performance since IPO. And I have to say, it's held up pretty well. It's trading above its first day close and as predicted there were better opportunities than day one but if you have to make a call from here. I mean, don't take my stock advice, do your research. Snowflake they're priced to perfection. So any disappointment is going to be met with selling. You saw that the day after they beat their earnings last quarter because their guidance in revenue growth,. Wasn't in the triple digits, it sort of moderated down to the 80% range. And they pointed, they pointed to a new storage compression feature that will lower customer costs and consequently, it's going to lower their revenue. I swear, I think that that before earnings calls, Scarpelli sits back he's okay, what kind of creative way can I introduce the dampen enthusiasm for the guidance. Now I'm not saying lower storage costs will translate into lower revenue for a period of time. But look at dropping storage prices, customers are always going to buy more, that's the way the storage market works. And stuff like did allude to that in all fairness. Let me introduce something that people in Silicon Valley are talking about, and that is the Cloud paradox for SaaS companies. And what is that? I was a clubhouse room with Martin Casado of Andreessen when I first heard about this. He wrote an article with Sarah Wang, calling it to question the merits of SaaS companies sticking with Cloud at scale. Now the basic premise is that for startups in early stages of growth, the Cloud is a no brainer for SaaS companies, but at scale, the cost of Cloud, the Cloud bill approaches 50% of the cost of revenue, it becomes an albatross that stifles operating leverage. Their conclusion ended up saying that as much as perhaps as much as the back of the napkin, they admitted that, but perhaps as much as 1/2 a trillion dollars in market cap is being vacuumed away by the hyperscalers that could go to the SaaS providers as cost savings from repatriation. And that Cloud repatriation is an inevitable path for large SaaS companies at scale. I was particularly interested in this as I had recently put on a post on the Cloud repatriation myth. I think in this instance, there's some merit to their conclusions. But I don't think it necessarily bleeds into traditional enterprise settings. But for SaaS companies, maybe service now has it right running their own data centers or maybe a hybrid approach to hedge bets and save money down the road is prudent. What caught my attention in reading through some of the Snowflake docs, like the S-1 in its most recent 10-K were comments regarding long-term purchase commitments and non-cancelable contracts with Cloud companies. And the companies S-1, for example, there was disclosure of $247 million in purchase commitments over a five plus year period. And the company's latest 10-K report, that same line item jumped to 1.8 billion. Now Snowflake is clearly managing these costs as it alluded to when its earnings call. But one has to wonder, at some point, will Snowflake follow the example of say Dropbox which Andreessen used in his blog and start managing its own IT? Or will it stick with the Cloud and negotiate hard? Snowflake certainly has the leverage. It has to be one of Amazon's best partners and customers even though it competes aggressively with Redshift but on the earnings call, CFO Scarpelli said, that Snowflake was working on a new chip technology to dramatically increase performance. What the heck does that mean? Is this Snowflake is not becoming a hardware company? So I going to have to dig into that a little bit and find out what that it means. I'm guessing, it means that it's taking advantage of ARM-based processes like graviton, which many ISVs ar allowing their software to run on that lower cost platform. Or maybe there's some deep dark in the weeds secret going on inside Snowflake, but I doubt it. We're going to leave all that for there for now and keep following this trend. So it's clear just in summary that Snowflake they're the pace setter in this new exciting world of data but there's plenty of room for others. And they still have a lot to prove. For instance, one customer in ETR, CTO round table express skepticism that Snowflake will live up to its hype because its success is going to lead to more competition from well-established established players. This is a common theme you hear it all the time. It's pretty easy to reach that conclusion. But my guess is this the exact type of narrative that fuels Slootman and sucked him back into this game of Thrones. That's it for now, everybody. Remember, these episodes they're all available as podcasts, wherever you listen. All you got to do is search braking analysis podcast and please subscribe to series. Check out ETR his website at etr.plus. We also publish a full report every week on wikinbon.com and siliconangle.com. You can get in touch with me, Email is David.vellante@siliconangle.com. You can DM me at DVelante on Twitter or comment on our LinkedIn posts. This is Dave Vellante for theCUBE Insights powered by ETR. Have a great week everybody, be well and we'll see you next time. (upbeat music)

>> From theCUBE Studios in Palo Alto and Boston, bringing you data-driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. >> UiPath has had a long, strange trip to IPO. How so you ask? Well, the company was started in 2005. But it's culture, is akin to a frenetic startup. The firm shunned conventions and instead of focusing on a narrow geographic area to prove its product market fit before it started to grow, it aggressively launched international operations prior to reaching unicorn status. Well prior, when it had very little revenue, around a million dollars. Today, more than 60% of UiPath business is outside of the United States. Despite its headquarters being in New York city. There's more, according to recent SEC filings, UiPath total revenue grew 81% last year. But it's free cash flow, is actually positive, modestly. Wait, there's more. The company raised $750 million in a Series F in early February, at a whopping $35 billion valuation. Yet, the implied back of napkin valuation, based on the number of shares outstanding after the offering multiplied by the proposed maximum offering price per share yields evaluation of just under 26 billion. (Dave chuckling) And there's even more to this crazy story. Hello everyone, and welcome to this week's Wikibon CUBE Insights, Powered by ETR. In this Breaking Analysis we'll share our learnings, from sifting through hundreds of pages (paper rustling) of UiPath's red herring. So you didn't have to, we'll share our thoughts on its market, its competitive position and its outlook. Let's start with a question. Mark Roberge, is a venture capitalist. He's a managing director at Stage 2 Capital and he's also a teacher, a professor at the B-School in Harvard. One of his favorite questions that he asks his students and others, is what's the best way to grow a company? And he uses this chart to answer that question. On the vertical axis is customer retention and the horizontal axis is growth to growth rate and you can see he's got modest and awesome and so forth. Now, so I want to let you look at it for a second. What's the best path to growth? Of course you want to be in that green circle. Awesome retention of more than 90% and awesome growth but what's the best way to get there? Should you blitz scale and go for the double double, triple, triple blow it out and grow your go to market team on the horizontal axis or should be more careful and focus on nailing retention and then, and only then go for growth? What do you think? What do you think most VCs would say? What would you say? When you want to maybe run the table, capture the flag before your competitors could get there or would you want to take a more conservative approach? What would Daniel Dines say the CEO of UiPath? Again, I'll let you think about that for a second. Let's talk about UiPath. What did they do? Well, I shared at the top that the company shunned conventions and expanded internationally, very rapidly. Well before it hit escape velocity and they grew like crazy and it got out of control and he had to reign it in, plug some holes, but the growth didn't stop, go. So very clearly based on it's performance and reading through the S1, the company has great retention. It uses a metric called gross retention rate which is at 96 or 97%, very high. Says customers are sticking with it. So maybe that's the right formula go for growth and grow like crazy. Let chaos reign, then reign in the chaos as Andy Grove would say. Go fast horizontally, and you can go vertically. Let me tell you what I think Mark Roberge would say, he told me you can do that. But churn is the silent killer of SaaS companies and perhaps the better path is to nail product market fit. And then your retention metrics, before you go into hyperbolic growth mode. There's all science behind this, which may be antithetical to the way many investors want to roll the dice and go for super growth, like go fast or die. Well, it worked for UiPath you might say, right. Well, no. And this is where the story gets even more interesting and long and strange for UiPath. As we shared earlier, UiPath was founded in 2005 out of Bucharest Romania. The company actually started as a software outsourcing startup. It called the company, DeskOver and it built automation libraries and SDKs for companies like Microsoft, IBM and Google and others. It also built automation scripts and developed importantly computer vision technology which became part of its secret sauce. In December 2015, DeskOver changed its name to UiPath and became a Delaware Corp and moved its headquarters to New York City a couple of years later. So our belief is that UiPath actually took the preferred path of Mark Roberge, five ticks North, then five more East. They slow-cooked for the better part of 10 years trying to figure out what market to serve. And they spent that decade figuring out their product market fit. And then they threw gas in the fire. Pretty crazy. All right, let's take a peak (chuckling) at the takeaways from the UiPath S1 the numbers are impressive. 580 million ARR with 65% growth. That asterisk is there because like you, we thought ARR stood for annual recurring revenue. It really stands for annualized renewal run rate. annualized renewal run rate is a metric that is one of UiPath's internal KPIs and are likely communicate that publicly over time. We'll explain that further in a moment. UiPath has a very solid customer base. Nearly 8,000, I've interviewed many of them. They're extremely happy. They have very high retention. They get great penetration into the fortune 500, around 63% of the fortune 500 has UiPath. Most of UiPath business around 70% comes from existing customers. I always say you're going to get more money out of existing customers than new customers but everybody's trying to go out and get new customers. But UiPath I think is taking a really interesting approach. It's their land and expand and they didn't invent that term but I'll come back to that. It kind of reminds me of the early days of Tableau. Actually I think Tableau is an interesting example. Like UiPath, Tableau started out as pretty much a point tool and it had, but it had very passionate customers. It was solving problems. It was simplifying things. And it would have bid into a company and grow and grow. Now the market fundamentals for UiPath are very good. Automation is super hot right now. And the pandemic has created an automation mandate to date and I'll share some data there as well. UiPath is a leader. I'm going to show you the Gartner Magic Quadrant for RPA. That's kind of a good little snapshot. UiPath pegs it's TAM at 60 billion dollars based on some bottoms up calculations and some data from Bain. Pre-pandemic, we pegged it at over 30 billion and we felt that was conservative. Post-pandemic, we think the TAM is definitely higher because of that automation mandate, it's been accelerated. Now, according to the S1, UiPath is going to raise around 1.2 billion. And as we said, if that's an implied valuation that is lower than the Series F, so we suspect the Series F investors have some kind of ratchet in there. UiPath needed the cash from its Series F investors. So it took in 750 million in February and its balance sheet in the S1 shows about 474 million in cash and equivalent. So as I say, it needed that cash. UiPath has had significant expense reductions that we'll show you in some detail. And it's brought in some fresh talent to provide some adult supervision around 70% of its executive leadership team and outside directors came to the company after 2019 and the company's S1, it disclosed that it's independent accounting firm identified last year what it called the "material weakness in our internal controls over financial report relating to revenue recognition for the fiscal year ending 2018, caused by a lack of oversight and technical competence within the finance department". Now the company outlined the steps it took to remediate the problem, including hiring new talent. However, we said that last year, we felt UiPath wasn't quite ready to go public. So it really had to get its act together. It was not as we said at the time, the well-oiled machine, that we said was Snowflake under Mike Scarpelli's firm operating guidance. The guy's the operational guru, but we suspect the company wants to take advantage of this mock market. It's a good time to go public. It needs the cash to bolster its balance sheet. And the public offering is going to give it cache in a stronger competitive posture relative to its main new competitor, autumn newbie competitor Automation Anywhere and the big whales like Microsoft and others that aspire and are watching what UiPath is doing and saying, hey we want a piece of that action. Now, one other note, UiPath's CEO Daniel Dines owns 100% of the class B shares of the company and has a 35 to one voting power. So he controls the company, subject of course to his fiduciary responsibilities but if UiPath, let's say it gets in trouble financially, he has more latitude to do secondary offerings. And at the same time, it's insulated from activist shareholders taking over his company. So lots of detail in the S1 and we just wanted to give you some of those highlights. Here are the pretty graphs. If whoever wrote this F1 was a genius. It's just beautiful. As we said, ARR, annualized renewal run rate all it does is it annualizes the invoice amount from subscriptions in the maintenance portion of the revenue. In other words, the parts that are recurring revenue, it excludes revenue from support and perpetual license. Like one-time licenses and services is just kind of the UiPath's and maybe that's some sort of legacy there. It's future is that recurring revenue. So it's pretty similar to what we think of as ARR, but it's not exact. Lots of customers with a growing number of six and seven figure accounts and a dollar-based net retention of 145%. This figure represents the rate of net expansion of the UiPath ARR, from existing listing customers over a 12 month period. Translation. This says UiPath's existing customers are spending more with the company, land and expand and we'll share some data from ETR on that. And as you can see, the growth of 86% CAGR over the past nine quarters, very impressive. Let's talk about some of the fundamentals of UiPath's business. Here's some data from the Brookings Institute and the OECD that shows productivity statistics for the US. The smaller charts in the right are for Germany and Japan. And I've shared some similar data before the US showed in the middle there. Showed productivity improvements with the personal productivity boom in the mid to late 90s. And it spilled into the early 2000s. But since then you can see it's dropped off quite significantly. Germany and Japan are also under pressure as are most developed countries. China's labor productivity might show declines but it's level, is at level significantly higher than these countries, April 16th headline of the Wall Street Journal says that China's GDP grew 18% this quarter. So, we've talked about the snapback in post-COVID and the post-isolation economy, but these are kind of one time bounces. But anyway, the point is we're reaching the limits of what humans can do alone to solve some of the world's most pressing challenges. And automation is one key to shifting labor away from these more mundane tasks toward more productive and more important activities that can deliver lasting benefits. This according to UiPath, is its stated purpose to accelerate human achievement, big. And the market is ready to be automated, for the most part. Now the post-isolation economy is increasingly going to focus on automation to drive toward activity as we've discussed extensively, I got to share the RPA Magic Quadrant where nearly everyone's a winner, many people are of course happy. Many companies are happy, just to get into the Magic Quadrant. You can't just, you have to have certain criteria. So that's good. That's what I mean by everybody wins. We've reported extensively on UiPath and Automation Anywhere. Yeah, we think we might shuffle the deck a little bit on this picture. Maybe creating more separation between UiPath and Automation Anywhere and the rest. And from our advantage point, UiPath's IPO is going to either force Automation Anywhere to respond. And I don't know what its numbers are. I don't know if it's ready. I suspect it's not, we'd see that already but I bet you it's trying to get there. Or if they don't, UiPath is going to extend its lead even further, that would be our prediction. Now personally, I would have Pegasystems higher on the vertical. Of course they're not an IPO, RPA specialist, so I kind of get what Gartner is doing there but I think they're executing well. And I'd probably, in a broader context I'd probably maybe drop blue prism down a little bit, even though last year was a pretty good year for the company. And I would definitely have Microsoft looming larger up in the upper left as a challenger more than a visionary in my opinion, but look, Gartner does good work and its analysts are very deep into this stuff, deeper than I am. So I don't want to discount that. It's just how I see it. Let's bring in the ETR data and show some of the backup here. This is a candlestick chart that shows the components of net score, which is spending momentum, however, ETR goes out every quarter. Says you're spending more, you're spending less. They subtract the lesses from the mores and that's net score. It's more complicated than that, but that's that blue line that you see in the top and yes it's trending downward but it's still highly elevated. We'll talk about that. The market share is in the yellow line at the bottom there. That green represents the percentage of customers that are spending more and the reds are spending less or replacing. That gray is flat. And again, even though UiPath's net score is declining, it's that 61%, that's a very elevated score. Anything over 40% in our view is impressive. So it's, UiPath's been holding in the 60s and 70s percents over the past several years. That's very good. Now that yellow line market share, yes it dips a bit, but again it's nuanced. And this is because Microsoft is so pervasive in the data stat. It's got so many mentions that it tends to somewhat overwhelm and skew these curves. So let's break down net score a little bit. Here's another way to look at this data. This is a wheel chart we show this often it shows the components of net score and what's happening here is that bright red is defection. So look at it, it's very small that wouldn't be churn. It's tiny. Remember that it's churn is the killer for software companies. And so that forest green is existing customers spending more at 49%, that's big. That lime green is new customers. So again, it's from the S1, 70% of UiPath's revenue comes from existing customers. And this really kind of underscores that. Now here's more evidence in the ETR data in terms of land and expand. This is a snapshot from the January survey and it lines up UiPath next to its competitors. And it cuts the data just on those companies that are increasing spending. It's so that forest green that we saw earlier. So what we saw in Q1 was the pace of new customer acquisition for UiPath was decelerating from previous highs. But UiPath, it shows here is outpacing its competition in terms of increasing spend from existing customers. So we think that's really important. UiPath gets very high scores in terms of customer satisfaction. There's, I've talked to many in theCUBE. There's places on the web where we have customer ratings. And so you want to check that out, but it'll confirm that the churn is low, satisfaction is high. Yeah, they get dinged sometimes on pricing. They get dinged sometimes, lately on service cause they're growing so fast. So, maybe they've taken the eye off the ball in a couple of counts, but generally speaking clients are leaning in, they're investing heavily. They're creating centers of excellence around RPA and automation, and UiPath is very focused on that. Again, land and expand. Now here's further evidence that UiPath has a strong account presence, even in accounts where its competitors are presence. In the 149 shared accounts from the Q1 survey where UiPath, Automation Anywhere and Microsoft have a presence, UiPath's net score or spending velocity is not only highly elevated, it's relative momentum, is accelerating compared to last year. So there's some really good news in the numbers but some other things stood out in the S1 that are concerning or at least worth paying attention to. So we want to talk about that. Here is the income statement and look at the growth. The company was doing like 1 million dollars in 2015 like I said before. And when it started to expand internationally it surpassed 600 million last year. It's insane growth. And look at the gross profit. Gross margin is almost 90% because revenue grew so rapidly. And last year, its cost went down in some areas like its services, less travel was part of that. Now jump down to the net loss line. And normally you would expect a company growing at this rate to show a loss. The street wants growth and UiPath is losing money, but it's net loss went from 519 million, half a billion down to only 92 million. And that's because the operating expenses went way down. Now, again, typically a company growing at this rate would show corresponding increases in sales and marketing expense, R&D and even G&A but all three declined in the past 12 months. Now reading the notes, there was definitely some meaningful savings from no travel and canceled events. UiPath has great events around the world. In fact theCUBE, Knock Wood is going to be at its event in October, in Las Vegas at the Bellagio . So we're stoked for that. But, to drop expenses that precipitously with such high growth, is kind of strange. Go look at Snowflake's income statement. They're in hyper-growth as well. We like to compare it to Snowflake is a very well-run company and it's in hyper-growth mode, but it's sales and marketing and R&D and G&A expense lines. They're all growing along with that revenue. Now, perhaps they're growing at a slower rate. Perhaps the percent of revenue is declining as it should as they achieve operating leverage but they're not shrinking in absolute dollar terms as shown in the UiPath S1. So either UiPath has applied some magic automation mojo to it's business (chuckling). Like magic beans or magic grits with my cousin Vinny. Maybe it has found the Holy grail of operating leverage. It's a company that's all about automation or the company was running way too hot on the expense side and had a cut and clean up its income statement for the IPO and conserve some cash. Our guess is the latter but maybe there's a combination there. We'll give him the benefit of the doubt. And just to add a bit more to this long, strange trip. When have you seen an explosive growth company just about to go public, show positive cashflow? Maybe it's happened, but it's rare in the tech and software business these days. Again, go look at companies like Snowflake. They're not showing positive cashflow, not yet anyway. They're growing and trying to run the table. So you have to ask why is UiPath operating this way? And we think it's because they were so hot and burning cash that they had to reel things in a little bit and get ready to IPO. It's going to be really interesting to see how this stock reacts when it does IPO. So here's some things that we want you to pay attention to. We have to ask. Is this IPO, is it window dressing? Or did UiPath again uncover some new productivity and operating leverage model. I doubt there's anything radically new here. This company doesn't want to miss the window. So I think it said, okay, let's do this. Let's get ready for IPO. We got to cut expenses. It had a lot of good advisors. It surrounded itself with a new board. Extended that board, new management, and really want to take advantage of this because it needs the cash. In addition, it really does want to maintain its lead. It's got Automation Anywhere competing with it. It's got Microsoft looming large. And so it wants to continue to lead. It's made some really interesting acquisitions. It's got very strong vision as you saw in the Gartner Magic Quadrant and obviously it's executing well but it's really had to tighten things up. So we think it's used the IPO as a fortune forcing function to really get its house in order. Now, will the automation mandate sustain? We think it will. The forced match to digital worked, it was effective. It wasn't pleasant, but even in a downturn we think it will confer advantage to automation players and particularly companies like UiPath that have simplified automation in a big way and have done a great job of putting in training, great freemium model and has a culture that is really committed to the future of humankind. It sounds ambitious and crazy but talk to these people, you'll see it's true. Pricing, UiPath had to dramatically expand or did dramatically expand its portfolio and had to reprice everything. And I'm not so worried about that. I think it'll figure that pricing out for that portfolio expansion. My bigger concern is for SaaS companies in general. I don't like SaaS pricing that has been popularized by Workday and ServiceNow, and Salesforce and DocuSign and all these companies that essentially lock you in for a year or two and basically charge you upfront. It's really is a one-way street. You can't dial down. You can only dial up. It's not true Cloud pricing. You look at companies like Stripe and Datadog and Snowflake. It is true Cloud pricing. It's consumption pricing. I think the traditional SaaS pricing model is flawed. It's very unfairly weighted toward the vendors and I think it's going to change. Now, the reason we put cloud on the chart is because we think Cloud pricing is the right way to price. Let people dial up and dial down, let them cancel anytime and compete on the basis of your product excellence. And yeah, give them a price concession if they do lock in. But the starting point we think should be that flexibility, pay by the drink. Cancel anytime. I mentioned some companies that are doing that as well. If you look at the modern SaaS startups and the forward-thinking VCs they're really pushing their startups to this model. So we think over time that the term lock-in model is going to give way to true consumption-based pricing and at the clients option, allow them to lock-in for a better price, way better model. And UiPath's Cloud revenue today is minimal but over time, we think it's going to continue to grow that cloud. And we think it will force a rethink in pricing and in revenue recognition. So watch for that. How is the street going to react to Daniel Dines having basically full control of the company? Generally, we feel that that solid execution if UiPath can execute is going to outweigh those concerns. In fact, I'm very confident that it will. We'll see, I kind of like what the CEO says has enough mojo to say (chuckling) you know what, I'm not going to let what happened to for instance, EMC happen to me. You saw Michael Dell do that. You saw just this week they're spinning out VMware, he's maintaining his control. VMware Dell shareholders get get 40.44 shares for every Dell share they're holding. And who's the biggest shareholder? Michael Dell. So he's, you got two companies, one chairman. He's controlling the table. Michael Dell beat the great Icahn. Who beats Carl Icahn? Well, Michael Dell beats Carl Icahn. So Daniel Dines has looked at that and says, you know what? I'm not just going to give up my company. And the reason I like that with an if, is that we think will allow the company to focus more on the long-term. The if is, it's got to execute otherwise it's so much pressure and look, the bottom line is that UiPath has really favorable market momentum and fundamentals. But it is signing up for the 90 day short clock. The fact that the CEO has control again means they can look more long term and invest accordingly. Oftentimes that's easier said than done. It does come down to execution. So it is going to be fun to watch (chuckling). That's it for now, thanks to the community for your comments and insights and really always appreciate your feedback. Remember, I publish each week on Wikibon.com and siliconangle.com and these episodes are all available as podcasts. All you got to do is search for the Breaking Analysis podcast. You can always connect with me on Twitter @dvellante or email me at david.vellante@siliconangle.com or comment on my LinkedIn posts. And we'll see you in clubhouse. Follow me and get notified when we start a room, which we've been doing with John Furrier and Sarbjeet Johal and others. And we love to riff on these topics and don't forget, please check out etr.plus for all the survey action. This is Dave Vellante, for theCUBE Insights Powered by ETR. Be well everybody. And we'll see you next time. (gentle upbeat music)

[Music] 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 uipath's recent 750 million dollar raise at a 35 billion valuation underscores investor enthusiasm for robotic process automation rpa and why not the pandemic has fueled a surge in automation as organizations retool their operations and prepare for a post-covered environment but look reasonable people are asking is this market getting overheated welcome to this week's wikibon cube insights powered by etr in this breaking analysis we'll explore the current trends in the rpa market and try to address the question is uipath's value supported by the spending data how will the rpa market evolve from a total available market perspective and where do some of the other players like automation anywhere pega systems and blue prism fit let's first summarize what's new in rpa since we last reported in the space we've all beat to death the positive impact that covet has had on many sectors and rpa is one of the beneficiaries from most if not many organizations if you're not a digital business today you're out of business and replacing labor with software is a major factor in the digital transformations that are taking place now uipath has raised about two billion dollars to date and has a value comparable to that of snowflake at its ipo many are predicting that it will in fact be the snowflake of 2021. look i'm optimistic about the future of uipath but in my opinion the operational excellence that frank slootman and mike scarpelli have brought to snowflake is not nearly as baked as at that at uipath and that that said the market conditions are quite good for uipath right now now while cost reduction is still the main driver for rpa adoptions we're seeing more business productivity use cases that point to a broader automation agenda than simply installing some software robots and point applications to eliminate mundane tasks rather we're seeing a much more holistic thinking in within organizations in a large part driven by the covid slap in the face and given the ceos have now a green light to make big changes that would have been culturally more difficult pre-pandemic to wit we're seeing many more centers of excellence pop up around rpa with a more aggressive agenda than we saw pre-covered before covert these efforts they've been met with a lot more resistance to change than we're seeing today now in the coming decade we expect two major trends to emerge one is a move from this search and destroy mentality toward process transformation to more of an automated approach around discovering candidates for automation second is low code implementations are likely to lead the rise of the so-called citizen developer now capabilities in this regard today are nascent within most products but we believe they will improve steadily over the next several years years and lead to the democracy democratization of rpa so the big question is are we in an rpa bubble or is this really the next big thing this chart depicts our attempt a while back to assess the total available market for robotic process automation and there are a few important points here first our effort was somewhat narrowly focused on rpa tooling but we did try to take into account a broader automation agenda across enterprises we tried to size the move from back office to front office to enterprise-wide automation efforts leading to this buzzword that ultimately gartner created called hyper automation now when we first published this chart we got feedback that we were too conservative and so you know we've thought about what could we be missing and that's depicted there in that red big question mark we've got to do more work on this but looking at the global automation market we see a multi-hundred billion dollar opportunity however that largely focuses on industrial automation versus replacing human tasks with robots process automation is a much smaller piece of that pie and overall these larger figures they also include drones autonomous vehicles and other innovations that rpa may or may not address is it possible that there's an order of magnitude greater opportunity for rpa than we initially thought well here's another way to look at it rpa generally is targeted at larger organizations which can justify the investment with faster returns according to fortune magazine the 500 largest companies in the world generate more than 30 trillion in revenue is it unreasonable to assume that they could spend one percent of revenue on rpa we don't think that's crazy so there very well could be a tam of hundreds of billions of dollars for this market we would say however to attack that opportunity point rpa tools won't get you there but automation platforms very well could in fact that better be the case because with a 35 billion dollar valuation pre-ipo uipath and its peers will need a massive massive market to justify those investments so we'll keep digging into that expanded opportunity to see if it holds water now another way to look at the opportunity is to look at the spending data so let's do that and bring in our etr friends to that discussion as we've reported for many quarters now rpa is one of the top areas in which organizations are investing and you can see that in this chart here this graphic shows net score or spending momentum across the etr taxonomy and you can see we've highlighted rpa which along with machine learning slash ai cloud and containers lead the pack the big four momentum leaders in the only four that consistently over the last several quarters show a net score in the survey above that dotted red forty percent line now remember that net score is a measure of spending velocity based on looking at the percent of customers in the survey that are spending more and subtracting those that are spending less the calculation is a bit more granular than that but you get the point now one of the components of net score is new adoptions and that's part of the spend more equation and this chart shows that only the new adoptions across that taxonomy in those sectors and you can see that rpa and machine learning slash ai top the charts that yellow line shows the january survey results you can see these two sectors are well ahead of others in terms of new spending albeit they are down somewhat from previous quarters a year ago rather but up from the previous quarter now here's another look at the data let's let's really drill into the the rpa sector and look at those components of net score what this chart shows is that granularity along with market share for the past nine surveys i'll explain that the bright green or that lime green on the bars that's new adoptions the forest green is the percent of customers that are spending more on rpa that means they're spending more than five percent the gray depicts flat spending the pink is spending less meaning less than five percent relative to earlier years and the the earlier year and the bright red is replacing the platform we're chucking it out and the net score blue line at the top it nets out the lesses from the moors so you can see very highly elevated for the rpa sector holding firm over time and now even increasing so very very positive now you see that yellow line at the bottom that shows so-called market share which depicts the pervasiveness of rpa within the overall survey relative to other sectors so the steady uptick over time suggests that buyers continue to allocate more and more budget to rpa so very very positive signs there because let's face it the return has been really positive and the mandate for automation thanks to covid is really staring us in the face now let's drill into some of the vendors and see who's winning in the market and maybe who's got less momentum the chart here shows spending momentum or net score over time for the five companies that we're showing now at the top is power automate from microsoft which last year required softer motive and is integrating rpa into its offerings microsoft look they loom large as we've reported and they're everywhere in so many many sectors and rpa is no different the reality is that power automate is not as mature as products from the leaders a classic microsoft 1.0 version if you will but they're in the game now and they cannot be taken lightly we expect microsoft to steadily improve its functionality and integration with the broader microsoft portfolio making it an easy choice for many if not most of microsoft's customers that either want to dabble in rpa or have it as an item in their portfolio you can see uipath has retaken the lead in net score over rival automation anywhere and is showing a nice uptick from last summer's survey as it has made some acquisitions and is moving toward becoming a platform play versus a product play we'd also note three factors that favor uipath in the marketplace first is its simplicity uipath is probably the easiest to adopt second is its emphasis on training and third is the very robust community and ecosystem that it's developed automation anywhere's line is under pressure and we think that's because the company essentially had to do a major product refresh and like any install based migration it's going to slow down momentum and create maybe some friction in the marketplace but we think from a competitive standpoint it was absolutely the right move by aa you've got to bite the bullet invest in the product and grow from there the company also has a really strong ecosystem good engineering and we expect continued improvement for automation anywhere going forward you also see a big uptick for blue prism it's got a mature product and a strong ecosystem as well and we've seen its momentum pop up and down in the survey over the last several quarters and years but they're clearly a solid player in this market they don't have the momentum of a ui path or an automation anywhere they're they're a smaller company but certainly they're a credible player now pega systems is really interesting to us we don't see them as an rpa player per se they're much more focused on a broader business process play include things like crm and intelligent automation in their portfolio rpa is a bundled offering that pega layers into its broader suite and we like what the company has accomplished we're going to come back to them in a moment and talk a little bit more about them and their performance but before we do that let's take another look at the competitive landscape this view is one of our favorites it's that it's that xy view so so we're plotting net score on the y-axis and market share or the pervasiveness within the survey on the x-axis and you can see uipath is they're literally off the charts in the upper right there with because microsoft looming large with its very strong presence and fast adoption of power automate but microsoft ui path automation anywhere in blue prism they all have shared ends or mentions in the survey of more than 50 and net scores over 50 percent so those stand out to us above the rest with uipath as the leader combining both the most significant market momentum and product excellence notwithstanding microsoft's presence again microsoft and their microsoft and we'd be foolish to minimize their their presence in the marketplace now again pega is in the mix they've got a respectable 31 net score but again they're not an rpa specialist and their strategy is paying off in our view the rpa froth combined with pegas history its vision its solid engineering culture and execution are paying off for the company as you can see in these charts so there's charts so what we're showing here is a graph of pegas stock price over the last five years what's most impressive is the strong upward move very very strong since march of last year peg is a billion dollar company been around for a long time but it's growing it's moving it's shifting into a subscription model so it's going through that process of communicating that to wall street i think doing a very very good job of it as it transitions it's transitioning to a recurring revenue stream that's going to have a much more predictable cash flow and profitability impact on the company and you can see its valuation it's at 12 billion it's about 12x revenue it's significantly lower than uipath's most recent value by a factor of roughly 3x but you know presumably that's due to its slower growth rate but pega they've got to love this dynamic because the market's coming to them they've got a mature business that's thriving through a transition to an arr model with solid growth strong customer base and a culture of innovation so really solid job within pega that management is doing in our opinion now let's close by digging into the two pure play leaders uipath and automation anywhere we do this quite frequently in these updates and we'll look at the so-called wheel charts for each company let's start with uipath so this is a pie if you will or wheel breakdown of what we described earlier in net score it's derived from this view by subtracting the reds from the greens several things stand out first you got a nice chunk of new adoptions at 15 percent supported by 56 percent of its customers spending more and only 5 percent spending less than zero percent replacing so that's a very nice picture now let's compare that to automation anywhere and its profile the chart shows the same picture and and even a larger substantially larger new adoptions so that perhaps is is a function of its new platform resonating with customers now automation anywhere's net score is lower than you ui pass owing to a much larger portion of the customer base that has flat spending and a slightly higher replacement figure but both these companies exhibit strong spending patterns in the etr data now we want to share one other data point that stands out in its early days this new relatively new era of rpa we're still there even though rpa has been around for for decades but the point is that large companies have they got a lot of divisions with a lot of buying autonomy within those divisions and as such you're going to see multiple rpa vendors within the account so the question here is okay how are these accounts doing these where they have multiple vendors in the account what stands out in this chart is uipath's performance in shared accounts the chart looks at microsoft power automate and automation anywhere accounts you can see that in the little pull down there in the in the left hand column and so it's it's it's it's microsoft power automate and aaa accounts that also have ui path installed and you can see that little cut on ui path there in the upper middle and there's 149 of those accounts in the etr data set this last quarter and you can see the performance of uipath since covid hit this is very encouraging it speaks to ui past strong go to market and it's really solid land and expand strategy so by no means is this game over for the other players but the etr data continues to support where investors are placing their bets what customers tell us and anecdotal information within the marketplace that that uipath continues to pave the way for a new wave of growth a well-funded automation anywhere is on its tail and these two continue to vie for leadership and are trying to break out from the pack we expect public offerings from both companies within the next 12 to 24 months in fact as you know probably uipath has filed confidentially to do an ipo and has given a time frame i think of 12 to 18 months and they both companies in our view got to get they got a window of 12 to 24 months to go public prior to microsoft getting its product act together and getting to a point where it could really cause some disruption to these respective businesses so anyway i hope this gives you a good snapshot of how we see the marketplace how do you see it please let me know you can dm me at d vallante or comment on my linkedin posts or email me at david.velante at siliconangle.com remember i publish each week on wikibon.com and siliconangle.com and don't forget to check out etr.plus as well all these episodes are available on podcasts wherever you listen thanks for watching this episode of thecube insights powered by etr this is dave vellante wishing you well stay safe and we'll see you next time you

>> From theCUBE Studios in Palo Alto in Boston, bringing you data driven insights from theCUBE and ETR. This is breaking analysis with Dave Vellante. >> In June of this year, Snowflake filed a confidential document suggesting that it would do an IPO. Now of course, everybody knows about it, found out about it and it had a $20 billion valuation. So, many in the community and the investment community and so forth are excited about this IPO. It could be the hottest one of the year, and we're getting a number of questions from investors and practitioners and the entire Wiki bond, ETR and CUBE community. So, welcome everybody. This is Dave Vellante. This is "CUBE Insights" powered by ETR. In this breaking analysis, we're going to unpack five critical questions around Snowflake's IPO or pending IPO. And with me to discuss that is Erik Bradley. He's the Chief Engagement Strategists at ETR and he's also the Managing Director of VENN. Erik, thanks for coming on and great to see you as always. >> Great to see you too. Always enjoy being on the show. Thank you. >> Now for those of you don't know Erik, VENN is a roundtable that he hosts and he brings in CIOs, IT practitioners, CSOs, data experts and they have an open and frank conversation, but it's private to ETR clients. But they know who the individual is, what their role is, what their title is, et cetera and it's a kind of an ask me anything. And I participated in one of them this past week. Outstanding. And we're going to share with you some of that. But let's bring up the agenda slide if we can here. And these are really some of the questions that we're getting from investors and others in the community. There's really five areas that we want to address. The first is what's happening in this enterprise data warehouse marketplace? The second thing is kind of a one area. What about the legacy EDW players like Oracle and Teradata and Netezza? The third question we get a lot is can Snowflake compete with the big cloud players? Amazon, Google, Microsoft. I mean they're right there in the heart, in the thick of things there. And then what about that multi-cloud strategy? Is that viable? How much of a differentiator is that? And then we get a lot of questions on the TAM. Meaning the total available market. How big is that market? Does it justify the valuation for Snowflake? Now, Erik, you've been doing this now. You've run a couple VENNs, you've been following this, you've done some other work that you've done with Eagle Alpha. What's your, just your initial sort of takeaway from all this work that you've been doing. >> Yeah, sure. So my first take on Snowflake was about two and a half years ago. I actually hosted them for one of my VENN interviews and my initial thought was impressed. So impressed. They were talking at the time about their ability to kind of make ease of use of a multi-cloud strategy. At the time although I was impressed, I did not expect the growth and the hyper growth that we have seen now. But, looking at the company in its current iteration, I understand where the hype is coming from. I mean, it's 12 and a half billion private valuation in the last round. The least confidential IPO (laughs) anyone's ever seen (Dave laughs) with a 15 to $20 billion valuation coming out, which is more than Teradata, Margo and Cloudera combined. It's a great question. So obviously the success to this point is warranted, but we need to see what they're going to be able to do next. So I think the agenda you laid out is a great one and I'm looking forward to getting into some of those details. >> So let's start with what's happening in the marketplace and let's pull up a slide that I very much love to use. It's the classic X-Y. On the vertical axis here we show net score. And remember folks, net score is an indicator of spending momentum. ETR every quarter does like a clockwork survey where they're asking people, "Essentially are you spending more or less?" They subtract the less from the more and comes up with a net score. It's more complicated than, but like NPS, it's a very simple and reliable methodology. That's the vertical axis. And the horizontal axis is what's called market share. Market share is the pervasiveness within the data set. So it's calculated by the number of mentions of the vendor divided by the number of mentions within that sector. And what we're showing here is the EDW sector. And we've pulled out a few companies that I want to talk about. So the big three, obviously Microsoft, AWS and Google. And you can see Microsoft has a huge presence far to the right. AWS, very, very strong. A lot of Redshift in there. And then they're pretty high on the vertical axis. And then Google, not as much share, but very solid in that. Close to 60% net score. And then you can see above all of them from a vertical standpoint is Snowflake with a 77.5% net score. You can see them in the upper right there in the green. One of the highest Erik in the entire data set. So, let's start with some sort of initial comments on the big guys and Snowflakes. Your thoughts? >> Sure. Just first of all to comment on the data, what we're showing there is just the data warehousing sector, but Snowflake's actual net score is that high amongst the entire universe that we follow. Their data strength is unprecedented and we have forward-looking spending intention. So this bodes very well for them. Now, what you did say very accurately is there's a difference between their spending intentions on a net revenue level compared to AWS, Microsoft. There no one's saying that this is an apples-to-apples comparison when it comes to actual revenue. So we have to be very cognizant of that. There is domination (laughs) quite frankly from AWS and from Azure. And Snowflake is a necessary component for them not only to help facilitate a multi-cloud, but look what's happening right now in the US Congress, right? We have these tech leaders being grilled on their actual dominance. And one of the main concerns they have is the amount of data that they're collecting. So I think the environment is right to have another player like this. I think Snowflake really has a lot of longevity and our data is supporting that. And the commentary that we hear from our end users, the people that take the survey are supporting that as well. >> Okay, and then let's stay on this X-Y slide for a moment. I want to just pull out a couple of other comments here, because one of the questions we're asking is Whither, the legacy EDW players. So we've got in here, IBM, Oracle, you can see Teradata and then Hortonworks and MapR. We're going to talk a little bit about Hortonworks 'cause it's now Cloudera. We're going to talk a little bit about Hadoop and some of the data lakes. So you can see there they don't have nearly the net score momentum. Oracle obviously has a huge install base and is investing quite frankly in R&D and do an Exadata and it has its own cloud. So, it's got a lock on it's customers and if it keeps investing and adding value, it's not going away. IBM with Netezza, there's really been some questions around their commitment to that base. And I know that a lot of the folks in the VENNs that we've talked to Erik have said, "Well, we're replacing Netezza." Frank Slootman has been very vocal about going after Teradata. And then we're going to talk a little bit about the Hadoop space. But, can you summarize for us your thoughts in your research and the commentary from your community, what's going on with the legacy guys? Are these guys cooked? Can they hang on? What's your take? >> Sure. We focus on this quite a bit actually. So, I'm going to talk about it from the data perspective first, and then we'll go into some of the commentary and the panel. You even joined one yesterday. You know that it was touched upon. But, first on the data side, what we're noticing and capturing is a widening bifurcation between these cloud native and the legacy on-prem. It is undeniable. There is nothing that you can really refute. The data is concrete and it is getting worse. That gap is getting wider and wider and wider. Now, the one thing I will say is, nobody's going to rip out their legacy applications tomorrow. It takes years and years. So when you look at Teradata, right? Their market cap's only 2 billion, 2.3 billion. How much revenue growth do they need to stay where they are? Not much, right? No one's expecting them to grow 20%, which is what you're seeing on the left side of that screen. So when you look at the legacy versus the cloud native, there is very clear direction of what's happening. The one thing I would note from the data perspective is if you switched from net score or adoptions and you went to flat spending, you suddenly see Oracle and Teradata move over to that left a little bit, because again what I'm trying to say is I don't think they're going to catch up. No, but also don't think they're going away tomorrow. That these have large install bases, they have relationships. Now to kind of get into what you were saying about each particular one, IBM, they shut down Netezza. They shut it down and then they brought it back to life. How does that make you feel if you're the head of data architecture or you're DevOps and you're trying to build an application for a large company? I'm not going back to that. There's absolutely no way. Teradata on the other hand is known to be incredibly stable. They are known to just not fail. If you need to kind of re-architect or you do a migration, they work. Teradata also has a lot of compliance built in. So if you're a financials, if you have a regulated business or industry, there's still some data sets that you're not going to move up to the cloud. Whether it's a PII compliance or financial reasons, some of that stuff is still going to live on-prem. So Teradata is still has a very good niche. And from what we're hearing from our panels, then this is a direct quote if you don't mind me looking off screen for one second. But this is a great one. Basically said, "Teradata is the only one from the legacy camp who is putting up a fight and not giving up." Basically from a CIO perspective, the rest of them aren't an option anymore. But Teradata is still fighting and that's great to hear. They have their own data as a service offering and listen, they're a small market cap compared to these other companies we're talking about. But, to summarize, the data is very clear. There is a widening bifurcation between the two camps. I do not think legacy will catch up. I think all net new workloads are moving to data as a service, moving to cloud native, moving to hosted, but there are still going to be some existing legacy on-prem applications that will be supported with these older databases. And of those, Oracle and Teradata are still viable options. >> I totally agree with you and my colleague David Floyd is actually quite high on Teradata Vantage because he really does believe that a key component, we're going to talk about the TAM in a minute, but a key component of the TAM he believes must include the on-premises workloads. And Frank Slootman has been very clear, "We're not doing on-prem, we're not doing this halfway house." And so that's an opportunity for companies like Teradata, certainly Oracle I would put it in that camp is putting up a fight. Vertica is another one. They're very small, but another one that's sort of battling it out from the old NPP world. But that's great. Let's go into some of the specifics. Let's bring up here some of the specific commentary that we've curated here from the roundtables. I'm going to go through these and then ask you to comment. The first one is just, I mean, people are obviously very excited about Snowflake. It's easy to use, the whole thing zero to Snowflake in 90 minutes, but Snowflake is synonymous with cloud-native data warehousing. There are no equals. We heard that a lot from your VENN panelist. >> We certainly did. There was even more euphoria around Snowflake than I expected when we started hosting these series of data warehousing panels. And this particular gentleman that said that happens to be the global head of data architecture for a fortune 100 financials company. And you mentioned earlier that we did a report alongside Eagle Alpha. And we noticed that among fortune 100 companies that are also using the big three public cloud companies, Snowflake is growing market share faster than anyone else. They are positioned in a way where even if you're aligned with Azure, even if you're aligned with AWS, if you're a large company, they are gaining share right now. So that particular gentleman's comments was very interesting. He also made a comment that said, "Snowflake is the person who championed the idea that data warehousing is not dead yet. Use that old monthly Python line and you're not dead yet." And back in the day where the Hadoop came along and the data lakes turned into a data swamp and everyone said, "We don't need warehousing anymore." Well, that turned out to be a head fake, right? Hadoop was an interesting technology, but it's a complex technology. And it ended up not really working the way people want it. I think Snowflake came in at that point at an opportune time and said, "No, data warehousing isn't dead. We just have to separate the compute from the storage layer and look at what I can do. That increases flexibility, security. It gives you that ability to run across multi-cloud." So honestly the commentary has been nothing but positive. We can get into some of the commentary about people thinking that there's competition catching up to what they do, but there is no doubt that right now Snowflake is the name when it comes to data as a service. >> The other thing we heard a lot was ETL is going to get completely disrupted, you sort of embedded ETL. You heard one panelist say, "Well, it's interesting to see that guys like Informatica are talking about how fast they can run inside a Snowflake." But Snowflake is making that easy. That data prep is sort of part of the package. And so that does not bode well for ETL vendors. >> It does not, right? So ETL is a legacy of on-prem databases and even when Hadoop came along, it still needed that extra layer to kind of work with the data. But this is really, really disrupting them. Now the Snowflake's credit, they partner well. All the ETL players are partnered with Snowflake, they're trying to play nice with them, but the writings on the wall as more and more of this application and workloads move to the cloud, you don't need the ETL layer. Now, obviously that's going to affect their talent and Informatica the most. We had a recent comment that said, this was a CIO who basically said, "The most telling thing about the ETL players right now is every time you speak to them, all they talk about is how they work in a Snowflake architecture." That's their only metric that they talk about right now. And he said, "That's very telling." That he basically used it as it's their existential identity to be part of Snowflake. If they're not, they don't exist anymore. So it was interesting to have sort of a philosophical comment brought up in one of my roundtables. But that's how important playing nice and finding a niche within this new data as a service is for ETL, but to be quite honest, they might be going the same way of, "Okay, let's figure out our niche on these still the on-prem workloads that are still there." I think over time we might see them maybe as an M&A possibility, whether it's Snowflake or one of these new up and comers, kind of bring them in and sort of take some of the technology that's useful and layer it in. But as a large market cap, solo existing niche, I just don't know how long ETL is for this world. >> Now, yeah. I mean, you're right that if it wasn't for the marketing, they're not fighting fashion. But >> No. >> really there're some challenges there. Now, there were some contrarians in the panel and they signaled some potential icebergs ahead. And I guarantee you're going to see this in Snowflake's Red Herring when we actually get it. Like we're going to see all the risks. One of the comments, I'll mention the two and then we can talk about it. "Their engineering advantage will fade over time." Essentially we're saying that people are going to copycat and we've seen that. And the other point is, "Hey, we might see some similar things that happened to Hadoop." The public cloud players giving away these offerings at zero cost. Essentially marginal cost of adding another service is near zero. So the cloud players will use their heft to compete. Your thoughts? >> Yeah, first of all one of the reasons I love doing panels, right? Because we had three gentlemen on this panel that all had nothing but wonderful things to say. But you always get one. And this particular person is a CTO of a well known online public travel agency. We'll put it that way. And he said, "I'm going to be the contrarian here. I have seven different technologies from private companies that do the same thing that I'm evaluating." So that's the pressure from behind, right? The technology, they're going to catch up. Right now Snowflake has the best engineering which interestingly enough they took a lot of that engineering from IBM and Teradata if you actually go back and look at it, which was brought up in our panel as well. He said, "However, the engineering will catch up. They always do." Now from the other side they're getting squeezed because the big cloud players just say, "Hey, we can do this too. I can bundle it with all the other services I'm giving you and I can squeeze your pay. Pretty much give it a waive at the cost." So I do think that there is a very valid concern. When you come out with a $20 billion IPO evaluation, you need to warrant that. And when you see competitive pressures from both sides, from private emerging technologies and from the more dominant public cloud players, you're going to get squeezed there a little bit. And if pricing gets squeezed, it's going to be very, very important for Snowflake to continue to innovate. That comment you brought up about possibly being the next Cloudera was certainly the best sound bite that I got. And I'm going to use it as Clickbait in future articles, because I think everyone who starts looking to buy a Snowflake stock and they see that, they're going to need to take a look. But I would take that with a grain of salt. I don't think that's happening anytime soon, but what that particular CTO was referring to was if you don't innovate, the technology itself will become commoditized. And he believes that this technology will become commoditized. So therefore Snowflake has to continue to innovate. They have to find other layers to bring in. Whether that's through their massive war chest of cash they're about to have and M&A, whether that's them buying analytics company, whether that's them buying an ETL layer, finding a way to provide more value as they move forward is going to be very important for them to justify this valuation going forward. >> And I want to comment on that. The Cloudera, Hortonworks, MapRs, Hadoop, et cetera. I mean, there are dramatic differences obviously. I mean, that whole space was so hard, very difficult to stand up. You needed science project guys and lab coats to do it. It was very services intensive. As well companies like Cloudera had to fund all these open source projects and it really squeezed their R&D. I think Snowflake is much more focused and you mentioned some of the background of their engineers, of course Oracle guys as well. However, you will see Amazon's going to trot out a ton of customers using their RA3 managed storage and their flash. I think it's the DC two piece. They have a ton of action in the marketplace because it's just so easy. It's interesting one of the comments, you asked this yesterday, was with regard to separating compute from storage, which of course it's Snowflakes they basically invented it, it was one of their climbs to fame. The comment was what AWS has done to separate compute from storage for Redshift is largely a bolt on. Which I thought that was an interesting comment. I've had some other comments. My friend George Gilbert said, "Hey, despite claims to the contrary, AWS still hasn't separated storage from compute. What they have is really primitive." We got to dig into that some more, but you're seeing some data points that suggest there's copycatting going on. May not be as functional, but at the same time, Erik, like I was saying good enough is maybe good enough in this space. >> Yeah, and especially with the enterprise, right? You see what Microsoft has done. Their technology is not as good as all the niche players, but it's good enough and I already have a Microsoft license. So, (laughs) you know why am I going to move off of it. But I want to get back to the comment you mentioned too about that particular gentleman who made that comment about RedShift, their separation is really more of a bolt on than a true offering. It's interesting because I know who these people are behind the scenes and he has a very strong relationship with AWS. So it was interesting to me that in the panel yesterday he said he switched from Redshift to Snowflake because of that and some other functionality issues. So there is no doubt from the end users that are buying this. And he's again a fortune 100 financial organization. Not the same one we mentioned. That's a different one. But again, a fortune 100 well known financials organization. He switched from AWS to Snowflake. So there is no doubt that right now they have the technological lead. And when you look at our ETR data platform, we have that adoption reasoning slide that you show. When you look at the number one reason that people are adopting Snowflake is their feature set of technological lead. They have that lead now. They have to maintain it. Now, another thing to bring up on this to think about is when you have large data sets like this, and as we're moving forward, you need to have machine learning capabilities layered into it, right? So they need to make sure that they're playing nicely with that. And now you could go open source with the Apache suite, but Google is doing so well with BigQuery and so well with their machine learning aspects. And although they don't speak enterprise well, they don't sell to the enterprise well, that's changing. I think they're somebody to really keep an eye on because their machine learning capabilities that are layered into the BigQuery are impressive. Now, of course, Microsoft Azure has Databricks. They're layering that in, but this is an area where I think you're going to see maybe what's next. You have to have machine learning capabilities out of the box if you're going to do data as a service. Right now Snowflake doesn't really have that. Some of the other ones do. So I had one of my guest panelist basically say to me, because of that, they ended up going with Google BigQuery because he was able to run a machine learning algorithm within hours of getting set up. Within hours. And he said that that kind of capability out of the box is what people are going to have to use going forward. So that's another thing we should dive into a little bit more. >> Let's get into that right now. Let's bring up the next slide which shows net score. Remember this is spending momentum across the major cloud players and plus Snowflake. So you've got Snowflake on the left, Google, AWS and Microsoft. And it's showing three survey timeframes last October, April 20, which is right in the middle of the pandemic. And then the most recent survey which has just taken place this month in July. And you can see Snowflake very, very high scores. Actually improving from the last October survey. Google, lower net scores, but still very strong. Want to come back to that and pick up on your comments. AWS dipping a little bit. I think what's happening here, we saw this yesterday with AWS's results. 30% growth. Awesome. Slight miss on the revenue side for AWS, but look, I mean massive. And they're so exposed to so many industries. So some of their industries have been pretty hard hit. Microsoft pretty interesting. A little softness there. But one of the things I wanted to pick up on Erik, when you're talking about Google and BigQuery and it's ML out of the box was what we heard from a lot of the VENN participants. There's no question about it that Google technically I would say is one of Snowflake's biggest competitors because it's cloud native. Remember >> Yep. >> AWS did a license one time. License deal with PowerShell and had a sort of refactor the thing to be cloud native. And of course we know what's happening with Microsoft. They basically were on-prem and then they put stuff in the cloud and then all the updates happen in the cloud. And then they pushed to on-prem. But they have that what Frank Slootman calls that halfway house, but BigQuery no question technically is very, very solid. But again, you see Snowflake right now anyway outpacing these guys in terms of momentum. >> Snowflake is out outpacing everyone (laughs) across our entire survey universe. It really is impressive to see. And one of the things that they have going for them is they can connect all three. It's that multi-cloud ability, right? That portability that they bring to you is such an important piece for today's modern CIO as data architects. They don't want vendor lock-in. They are afraid of vendor lock-in. And this ability to make their data portable and to do that with ease and the flexibility that they offer is a huge advantage right now. However, I think you're a hundred percent right. Google has been so focused on the engineering side and never really focusing on the enterprise sales side. That is why they're playing catch up. I think they can catch up. They're bringing in some really important enterprise salespeople with experience. They're starting to learn how to talk to enterprise, how to sell, how to support. And nobody can really doubt their engineering. How many open sources have they given us, right? They invented Kubernetes and the entire container space. No one's really going to compete with them on that side if they learn how to sell it and support it. Yeah, right now they're behind. They're a distant third. Don't get me wrong. From a pure hosted ability, AWS is number one. Microsoft is yours. Sometimes it looks like it's number one, but you have to recognize that a lot of that is because of simply they're hosted 365. It's a SAS app. It's not a true cloud type of infrastructure as a service. But Google is a distant third, but their technology is really, really great. And their ability to catch up is there. And like you said, in the panels we were hearing a lot about their machine learning capability is right out of the box. And that's where this is going. What's the point of having this huge data if you're not going to be supporting it on new application architecture. And all of those applications require machine learning. >> Awesome. So we're. And I totally agree with what you're saying about Google. They just don't have it figured out how to sell the enterprise yet. And a hundred percent AWS has the best cloud. I mean, hands down. But a very, very competitive market as we heard yesterday in front of Congress. Now we're on the point about, can Snowflake compete with the big cloud players? I want to show one more data point. So let's bring up, this is the same chart as we showed before, but it's new adoptions. And this is really telling. >> Yeah. >> You can see Snowflake with 34% in the yellow, new adoptions, down yes from previous surveys, but still significantly higher than the other players. Interesting to see Google showing momentum on new adoptions, AWS down on new adoptions. And again, exposed to a lot of industries that have been hard hit. And Microsoft actually quite low on new adoption. So this is very impressive for Snowflake. And I want to talk about the multi-cloud strategy now Erik. This came up a lot. The VENN participants who are sort of fans of Snowflake said three things: It was really the flexibility, the security which is really interesting to me. And a lot of that had to do with the flexibility. The ability to easily set up roles and not have to waste a lot of time wrangling. And then the third was multi-cloud. And that was really something that came through heavily in the VENN. Didn't it? >> It really did. And again, I think it just comes down to, I don't think you can ever overstate how afraid these guys are of vendor lock-in. They can't have it. They don't want it. And it's best practice to make sure your sensitive information is being kind of spread out a little bit. We all know that people don't trust Bezos. So if you're in certain industries, you're not going to use AWS at all, right? So yeah, this ability to have your data portability through multi-cloud is the number one reason I think people start looking at Snowflake. And to go to your point about the adoptions, it's very telling and it bodes well for them going forward. Most of the things that we're seeing right now are net new workloads. So let's go again back to the legacy side that we were talking about, the Teradatas, IBMs, Oracles. They still have the monolithic applications and the data that needs to support that, right? Like an old ERP type of thing. But anyone who's now building a new application, bringing something new to market, it's all net new workloads. There is no net new workload that is going to go to SAP or IBM. It's not going to happen. The net new workloads are going to the cloud. And that's why when you switch from net score to adoption, you see Snowflake really stand out because this is about new adoption for net new workloads. And that's really where they're driving everything. So I would just say that as this continues, as data as a service continues, I think Snowflake's only going to gain more and more share for all the reasons you stated. Now get back to your comment about security. I was shocked by that. I really was. I did not expect these guys to say, "Oh, no. Snowflake enterprise security not a concern." So two panels ago, a gentleman from a fortune 100 financials said, "Listen, it's very difficult to get us to sign off on something for security. Snowflake is past it, it is enterprise ready, and we are going full steam ahead." Once they got that go ahead, there was no turning back. We gave it to our DevOps guys, we gave it to everyone and said, "Run with it." So, when a company that's big, I believe their fortune rank is 28. (laughs) So when a company that big says, "Yeah, you've got the green light. That we were okay with the internal compliance aspect, we're okay with the security aspect, this gives us multi-cloud portability, this gives us flexibility, ease of use." Honestly there's a really long runway ahead for Snowflake. >> Yeah, so the big question I have around the multi-cloud piece and I totally and I've been on record saying, "Look, if you're going looking for an agnostic multi-cloud, you're probably not going to go with the cloud vendor." (laughs) But I've also said that I think multi-cloud to date anyway has largely been a symptom as opposed to a strategy, but that's changing. But to your point about lock-in and also I think people are maybe looking at doing things across clouds, but I think that certainly it expands Snowflake's TAM and we're going to talk about that because they support multiple clouds and they're going to be the best at that. That's a mandate for them. The question I have is how much of complex joining are you going to be doing across clouds? And is that something that is just going to be too latency intensive? Is that really Snowflake's expertise? You're really trying to build that data layer. You're probably going to maybe use some kind of Postgres database for that. >> Right. >> I don't know. I need to dig into that, but that would be an opportunity from a TAM standpoint. I just don't know how real that is. >> Yeah, unfortunately I'm going to just be honest with this one. I don't think I have great expertise there and I wouldn't want to lead anyone a wrong direction. But from what I've heard from some of my VENN interview subjects, this is happening. So the data portability needs to be agnostic to the cloud. I do think that when you're saying, are there going to be real complex kind of workloads and applications? Yes, the answer is yes. And I think a lot of that has to do with some of the container architecture as well, right? If I can just pull data from one spot, spin it up for as long as I need and then just get rid of that container, that ethereal layer of compute. It doesn't matter where the cloud lies. It really doesn't. I do think that multi-cloud is the way of the future. I know that the container workloads right now in the enterprise are still very small. I've heard people say like, "Yeah, I'm kicking the tires. We got 5%." That's going to grow. And if Snowflake can make themselves an integral part of that, then yes. I think that's one of those things where, I remember the guy said, "Snowflake has to continue to innovate. They have to find a way to grow this TAM." This is an area where they can do so. I think you're right about that, but as far as my expertise, on this one I'm going to be honest with you and say, I don't want to answer incorrectly. So you and I need to dig in a little bit on this one. >> Yeah, as it relates to question four, what's the viability of Snowflake's multi-cloud strategy? I'll say unquestionably supporting multiple clouds, very viable. Whether or not portability across clouds, multi-cloud joins, et cetera, TBD. So we'll keep digging into that. The last thing I want to focus on here is the last question, does Snowflake's TAM justify its $20 billion valuation? And you think about the data pipeline. You go from data acquisition to data prep. I mean, that really is where Snowflake shines. And then of course there's analysis. You've got to bring in EMI or AI and ML tools. That's not Snowflake's strength. And then you're obviously preparing that, serving that up to the business, visualization. So there's potential adjacencies that they could get into that they may or may not decide to. But so we put together this next chart which is kind of the TAM expansion opportunity. And I just want to briefly go through it. We published this stuff so you can go and look at all the fine print, but it's kind of starts with the data lake disruption. You called it data swamp before. The Hadoop no schema on, right? Basically the ROI of Hadoop became reduction of investment as my friend Abby Meadow would say. But so they're kind of disrupting that data lake which really was a failure. And then really going after that enterprise data warehouse which is kind of I have it here as a 10 billion. It's actually bigger than that. It's probably more like a $20 billion market. I'll update this slide. And then really what Snowflake is trying to do is be data as a service. A data layer across data stores, across clouds, really make it easy to ingest and prepare data and then serve the business with insights. And then ultimately this huge TAM around automated decision making, real-time analytics, automated business processes. I mean, that is potentially an enormous market. We got a couple of hundred billion. I mean, just huge. Your thoughts on their TAM? >> I agree. I'm not worried about their TAM and one of the reasons why as I mentioned before, they are coming out with a whole lot of cash. (laughs) This is going to be a red hot IPO. They are going to have a lot of money to spend. And look at their management team. Who is leading the way? A very successful, wise, intelligent, acquisitive type of CEO. I think there is going to be M&A activity, and I believe that M&A activity is going to be 100% for the mindset of growing their TAM. The entire world is moving to data as a service. So let's take as a backdrop. I'm going to go back to the panel we did yesterday. The first question we asked was, there was an understanding or a theory that when the virus pandemic hit, people wouldn't be taking on any sort of net new architecture. They're like, "Okay, I have Teradata, I have IBM. Let's just make sure the lights are on. Let's stick with it." Every single person I've asked, they're just now eight different experts, said to us, "Oh, no. Oh, no, no." There is the virus pandemic, the shift from work from home. Everything we're seeing right now has only accelerated and advanced our data as a service strategy in the cloud. We are building for scale, adopting cloud for data initiatives. So, across the board they have a great backdrop. So that's going to only continue, right? This is very new. We're in the early innings of this. So for their TAM, that's great because that's the core of what they do. Now on top of it you mentioned the type of things about, yeah, right now they don't have great machine learning. That could easily be acquired and built in. Right now they don't have an analytics layer. I for one would love to see these guys talk to Alteryx. Alteryx is red hot. We're seeing great data and great feedback on them. If they could do that business intelligence, that analytics layer on top of it, the entire suite as a service, I mean, come on. (laughs) Their TAM is expanding in my opinion. >> Yeah, your point about their leadership is right on. And I interviewed Frank Slootman right in the heart of the pandemic >> So impressed. >> and he said, "I'm investing in engineering almost sight unseen. More circumspect around sales." But I will caution people. That a lot of people I think see what Slootman did with ServiceNow. And he came into ServiceNow. I have to tell you. It was they didn't have their unit economics right, they didn't have their sales model and marketing model. He cleaned that up. Took it from 120 million to 1.2 billion and really did an amazing job. People are looking for a repeat here. This is a totally different situation. ServiceNow drove a truck through BMCs install base and with IT help desk and then created this brilliant TAM expansion. Let's learn and expand model. This is much different here. And Slootman also told me that he's a situational CEO. He doesn't have a playbook. And so that's what is most impressive and interesting about this. He's now up against the biggest competitors in the world: AWS, Google and Microsoft and dozens of other smaller startups that have raised a lot of money. Look at the company like Yellowbrick. They've raised I don't know $180 million. They've got a great team. Google, IBM, et cetera. So it's going to be really, really fun to watch. I'm super excited, Erik, but I'll tell you the data right now suggest they've got a great tailwind and if they can continue to execute, this is going to be really fun to watch. >> Yeah, certainly. I mean, when you come out and you are as impressive as Snowflake is, you get a target on your back. There's no doubt about it, right? So we said that they basically created the data as a service. That's going to invite competition. There's no doubt about it. And Yellowbrick is one that came up in the panel yesterday about one of our CIOs were doing a proof of concept with them. We had about seven others mentioned as well that are startups that are in this space. However, none of them despite their great valuation and their great funding are going to have the kind of money and the market lead that Slootman is going to have which Snowflake has as this comes out. And what we're seeing in Congress right now with some antitrust scrutiny around the large data that's being collected by AWS as your Google, I'm not going to bet against this guy either. Right now I think he's got a lot of opportunity, there's a lot of additional layers and because he can basically develop this as a suite service, I think there's a lot of great opportunity ahead for this company. >> Yeah, and I guarantee that he understands well that customer acquisition cost and the lifetime value of the customer, the retention rates. Those are all things that he and Mike Scarpelli, his CFO learned at ServiceNow. Not learned, perfected. (Erik laughs) Well Erik, really great conversation, awesome data. It's always a pleasure having you on. Thank you so much, my friend. I really appreciate it. >> I appreciate talking to you too. We'll do it again soon. And stay safe everyone out there. >> All right, and thank you for watching everybody this episode of "CUBE Insights" powered by ETR. This is Dave Vellante, and we'll see you next time. (soft music)

(upbeat music) >> Narrator: From theCUBE Studios in Palo Alto and Boston, connecting with thought leaders all around the world, this is theCUBE Coversation. >> All right everybody, this is Dave Vellante and welcome to this special CUBE Conversation. I first met Frank Slootman in 2007 when he was the CEO of Data Domain. Back then he was the CEO of a disruptive company and still is. Data Domain, believe or not back then, was actually replacing tape drives as the primary mechanism for backup. Yes, believe it or not, it used to be tape. Fast forward several years later, I met Frank again at VMworld when he had become the CEO of ServiceNow. At the time ServiceNow was a small company, about 100 plus million dollars. Frank and his team took that company to 1.2 billion. And Gartner, at the time of IPO said "you know, this doesn't make sense. "It's a small market, it's a very narrow help desk market, "it's maybe a couple billion dollars." The vision of Slootman and his team was to really expand the total available market and execute like a laser. Which they did and today, ServiceNow a very, very successful company. Snowflake first came into my line of sight in 2015 when SiliconANGLE wrote an article, "Why Snowflake is Better "Than Amazon Redshift, Re-imagining Data". Well last year Frank Slootman joined Snowflake, another disruptive company. And he's here today to talk about how Snowflake is really participating in this COVID-19 crisis. And I really want to share some of Frank's insights and leadership principles, Frank great to see you, thanks for coming on. >> Yeah, thanks for having us Dave. >> So when I first reported earlier this year on Snowflake and shared some data with the community, you reached back out to me and said "Dave, I want to just share with you. "I am not a playbook CEO, I am a situational CEO. "This is what I learned in the military." So Frank, this COVID-19 situation was thrown at you, it's a black swan, what was your first move as a leader? >> Well, my first move is let's not overreact. Take a deep breath. Let's really examine what we know. Let's not jump to conclusions, let's not try to project things that we're not capable of projecting. That's hard because we tend to have sort of levels of certainty about what's going to happen in the week, in the next month and so on and all of a sudden that's out of the window. It creates enormous anxiety with people. So in other words you got to sort of reset to okay, what do we know, what can we do, what do we control? And not let our minds sort of go out of control. So I talk to our people all the time about maintain a sense of normalcy, focus on the work, stay in the moment and by the way, turn the newsfeed off, right, because the hysteria you get fed through the media is really not helpful, right? So just cool down and focus on what we still can do. And then I think then everybody takes a deep breath and we just go back to work. I mean, we're in this mode now for three weeks and I can tell you, I'm on teleconferencing calls, whatever, eight, nine hours a day. Prospects, customers, all over the world. Pretty much what I was doing before except I'm not traveling right now. So it's not, >> Yeah, so it sounds clear-- >> Not that different than what it was before. (laughs) >> It sounds very Bill Belichickian, you know? >> Yeah. >> Focus on those things of which you can control. When you were running ServiceNow I really learned it from you and of course Mike Scarpelli, your then and current CFO about the importance of transparency. And I'm interested in how you're communicating, it sounds like you're doing some very similar things but have you changed the way in which you've communicated to your team, your internal employees at all? >> We're communicating much more. Because we can no longer rely on sort of running into people here, there and everywhere. So we have to be much more purposeful about communications. For example, I mean I send an email out to the entire company on Monday morning. And it's kind of a bunch of anecdotes. Just to bring the connection back, the normalcy. It just helps people get connected back to the mothership and like well, things are still going on. We're still talking in the way we always used to be. And that really helps and I also, I check in with people a lot more, I ask all of our leadership to constantly check in with people because you can't assume that everybody is okay, you can't be out of sight, out of mind. So we need to be more purposeful in reaching out and communicating with people than we were previously. >> And a lot of people obviously concerned about their jobs. Have you sort of communicated, what have you communicated to employees about layoffs? I mean, you guys just did a large raise just before all this, your timing was kind of impeccable. But what have you communicated in that regard? >> I've said, there's no layoffs on our radar, number one. Number two, we are hiring. And number three is we have a higher level of scrutiny on the hires that we're making. And I am very transparent. In other words I tell people look, I prioritize the roles that are closest to the direct train of the business. Right, it's kind of common sense. But I wanted to make sure that this is how we're thinking about it. There are some roles that are more postponable than others. I'm hiring in engineering without any reservation because that is the long term strategic interest of the company. One the sales side, I want to know that sales leaders know how to convert to yields, that we're not just sort of bringing capacity online. And the leadership is not convinced or confident that they can convert to yield. So there's a little bit finer level of scrutiny on the hiring. But by and large, it's not that different. There's this saying out there that we should suspend all non-essential spending and hiring, I'm like you should always do that. Right? I mean what's different today? (both laugh) If it's non-essential, why do it, right? So all of this comes back to this is probably how we should operate anyways, yep. >> I want to talk a little bit about the tech behind Snowflake. I'm very sensitive when CEOs come on my program to make sure that we're not, I'm not trying to bait CEOs into ambulance chasing, that's not what it's about. But I do want to share with our community kind of what's new, what's changed and how companies like Snowflake are participating in this crisis. And in particular, we've been reporting for awhile, if you guys bring up that first slide. That the innovation in the industry is really no longer about Moore's Law. It's really shifted. There's a new, what we call an innovation cocktail in the business and we've collected all this data over the last 10 years. With Hadoop and other distributed data and now we have Edge Data, et cetera, there's this huge trove of data. And now AI is becoming real, it's becoming much more economical. So applying machine intelligence to this data and then the Cloud allows us to do this at scale. It allows us to bring in more data sources. It brings an agility in. So I wonder if you could talk about sort of this premise and how you guys fit. >> Yeah, I would start off by reordering the sequence and saying Cloud's number one. That is foundational. That helps us bring scale to data that we never had to number two, it helps us bring computational power to data at levels we've never had before. And that just means that queries and workloads can complete orders of magnitude faster than they ever could before. And that introduces concepts like the time value of data, right? The faster you get it, the more impactful and powerful it is. I do agree, I view AI as sort of the next generation of analytics. Instead of using data to inform people, we're using data to drive processes and businesses directly, right? So I'm agreeing obviously with these strengths because we're the principal beneficiaries and drivers of these platforms. >> Well when we talked about earlier this year about Snowflake, we really brought up the notion that you guys were one of the first if not the first. And guys, bring back Frank, I got to see him. (Frank chuckles) One of the first to really sort of separate the notion of being able to scale, compute independent of storage. And that brought not only economics but it brought flexibility. So you've got this Cloud-native database. Again, what caught my attention in that Redshift article we wrote is essentially for our audience, Redshift was based on ParAccel. Amazon did a great job of really sort of making that a Cloud database but it really wasn't born in the Cloud and that's sort of the advantage of Snowflake. So that architectural approach is starting to really take hold. So I want to give an example. Guys if you bring up the next chart. This is an example of a system that I've been using since early January when I saw this COVID come out. Somebody texted me this. And it's the Johns Hopkins dataset, it's awesome. It shows you, go around the map, you can follow it, it's pretty close to real time. And it's quite good. But the problem is, all right thank you guys. The problem is that when I started to look at, I wanted to get into sort of a more granular view of the counties. And I couldn't do that. So guys bring up the next slide if you would. So what I did was I searched around and I found a New York Times GitHub data instance. And you can see it in the top left here. And basically it was a CSV. And notice what it says, it says we can't make this file beautiful and searchable because it's essentially too big. And then I ran into what you guys are doing with Star Schema, Star Schema's a data company. And essentially you guys made the notion that look, the Johns Hopkins dataset as great as it is it's not sort of ready for analytics, it's got to be cleaned, et cetera. And so I want you to talk about that a little bit. Guys, if you could bring Frank back. And share with us what you guys have done with Star Schema and how that's helping understand COVID-19 and its progression. >> Yeah, one of the really cool concepts I've felt about Snowflake is what we call the data sharing architecture. And what that really means is that if you and I both have Snowflake accounts, even though we work for different institutions, we can share data optics, tables, schema, whatever they are with each other. And you can process against that in place if they are residing in a local, to your own platform. We have taken that concept from private also to public. So that data providers like Star Schema can list their datasets, because they're a data company, so obviously it's in their business interest to allow this data to be profiled and to be accessible by the Snowflake community. And this data is what we call analytics ready. It is instantly accessible. It is also continually updated, you have to do nothing. It's augmented with incremental data and then our Snowflake users can just combine this data with supply chain, with economic data, with internal operating data and so on. And we got a very strong reaction from our customer base because they're like "man, you're saving us weeks "if not months just getting prepared to start to do an al, let alone doing them." Right? Because the data is analytics ready and they have to do literally nothing. I mean in other words if they ask us for it in the morning, in the afternoon they'll be running workloads again. Right, and then combining it with their own data. >> Yeah, so I should point out that that New York Times GitHub dataset that I showed you, it's a couple of days behind. We're talking here about near realtime, or as close as realtime as you can get, is that right? >> Yep. Yeah, every day it gets updated. >> So the other thing, one of the things we've been reporting, and Frank I wondered if you could comment on this, is this new emerging workloads in the Cloud. We've been reporting on this for a couple of years. The first generation of Cloud was IS, was really about compute, storage, some database infrastructure. But really now what we're seeing is these analytic data stores where the valuable data is sitting and much of it is in the Cloud and bringing machine intelligence and data science capabilities to that, to allow for this realtime or near realtime analysis. And that is a new, emerging workload that is really gaining a lot of steam as these companies try to go to this so-called digital transformation. Your comments on that. >> Yeah, we refer to that as the emergence or the rise of the data Cloud. If you look at the Cloud landscape, we're all very familiar with the infrastructure clouds. AWS and Azure and GCP and so on, it's just massive storage and servers. And obviously there's data locked in to those infrastructure clouds as well. We've been familiar for it for 10, 20 years now with application clouds, notably Salesforce but obviously Workday, ServiceNow, SAP and so on, they also have data in them, right? But now you're seeing that people are unsiloing the data. This is super important. Because as long as the data is locked in these infrastructure clouds, in these application clouds, we can't do the things that we need to do with it, right? We have to unsilo it to allow the scale of querying and execution against that data. And you don't see that any more clear that you do right now during this meltdown that we're experiencing. >> Okay so I learned long ago Frank not to argue with you but I want to push you on something. (Frank laughs) So I'm not trying to be argumentative. But one of those silos is on-prem. I've heard you talk about "look, we're a Cloud company. "We're Cloud first, we're Cloud only. "We're not going to do an on-prem version." But some of that data lives on-prem. There are companies out there that are saying "hey, we separate compute and storage too, "we run in the Cloud. "But we also run on-prem, that's our big differentiator." Your thoughts on that. >> Yeah, we burnt the ship behind us. Okay, we're not doing this endless hedging that people have done for 20 years, sort of keeping a leg in both worlds. Forget it, this will only work in the public Cloud. Because this is how the utility model works, right? I think everybody is coming to this realization, right? I mean excuses are running out at this point. We think that it'll, people will come to the public Cloud a lot sooner than we will ever come to the private Cloud. It's not that we can't run on a private cloud, it just diminishes the potential and the value that we bring. >> So as sort of mentioned in my intro, you have always been at the forefront of disruption. And you think about digital transformation. You know Frank we go to all of these events, it used to be physical and now we're doing theCUBE digital. And so everybody talks about digital transformation. CEOs get up, they talk about how they're helping their customers move to digital. But the reality is is when you actually talk to businesses, there was a lot of complacency. "Hey, this isn't really going to happen in my lifetime" or "we're doing pretty well." Or maybe the CEO might be committed but it doesn't necessarily trickle down to the P&L managers who have an update. One of the things that we've been talking about is COVID-19 is going to accelerate that digital transformation and make it a mandate. You're seeing it obviously in retail play out and a number of other industries, supply chains are, this has wreaked havoc on supply chains. And so there's going to be a rethinking. What are your thoughts on the acceleration of digital transformation? >> Well obviously the crisis that we're experiencing is obviously an enormous catalyst for digital transformation and everything that that entails. And what that means and I think as a industry we're just victims of inertia. Right, I mean haven't understood for 20 years why education, both K through 12 but also higher ed, why they're so brick and mortar bound and the way they're doing things, right? And we could massively scale and drop the cost of education by going digital. Now we're forced into it and everybody's like "wow, "this is not bad." You're right, it isn't, right but we haven't so the economics, the economic imperative hasn't really set in but it is now. So these are all great things. Having said that, there are also limits to digital transformation. And I'm sort of experiencing that right now, being on video calls all day. And oftentimes people I've never met before, right? There's still a barrier there, right? It's not like digital can replace absolutely everything. And that is just not true, right? I mean there's some level of filter that just doesn't happen when you're digital. So there's still a need for people to be in the same place. I don't want to sort of over rotate on this concept, that like okay, from here on out we're all going to be on the wires, that's not the way it will be. >> Yeah, be balanced. So earlier you made a comment, that "we should never "be spending on non-essential items". And so you've seen (Frank laughs) back in 2008 you saw the Rest in Peace good times, you've seen the black swan memos that go out. I assume that, I mean you're a very successful investor as well, you've done a couple of stints in the VC community. What are you seeing in the Valley in regard to investments, will investments continue, will we continue to feed innovation, what's your sense of that? Well this is another wake up call. Because in Silicon Valley there's way too much money. There's certainly a lot of ideas but there's not a lot of people that can execute on it. So what happens is a lot of things get funded and the execution is either no good or it's just not a valid opportunity. And when you go through a downturn like this you're finding out that those businesses are not going to make it. I mean when the tide is running out, only the strongest players are going to survive that. It's almost a natural selection process that happens from time to time. It's not necessarily a bad thing because people get reallocated. I mean Silicon Valley is basically one giant beehive, right? I mean we're constantly repurposing money and people and talent and so on. And that's actually good because if an idea is not worth in investing in, let's not do it. Let's repurpose those resources in places where it has merit, where it has viability. >> Well Frank, I want to thank you for coming on. Look, I mean you don't have to do this. You could've retired long, long ago but having leaders like you in place in these times of crisis, but even when in good times to lead companies, inspire people. And we really appreciate what you do for companies, for your employees, for your customers and certainly for our community, so thanks again, I really appreciate it. >> Happy to do it, thanks Dave. >> All right and thank you for watching everybody, Dave Vellante for theCUBE, we will see you next time. (upbeat music)

>> Announcer: Live from Las Vegas, it's theCUBE. Covering UiPath Forward Americas 2019. Brought to you by UiPath. >> We're back, UiPath Forward III from Las Vegas at the Bellagio, you're watching theCUBE, the leader in live tech coverage, my name is Dave Vellante. Marie Myers is here, she's the CFO of the rocket-ship known as UiPath. Welcome to theCUBE, thanks for coming on. >> Thank you. >> So, wow. You must be under a lot of pressure to keep the ship moving in a fast direction. But I was just talking to Daniel, he said, you know, when we started the company, we had basic finance systems, kind of like every other startup, but that obviously has changed, so. Well, congratulations, I know you got a lot more work to do but how are you spending your time these days? >> Doing a lot of work, is what I would say. So, as you've kind of seen, that tremendous growth, so huge pressure to just scale the company and ensure that the company has the ability to meet the growth that we're experiencing. So right now I've been really focused on building the operational backbone and actually building a lot of robots for UiPath, actually. That's something I wasn't expecting but came into the role and really help build our own ecosystem around robotics as well. >> I was asking Daniel how much dogfooding, champagne sipping you guys have done and, if it has contributed to the growth and it sounds like quite a bit, actually. >> Absolutely, I'd say we're really hitting the gas pedal right now in terms of building out our own competency and kind of to your point, eating the dog food, drinking the champagne and starting to push the envelope on how we actually use automation and AI to really scale our own business. You asked me where I was spending my time and where I was focused, I literally moved my family to Bucharest for the summer to really focus in on helping to scale the infrastructure. >> So, CFOs usually have a philosophy, a framework, that they like to work with. Obviously you got to stay flexible. How would you describe your philosophy as to how you'd like to manage this company? >> Well clearly, for us we're at an incredible stage of momentum in the market, and the ability for us to continue to build distance in terms of being number one is critical, so in terms of strategy, supporting that number one position, being agile. Able to scale for growth and ultimately do so profitably is certainly the ambition that we have in mind. And that requires turning a lot of different dials, right? And being able to turn them at the right time but at the same time ensure that we've got enough, let's just say, cushion underneath to scale that growth, because the growth is happening very very quickly. >> So CFOs, today's CFO is definitely, I would say more strategic than when I first got into the business, we used to joke that the cheap financial officer. But, I think of CFOs that I really admire, guys like Mike Scarpelli, who was at ServiceNow, now he's at Snowflake. I think he was at Data Domain too, Tom Sweet at Dell, whole different example, they're doing crazy financial engineering. But, much more of a strategic focus. Want to throw gasoline in the fire, and drive growth, but at the same time, thinking about efficiency, so. How have you seen that role evolving and how does that apply to what you guys are doing? >> So I think your comments about the role of the CFO are really right on, I mean, what's perhaps even more interesting, I think, for CFOs that are in software and maybe in a space like we're in is that you ultimately also get involved in being an advocate for your business. In robotics process automation, almost 40% of the first use cases are in finance. So, you're out there supporting the business case with other CFOs who want to understand how does efficiency really, why they should buy from us and what's the business proposition? So you've got to balance the demands of the business with running the business and so, I think that does give you the very unique lens because you understand how this product, to your point, drives operational efficiency. And obviously all CFOs really care, that's right on the list of the top three. >> You know, that's interesting, Marie, because the tech company CIOs are always being pulled in. Because they're early users of some technology. It's not common anyway, that the CFO is one of the lead sales go-to people but it sounds like it is in your case. How much time do you spend in the field? >> I try to balance my time, because you could get pulled very heavily I feel because of the nature of our business into that but I think because robotics process automation has been a key entry point into finance, there's a lot of work for CFOs to do there. So I try to balance my time, but it is, I think, a very important part of our own learning for our company, we get a lot of feedback from our customers. And, even helps me in my role because I get use cases from customers that I apply internally to drive our own efficiency. >> Well, plus, you know, you can see what's happening in the field, you can feel the pain of the sales reps, you can tell which ones are kind of sandbagging, >> You're right, absolutely! >> 'cause they're all sandbaggers! >> You're right about that, so it's been great being at this event, I know a lot of the great reps and so you really understand, you've got a good pulse on what's happening in terms of the business and where the risks are in the quarter. So that's one advantage. >> What're the metrics that you're driving? I mean, obviously the conventional ones, throw those in, but. >> Yeah, I mean obviously productivity, very important for us, we've got a lot of folks we've hired so really understanding what that productivity looks like. The usual cast of characters, AR. Customer acquisition costs, really focused on, what is that first customer costing and then how we're managing our land and expand. What our upsell looks like, so I think the usual cast of characters. >> And then eventually, as all these M and As happen, you'll get cohort sales coming in and the like. So, is everything that you guys sell recognized on a deferred revenue basis? >> No, we're in the midst of converting to 606 right now so we're kind of like subscription one year on prem. So pretty conventional software, red rack. >> Okay, but as you move to the cloud model. >> That gives us a different model, yeah. And we have it, we're just starting that journey. >> It seems like, you see different models. You know, Adobe bit the bullet, Splunk sort of peeled the Band-Aid off very slowly and they both can work. But it seems like a lot of the, I'll call it game, maybe it's the wrong word. But that's what came to mind, is educating the street. On that metric, on that transition. You certainly see it, for instance, in Oracle's case. Putting a lot of emphasis on helping the street understand that transition. That's not your primary focus right now, I'm sure you're spending some time with the analysts, I saw many buzzing around here. >> There was a lot here in the last few days. >> Dave: Yeah, they all want your business! >> (she laughs) They all want your business! I got a lot of texts in the last 48 hours. >> Well, it's an exciting time. And you know, eventually you guys are going to do an IPO and why wouldn't they? Be smart to be here, but what are your thoughts on that? Is that something that you really don't pay attention to right now, are you preparing for that? >> I'd say we're just getting total transparency, we're just moving through 606. So we're digesting that transition first and we're just starting down the whole cloud migration path. So as we start to think that through it's going to be I'd say a priority for 2020. And it's going to be important, I mean, for this business we expect, who's to say what the uptake rate is as customers move to the cloud? But I suspect it's going to be fairly aggressive in our business just because of the nature of bots and how customers think about bots. >> Yeah, so, Daniel said on the previous segment, he said, look, IPO's in our future, probably not 2020, we need at least a year to get our act together. So we're looking at 2021 but it depends on what the climate is, et cetera. My question is, and I've talked to, I see you orange here, Pure Storage is a high flyer in the infrastructure business, they're all orange, so they paint the town orange. >> Seems orange is very popular right now. >> It's a great color, recognizable. But I was talking about, they're all about growth. Not about optimizing profit right now and that's the right play because the street's rewarding growth. You guys, clearly, all about growth. >> We've got the growth story buttoned down, yeah. >> Yeah, you've got that down. But you still want to put gas on the fire, right? So, right now you're still optimized for growth. >> Absolutely, you see what's happening here, right? So, yeah, I think that kind of-- >> And you're well capitalized, so that's not the issue. So the strategy, I presume, is keep growing, get escape velocity, because, the company that gets escape velocity and is the leader in this business, you guys are the leader right now. You're not going to rest, you're going to stay paranoid, I'm sure. But the one that leads is going to make the most money. That always happens. >> Well, extending that leadership role is part of our core strategy, right? Maintaining number one, putting distance. I think you've seen the products that we announced here the last couple of days, adding to the portfolio or giving us incremental TAM so we can grow across the space. I think growing both down the stack and up the stack is critically important for us as we think forward to the future, too, right? We just don't want to be a pure robotics process automation company. We want to look across AI, down the stack into process mining. >> How do you think about your TAM? >> That's a great question. So I've been studying up a little over the last few days preparing for the board meeting tomorrow. I mean, robotics process automation, TAM next year is about two and a half, or two and change in terms of revenue, two billion. I've been looking at it a lot more broadly because I do believe that it is defined today quite narrowly in terms of very traditional RPE. And that started very much in the back office. As we've spread automation and kind of created that platform mentality, the TAM becomes additive. You've got now the process mining TAM which I think we can clearly start to play in that space. And then also the BPMs and now, obviously, AI. So, I was just doing our own back of the envelope in the last few days and you can get, easily, I think now, above that $10 billion mark and it depends on how you start to think about AI as you go forward and that just adds incremental TAM. >> Well, and you throw in services, you're already there. >> Yeah, exactly. >> Probably be there by next year. I think generally, I'll just give you my quick opinion. I think the market's undercounting the TAM potential. And I haven't done a detailed TAM analysis of the, I don't even want to say RPA 'cause that's the core. >> Exactly. >> But I could see this thing expanding dramatically, we talked about cohort sales. Just talking to customers, you're like one to 2% penetrated and there's so many more use cases. As you bring in AI, which, I really think of AI as a horizontal. But if you start applying AI and bringing in automation as an adjacency to you guys, I think that TAM are going to be many many tens of billions beyond what you're thinking. >> That's exactly how I like to think about it, of course, I go back to my IDC friends and try to use some of their benchmarks. But I think they're somewhat conservative. And I think as the market matures and people understand the breadth of the category, I just think that when RPA started it was kind of pigeonholed as a back office opportunity. >> Yeah, I mean, I was at IDC for a long time and we were really crappy at long-term TAM analysis. And you saw it with, Craig LeClair was awesome today. >> Yeah, I love Craig. >> Love him, fantastic. >> Very witty. >> His forecast, however, and same with IDC, we were there, we used to do these linear forecasts and that's not how these markets grow. It's an ogive and a steep S-curve and I think that's my prediction. >> Marie: I couldn't agree more with you. >> We heard predictions this morning, I summarized the predictions and gave my own. And that's one that I see. I'd like to see a longer-term forecast. Maybe we'll work on that. >> Well, we'd love that, I think that's going to be important. I think, part of it's just the maturity of this category. And as folks are starting to understand the breadth of the application, if you think about it, that's why there was so much early work in finance. Now you're starting to see the business spread across the enterprise, right? And I think as it spreads across the enterprise it just adds that incremental TAM and it becomes a gateway to AI. >> I've been using ServiceNow as an example, even though a totally different business, they had a much heavier lift, they started in IT, and went on, so it took longer for adoption. But there's a lot of similarities that I see just in terms of extending beyond just the core of the business, growing the ecosystem, I think is a critical part of that but as far as the customer adoption and the applicability of your technology, I think it's got a lot of legs, so. Like you say, Marie, we'll work on that a little bit. >> I'd love that, thank you. >> Dave: Appreciate you coming on, it was great to have you and wonderful to meet you. >> Enjoyed it. You too, thank you very much. >> You're welcome. Alright, keep right there, buddy, we'll be back to wrap up UiPath Forward III right after this short break. You're watching theCUBE. (electronic music)

>> from Austin, Texas. It's Theo Cube covering your storage Accelerate 2019 Brought to you by pure storage. >> How do y'all welcome back Thio, the Cube leader In live coverage we're covering day to a pure accelerate 19 Lisa Martin With Day Volonte Welcoming to the cue for the first time from SG Mark Peters principal analyst and practice >> Oh, my apologies. So young. >> I wish I wish that was true. >> In fact, one of the first analysts I think that's true if not the first analyst ever on the Q. But, >> well, I'll say Welcome back. Thank you. We're glad to have you here. So you've been with Ishii for quite a while, You know, the storage industry inside and out, I'm sure pure. Just about to celebrate their 10th anniversary. Yesterday we heard lots of news, which is always nice for us to have father to talk about. But I'd love to get your take on this disruptive company. What they've been able to achieve in their 1st 10 years going directly through is Dave's been saying the last two days driving a truck there am sees, install, base, back of the day, your thoughts on how they've been able to achieve what they have. >> That'll last me to talk about something I really want to talk about. And I think it addresses your question. How have they been able to do it? It's by being different. Andi, I don't know. I mean, obviously you do a stack of into sheer and maybe other people have talked about that. But that is the end. When I say different, I don't necessarily mean technology. I have a kind of standard riff in this business that we get so embroiled in the technology. Do not for one second think it's not important, but we get so embroiled in that that we missed the human element or the emotional element on dhe. I think that's important. So they were very different. They created, you know, these thes armies of fans who just bought into what they did. Now, of course, that was based on initially bringing flash to the market making flasher Fordham. Well, they've extended that here with the sea announcement and other things as well, so I don't want to just focus on that, but you know, they continue to do things differently with the technology, But I think what really made them an attractive company and why they've survived 10 years on her now big sizable is because they were a different sort of company to deal with. >> Are you at all surprised that the fourth accelerate is in Austin, Texas? Dell's backyard? Yes. Well, they're disruptive. They're different. They're bold. We're okay, >> you see, But But also, did you go to the other three? >> Uh, the last two. I was trying to remind >> myself where they were. I know one was kind of on a pier in a ballpark in San Francisco. One words. You remember the one that was in that you Worf, But that was a a rusting, so cool it was. But it was a metaphor in a rusting spinning desk, right. But it was also such a different sort of place on, So I probably was also a few it D m c. But I agree. And then the last one was in some sort of constantly. Yes, So >> they were all >> different. And so I Yes, I know this is Dell's backyard. Probably literally, because I'm sure Michael owns a lot of the place. It's also kind of very normal place and so there's a little bit of me that I don't want to use the world worry. But as you grow up and of course, we've got the 10 year anniversary, we're in Austin. What's the tagline of Austin? >> I don't know. No. Keep Austin weird. Okay, >> I >> don't want to suggest appears weird, but they were always a little different, I said. That's why I think they were attracted as much as anything. Yes, that's why I had the hordes of admiring fans, all wearing their orange socks and T shirts and cheering on DDE as they get older as they get more mature as they expand their portfolio. Charlie was on stage talking not so much about scale the problem when he was asked, but more about complexity. As you get more complex, you actually get more normal on, So I don't know that weird is the word, but a bit like Austin pure needs to keep your interesting. >> I like that >> Very interesting. So >> you and I, >> we've been around a while. We were kind of students of the industry. I was commenting earlier that it's just to me very impressive that this company has achieved a new definition of escape velocity receiving a billion dollars show. First company since Nana to do it, I gotta listed three. Park couldn't do it. Compelling data domain isolani ecological left hand. Really good cos all very successful companies. Uh, >> what do you think? It's >> all coming out of >> the dot com crash. Maybe that pay part of it. Pure kind of came out of the, you know, the recession. Why >> do you >> think Pure has been able to achieve that? That you know, four x three par, for example in terms of revenues. And it's got a ways to go. They probably do 1.7 this year. I think they have aspirations for five on enough there. Publicly stated that they probably have, right? Of course. Why wouldn't they thoughts on why they were able to achieve that? What were the sort of factors genuinely know? Having no idea what you were gonna ask me. And now actually, listening to question let me You've just made me think of something that I had not really thought. So I took so long to ask the question formulated. And you are so, um, you used the word escape velocity. Let's think about planes. I mean, you know, I think it's a V one, isn't it to take off, Mitch? Maybe not the same as escape, which is in the skies. But you get the point. How long to really take off? Be independently airborne? They gave themselves. I don't know how much was by design default how it really happened? I don't know. They had an immensely long runway. You think the whole conversation about pure for years and years was Oh, yeah, yeah, they're making loads of revenue, but they lose 80 cents every time they get 50. That was the conversation for years and years. I know they've now turned that corner, and I think the difference. Actually, the more I think about it, yes. You can talk about product. Yes, you can talk about the experience. I think those things are both part of it. But the other companies you named had cool things too. They all had cool products you had. What was it? The autopilot thing with compelling. And they had lots of people cheering. Actually, in this building, I think three part was yellow and kind of cool in a different part of the market. and disruptive. But they were both trying to get to the exit fast. Whether the exit was being bought or whether it was going under. I don't know it was gonna be one or the other, and for both of them, they got bought. I don't think pure had that same intention, and it's certainly got funding and backers that allowed it to take longer. So that's a really good point. I think there's a There's a new Silicon Valley playbook. You saw it with service. Now, with Frank's limits like the Silicon Valley Mafia's Sweetman Dietzen, Bush re at Work Day, they all raised a boatload of cash and a sacrifice profits for for growth. I mean, I remember Dave Scott telling me, you know, when he came on, the board was saying, Hey, we're ready to you know, we're prepared to raise 30 million. He said, I need 80 eighties chump change today compared to what these guys were raising. Well, I mean, I think I mean, they pretty quickly raised hundreds of millions, didn't they? They weren't scraping by on 50 or 80 million, which which is what you see. You sort of want one more thought just this escape velocity idea, I think is interesting because the other thing about escape velocity is partly how long you take runway orbit, whatever. But it's the payload on, you know, The more the payload, the longer it takes the take off the ground or the more thrust you need thrust in this case, his money again. But if you think about it, this is another thing where he and I gotta say, we've been doing this a long time. The storage industry over decades has been one of the easiest industries to enter on one of the hardest to actually do well. Why is that? Because the payload is heavy. It's easy to make a box that works fast, big whatever you want in your garage. Two men on one application working for a day. It's really hard to be interoperable with every app, every other system, operational needs and so on and so forth. And so the payload to be successful. I think they understood that, too. So, you know, they didn't let ourselves get distracted by like the initial shiny, glittery we need to get out of this business. >> I love the parallels with payloads and Rockets. Because, of course, we had Leland Melvin inner keynote this morning. I'm a former NASA geek. Talk to us about your thoughts on their cloud strategy, the evolution of the partnership with a W s. We talked about that yesterday. Sort of this customers bringing this forcing function together, but being able to sort of simplify and give customers this pure management playing the software layer wherever their data is your thoughts on how their position themselves for multi cloud hybrid world. >> Okay, two thoughts, one cloud. Then you also used the word simplicity. So I want to talk about both of those things if I can, Um I don't know. I'm sorry. This is not a very good answer. I think it's the truth. I mean, you can't exist in this world if you haven't got a cloud story, and it better be hybrid or pub. Oh, are multi, whichever you prefer. I think those have very distinct meanings, by the way, but we would be here for an hour and 1/2. It'll be a cube special to really get into that. However, So you've got to do this. I mean, there is just, you know, none of the clients they're dealing with. Almost none. That's not research. I'll talk research in a second but glib statement. Everyone's got a cloud strategy. It doesn't matter which analyst company you put up the data, we'll do it. I want to talk about a cup, some research we've done in a second. But everyone will tell you a high number of people who have a cloud first strategy, whether that's overall or just the new applications or whatever. So they've got to do it. What's crucial to whether or not they succeed is not the AWS branding, because everyone's got a W s branding me people that they don't work with or will not work within the next year or two. I mean, I'm sure there's one God you look like you're anxious, you're on a roll. But simplicity is really important. So David knows we do a lot of research early yesterday, one of our cornerstone piece of researchers think all the spending intentions we do every year. One of the questions this year's Bean for a couple of years now is basically saying simple question Excuse. The overuse of the word is how much more complex is I t you know, in your experience, more or less complex. And it was two years ago. I t broadly and you know that I love this question. You know the answer on dhe. 66% of people say it is more complex now than it was two years ago. People don't want complexity. We all know that there's not enough skills around the research to back that up. A swell on dso Simplicity is really important cause who was sitting in this seat before May I think I will say that the company here was founded on simplicity. That was the point. They were to be the apple of storage. I think that's why people love them. They were just very easy to use on dso coming finally back to your question. If they can do this and keep it simple, then they have a better chance of success than others. But how do you define successful them isn't keeping their customers are getting new ones. That's a challenge. >> They do have a very high retention rate. I want to say like 140% but things like we have our dinner for two U percent attention. Yes. How did >> you do? So? So this is is interesting. It's actually 100 and 50% renewal rate. Oh, by the Mike Scarpelli CFO Math of renewal rates on a dollar value on net dollar value renewal rate subscriptions. Mike Scarpelli was the CFO of service. Now invented this model and service now had, like, 100 and whatever 1500 whatever 27. And so it's a revenue based renewal. Makes sense. Sorry for one second you're retaining more people than you >> go. 101 100 >> 50% is insane. 105 >> percent is great. Yeah, 150% is interrupted. Your question. >> Well, I'm just saying >> it's good. Good nuance, >> Yes, Thanks for clarifying its. You know, companies can say whether it's one. Appears customers are pure themselves or competitors. We are cloud. First, we have a cloud for strategy, and a company like pure can say we deliver simplicity, those air marketing terms until they're actually put in the field and delivered. So in your perspective, how does pure take what I T professionals are saying? Things are so much more complex these days? How does a pure commit and say simple, seamless, sustainable, like Charlie, Giancarlo said yesterday. And actually make that a reality. Well, I >> mean, obviously, that's their challenge, and that's what they have work to do to some degree. And this comes back to what I was saying that to some degree it becomes self fulfilling because your that's why your customers come back with more money because they bought into this on. So as long as they're kept happy, they're probably not going to go and look at 20 other people. I'm not saying they never had any of that simplicity to start off with, but it's very interesting if you go to a pure event, their customers and this might be sacrilege sitting in this environment don't talk about the product. They talk about the company, >> right? >> The experience There's that word again, off being appear customer yes on So they're into it. They brought into whatever this is, and as long as the product, please do not strike me down is good enough. I'm not saying that's all it is. I think it's a lot better that, but as long as it's good enough, but you're really well looked after a few minutes ago, when I'm saying that's why I think this market is about so much more than just how fast can you make the box? How big can you make the box? How smart can you make the box? All of those are interesting, But ultimately, I'm only looking at Dave because he's so old. Ultimately, technology is a leapfrog game. Yeah, branding is not >> Beaver >> s O. So that's a good point. But we've not seen the competitors be able to leap frog pure or be able to neutralize them the way, for example, that DMC was able to somewhat neutralize three par by saying, Oh, yeah, we have virtual ization, too, you know, are thin provisioning. Rather. Yeah. And even though they had a thin provisioning bolt on, it was it was good enough. Yes, they did the check box. You haven't seen the competitors be able to do that here? I'm not saying they won't, but are they? I think, um, I was going to say basically this on my MBA, but I don't have one, so I can't say that, but, you know, I've read that. Read the books. If you look at Harvard Business School cases, I think the mistake made by the competition was to assume that Pierre would go away, that they would each try it or that it would fail on will make fun of the fact they don't make any money for the first few years on dhe. You know, the people going to them, we're gonna be sadly mistaken when they can't handle these features, whether that be cloud or whether that be analytics or fresh blades or whatever else again to add on. They thought they would just go away that there are great parallels in history when you let competition in and you just keep thinking at each point they're going to go away. Spot the accent. British motorcycle industry. When the Japanese came in, they literally said, Well, let them. There are records. We'll let them have the 50 cc market because we don't really care about that. But we'll make the big bikes Well, Okay, well, let them have 152 100 cc because really, that doesn't matter. And 10 years later, there was no industry well, and I think what happened with the emcee in particular because, let's face it, pure hired a bunch of DMC wraps. They took your product and, as I've said before, they drove a truck to the the symmetric V n X install base Emcee responded by buying X extreme io and they said, You know what? We're sick of losing the pure. We're gonna go really aggressive into our own accounts and we're gonna keep them with flash. And then what happened is their accounts. It Hey, we're good. We don't actually really need more stores because the emcee tried to keep it is trying to keep both lines alive. And now they're conflicted, pure. You know, I had a what? We're mission. >> You thought not up a great point. Sorry. Just just because I think >> thing about that is if you look at how e. M. C using my words accurately usedto act, I think you said that, too. So I'm not criticizing Adele is they were exceptional organized marketing organization. We go that way. And if you're not going that way, you got a big problem both as a custom, Miranda's UN employees. But the problem with that is also is that way would sometimes become that way, and then it become that way on the product depending what was doing well. So, for example, they had, you know, tens of thousands of feet, all marching to the extreme. I owe beat for a few quarters, and then they would go off on to the next product pure. Just carried on, marching to its beat down that runway escape velocity question >> appoint you brought up a minute ago before we wrap her. That I think is really interesting is that you write your customers talk about the experience. I think we were talking with a customer yesterday. Dave was asking, Well, what technologies are you think he started talking about workloads? So when we're at other events, you hear other names of boxes brought up here to your point. It is all about the experience so interesting and how they're Can you continuing to just be different, but to wrap things up since they're in my ear, we're almost that time. I just wanna take a minute to ask you kind of upcoming research. What are some of the things that you're working on? Their really intriguing you and SG land. I think right >> now, from my perspective, I mean, as a company would continue to do 27,000 different things because there's so much going on in the market. So whether that's security is massive area of focus right now, even improvements in networking. So it's not just the regular run of the mill, you know, Bigger, faster, cheaper. Which is always there s o A. I, of course, in all these again, you may both know you will now doesn't mean we're always looking at buying intentions rather than counting boxes. So it's really where people are moving over the next few years. That said to May. I think what's really interesting is to other things. Number one is to what extent can. I don't think we can really measure this easily. But to what extent can we get people talking about pure again to acknowledge that emotions, attitudes, experiences are an important part of this business? I'm old enough that I'm not scared of saying it, and I think pure is a company is not scared of saying it, you know, I think a lot of companies don't want to admit that Andi all know that they have different corporate cultures and mantras and views on their customers reflect that two on The other thing just generally is the future of I t. As a whole. I know that. So, I mean, I'm doing this because none of us really know what that is, but, you know, clearly way gotta stop talking about the cloud At some point. It's just part of I t. It's not a thing as such. It's just another resource that you bring to bear. I don't know that we're yet at that point, but that's >> got to happen. >> Interesting. Thanks for looking. I'm imagine this was a crystal ball. But Mark, I wish we had more time because I know we could keep talking. But it's been a pleasure to have you >> got the whole multi cloud hybrid cloud for an hour and 1/2. >> We come back, we'll have that discussion. Like what I'll means and yeah, back anytime. >> Excellent. Thank you for joining David. Me. Thank you for David. Dante. I'm Lisa Martin. You were watching the Cube from pure accelerate 19

from the silicon angle media office in Boston Massachusetts it's the queue now here's your host David on tape hi everybody welcome to this special cube in size powered by ET our enterprise Technology Research our partner who's got this database to solve the spending data and what we're gonna do is a braking analysis on the analytic database market we're seeing that cloud and cloud players are disrupting that marketplace and that marketplace really traditionally has been known as the enterprise data warehouse market so Alex if you wouldn't mind bringing up the first slide I want to talk about some of the trends in the traditional EDW market I almost don't like to use that term anymore because it's sort of a pejorative but let's look at it's a very large market it's about twenty billion dollars today growing it you know high single digits low double digits it's expected to be in the 30 to 35 billion dollar size by mid next decade now historically this is dominated by teradata who started this market really back in the 1980s with the first appliance the first converged appliance or coal with Exadata you know IBM I'll talk about IBM a little bit they bought a company called mateesah back in the day and they've basically this month just basically killed the t's and killed the brand Microsoft has entered the fray and so it's it's been a fairly large market but I say it's failed to really live up to the promises that we heard about in the late 90s early parts of the 2000 namely that you were going to be able to get a 360 degree view of your data and you're gonna have this flexible easy access to the data you know the reality is data warehouses were really expensive they were slow you had to go through a few experts to to get data it took a long time I'll tell you I've done a lot of research on this space and when you talked to the the data warehouse practitioners they would tell you we always had to chase the chips anytime Intel would come out with a new chip we forced it in there because we just didn't have the performance to really run the analytics as we need to it's took so long one practitioner described it as a snake swallowing a basketball so you've got all those data which is the sort of metaphor for the basketball just really practitioners had a hard time standing up infrastructure and what happened as a spate of new players came into the marketplace these these MPP players trying to disrupt the market you had Vertica who was eventually purchased by HP and then they sold them to Micro Focus greenplum was buy bought by EMC and really you know company is de-emphasized greenplum Netezza 1.7 billion dollar acquisition by IBM IBM just this month month killed the brand they're kind of you know refactoring everything par Excel was interesting was it was a company based on an open-source platform that Amazon AWS did a one-time license with and created a redshift it ever actually put a lot of innovation redshift this is really doing well well show you some data on that we've also at the time saw a major shift toward unstructured data and read much much greater emphasis on analytics it coincided with Hadoop which also disrupted the market economics I often joked it the ROI of a dupe was reduction on investment and so you saw all these data lakes being built and of course they turned into the data swamps and you had dozens of companies come into the database space which used to be rather boring but Mike Amazon with dynamodb s AP with HANA data stacks Redis Mongo you know snowflake is another one that I'm going to talk about in detail today so you're starting to see the blurring of lines between relational and non relational and what was was what once thought of is no sequel became not only sequel sequel became the killer app for Hadoop and so at any rate you saw this new class of data stores emerging and snowflake was one of the more interesting and and I want to share some of that data with you some of the spending intentions so over the last several weeks and months we've shared spending intentions from ETR enterprise technology research they're a company that that the manages of the spending data and has a panel of about 4,500 end-users they go out and do spending in tension surveys periodically so Alex if you bring up this survey data I want to show you this so this is spending intentions and and what it shows is that the public cloud vendors in snowflake who really is a database as a service offering so cloud like are really leading the pack here so the sector that I'm showing is the enterprise data warehouse and I've added in the the analytics business intelligence and Big Data section so what this chart shows is the vendor on the left-hand side and then this bar chart has colors the the red is we're leaving the platform the gray is our spending will be flat so this is from the July survey expect to expectations for the second half of 2019 so gray is flat the the dark green is increase and the lime green is we are a new customer coming on to the platform so if you take the the greens and subtract out the red and there's two Reds the dark red is leaving the lighter red is spending less so if you subtract the Reds from the greens you get what's called a net score so the higher the net score the better so you can see here the net score of snowflake is 81% so that very very high you can also see AWS in Microsoft a very high and Google so the cloud vendors of which I would consider a snowflake at cloud vendor like at the cloud model all kicking butt now look at Oracle look at the the incumbents Oracle IBM and Tara data Oracle and IBM are in the single digits for a net score and the Terra data is in a negative 10% so that's obviously not a good sign for those guys so you're seeing share gains from the cloud company snowflake AWS Microsoft and Google at the expense of certainly of teradata but likely IBM and Oracle Oracle's little for animal they got Exadata and they're putting a lot of investments in there maybe talk about that a little bit more now you see on the right hand side this black says shared accounts so the N in this survey this July survey that ETR did is a thousand sixty eight so of a thousand sixty eight customers each er is asking them okay what's your spending going to be on enterprise data warehouse and analytics big data platforms and you can see the number of accounts out of that thousand sixty eight that are being cited so snowflake only had 52 and I'll show you some other data from from past surveys AWS 319 Microsoft the big you know whale here trillion dollar valuation 851 going down the line you see Oracle a number you know very large number and in Tara data and IBM pretty large as well certainly enough to get statistically valid results so takeaway here is snowflake you know very very strong and the other cloud vendors the hyper scale is AWS Microsoft and Google and their data stores doing very well in the marketplace and challenging the incumbents now the next slide that I want to show you is a time series for selected suppliers that can only show five on this chart but it's the spending intentions again in that EDW and analytics bi big data segment and it shows the spending intentions from January 17 survey all the way through July 19 so you can see the the period the periods that ETR takes this the snapshots and again the latest July survey is over a thousand n the other ones are very very large too so you can see here at the very top snowflake is that yellow line and they just showed up in the January 19 a survey and so you're seeing now actually you go back one yeah January 19 survey and then you see them in July you see the net score is the July next net score that I'm showing that's 35 that's the number of accounts out of the corpus of data that snowflake had in the survey back in January and now it's up to 52 you can see they lead the packet just in terms of the spending intention in terms of mentions AWS and Microsoft also up there very strong you see big gap down to Oracle and Terra data I didn't show I BM didn't show Google Google actually would be quite high to just around where Microsoft is but you can see the pressure that the cloud is placing on the incumbents so what are the incumbents going to do about it well certainly you're gonna see you know in the case of Oracle spending a lot of money trying to maybe rethink the the architecture refactor the architecture Oracle open worlds coming up shortly I'm sure you're gonna see a lot of new announcements around Exadata they're putting a lot of wood behind the the exadata arrow so you know we'll keep in touch with that and stay tuned but you can see again the big takeaways here is that cloud guys are really disrupting the traditional edw marketplace alright let's talk a little bit about snowflakes so I'm gonna highlight those guys and maybe give a little bit of inside baseball here but what you need to know about snowflakes so I've put some some points here just some quick points on the slide Alex if you want to bring that up very fast-growing cloud and SAS based data warehousing player growing that couple hundred percent annually their annual recurring revenue very high these guys are getting ready to do an IPO talk about that a little bit they were founded in 2012 and it kind of came out of stealth and hiding in 2014 after bringing Bob Moog Leon from Microsoft as the CEO it was really the background on these guys is they're three engineers from Oracle will probably bored out of their mind like you know what we got this great idea why should we give it to Oracle let's go pop out and start a company and that NIN's and as such they started a snowflake they really are disrupting the incumbents they've raised over 900 million dollars in venture and they've got almost a four billion dollar valuation last May they brought on Frank salute Minh and this is really a pivot point I think for the company and they're getting ready to do an IPO so and so let's talk a little bit about that in a moment but before we do that I want to bring up just this really simple picture of Alex if you if you'd bring this this slide up this block diagram it's like a kindergarten so that you know people like you know I can even understand it but basically the innovation around the snowflake architecture was that they they separated their claim is that they separated the storage from the compute and they've got this other layer called cloud services so let me talk about that for a minute snowflake fundamentally rethought the architecture of the data warehouse to really try to take advantage of the cloud so traditionally enterprise data warehouses are static you've got infrastructure that kind of dictates what you can do with the data warehouse and you got to predict you know your peak needs and you bring in a bunch of storage and compute and you say okay here's the infrastructure and this is what I got it's static if your workload grows or some new compliance regulation comes out or some new data set has to be analyzed well this is what you got you you got your infrastructure and yeah you can add to it in chunks of compute and storage together or you can forklift out and put in new infrastructure or you can chase more chips as I said it's that snake swallowing a basketball was not pretty so very static situation and you have to over provision whereas the cloud is all about you know pay buy the drink and it's about elasticity and on demand resources you got cheap storage and cheap compute and you can just pay for it as you use it so the innovation from snowflake was to separate the compute from storage so that you could independently scale those and decoupling those in a way that allowed you to sort of tune the knobs oh I need more compute dial it up I need more storage dial it up or dial it down and pay for only what you need now another nuance here is traditionally the computing and data warehousing happens on one cluster so you got contention for the resources of that cluster what snowflake does is you can spin up a warehouse on the fly you can size it up you can size it down based on the needs of the workload so that workload is what dictates the infrastructure also in snowflakes architecture you can access the same data from many many different houses so you got again that three layers that I'm showing you the storage the compute and the cloud services so let me go through some examples so you can really better understand this so you've got storage data you got customer data you got you know order data you got log files you might have parts data you know what's an inventory kind of thing and you want to build warehouses based on that data you might have marketing a warehouse you might have a sales warehouse you might have a finance warehouse maybe there's a supply chain warehouse so again by separating the compute from that sort of virtualized compute from the from the storage layer you can access any data leave the data where it is and I'll talk about this in more and bring the compute to the data so this is what in part the cloud layer does they've got security and governance they got data warehouse management in that cloud layer and and resource optimization but the key in in my opinion is this metadata management I think that's part of snowflakes secret sauce is the ability to leave data where it is and have the smarts and the algorithms to really efficiently bring the compute to the data so that you're not moving data around if you think about how traditional data warehouses work you put all the data into a central location so you can you know operate on it well that data movement takes a long long time it's very very complicated so that's part of the secret sauce is knowing what data lives where and efficiently bringing that compute to the data this dramatically improves performance it's a game changer and it's much much less expensive now when I come back to Frank's Luqman this is somebody that I've is a career that I've followed I've known had him on the cube of a number of times I first met Frank Sloot when he was at data domain he took that company took it public and then sold it originally NetApp made a bid for the company EMC Joe Tucci in the defensive play said no we're not gonna let Ned afgan it there was a little auction he ended up selling the company for I think two and a half billion dollars sloop and came in he helped clean up the the data protection business of EMC and then left did a stint as a VC and then took over service now when snoop and took over ServiceNow and a lot of people know this the ServiceNow is the the shiny toy on Wall Street today service that was a mess when saluteth took it over it's about 100 120 million dollar company he and his team took it to 1.2 billion dramatically increased the the valuation and one of the ways they did that was by thinking about the Tam and expanding that Tim that's part of a CEOs job as Tam expansion Steuben is also a great operational guy and he brought in an amazing team to do that I'll talk a little bit about that team effect uh well he just brought in Mike Scarpelli he was the CFO was the CFO of ServiceNow brought him in to run finance for snowflake so you've seen that playbook emerge you know be interesting Beth white was the CMO at data domain she was the CMO at ServiceNow helped take that company she's an amazing resource she kind of you know and in retirement she's young but she's kind of in retirement doing some advisory roles wonder if slooping will bring her back I wonder if Dan Magee who was ServiceNow is operational you know guru wonder if he'll come out of retirement how about Dave Schneider who runs the sales team at at ServiceNow well he you know be be lord over we'll see the kinds of things that Sluman looks for just in my view of observing his playbook over the years he looks for great product he looks for a big market he looks for disruption and he looks for off-the-chart ROI so his sales teams can go in and really make a strong business case to disrupt the existing legacy players so I one of the things I said that snoopin looks for is a large market so let's look at this market and this is the thing that people missed around ServiceNow and to credit Pat myself and David for in the back you know we saw the Tam potential of ServiceNow is to be many many tens of billions you know Gartner when they when ServiceNow first came out said hey helpdesk it's a small market couple billion dollars we saw the potential to transform not only IT operations but go beyond helpdesk change management at cetera IT Service Management into lines of business and we wrote a piece on wiki Vaughn back then it's showing the potential Tam and we think something similar could happen here so the market today let's call 20 billion growing to 30 Billy big first of all but a lot of players in here what if so one of the things that we see snowflake potentially being able to do with its architecture and its vision is able to bring enterprise search you know to the marketplace 80% of the data that's out there today sits behind firewalls it's not searchable by Google what if you could unlock that data and access it in query at anytime anywhere put the power in the hands of the line of business users to do that maybe think Google search for enterprises but with provenance and security and governance and compliance and the ability to run analytics for a line of business users it's think of it as citizens data analytics we think that tam could be 70 plus billion dollars so just think about that in terms of how this company might this company snowflake might go to market you by the time they do their IPO you know it could be they could be you know three four five hundred billion dollar company so we'll see we'll keep an eye on that now because the markets so big this is not like the ITSM the the market that ServiceNow was going after they crushed BMC HP was there but really not paying attention to it IBM had a product it had all these products that were old legacy products they weren't designed for the cloud and so you know ServiceNow was able to really crush that market and caught everybody by surprise and just really blew it out there's a similar dynamic here in that these guys are disrupting the legacy players with a cloud like model but at the same time so the Amazon with redshift so is Microsoft with its analytics platform you know teradata is trying to figure it out they you know they've got an inertia of a large install base but it's a big on-prem install base I think they struggle a little bit but their their advantages they've got customers locked in or go with exudate is very interesting Oracle has burned the boats and in gone to cloud first in Oracle mark my words is is reacting everything for the cloud now you can say Oh Oracle they're old school they're old guard that's fine but one of the things about Oracle and Larry Ellison they spend money on R&D they're very very heavy investor in Rd and and I think that you know you can see the exadata as it's actually been a very successful product they will react attacked exadata believe you me to to bring compute to the data they understand you can't just move all this the InfiniBand is not gonna solve their problem in terms of moving data around their architecture so you know watch Oracle you've got other competitors like Google who shows up well in the ETR survey so they got bigquery and BigTable and you got a you know a lot of other players here you know guys like data stacks are in there and you've got you've got Amazon with dynamo DB you've got couch base you've got all kinds of database players that are sort of blurring the lines as I said between sequel no sequel but the real takeaway here from the ETR data is you've got cloud again is winning it's driving the discussion and the spending discussion with an IT watch this company snowflake they're gonna do an IPO I guarantee it hopefully they will see if they'll get in before the booth before the market turns down but we've seen this play by Frank Sluman before and his team and and and the spending data shows that this company is hot you see them all over Silicon Valley you're seeing them show up in the in the spending data so we'll keep an eye on this it's an exciting market database market used to be kind of boring now it's red-hot so there you have it folks thanks for listening is a Dave Volante cube insights we'll see you next time