 From theCUBE Studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. Snowflake, they love the stock at 400 and hate it 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 Simington, a longtime trader told me, when great companies trade at all-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've got to do your own research, but I have lots of data and I have pinions and I'm willing to share that with you. Stocks like Snowflake, CrowdStrike, Zscaler, Okta 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, when you see panic selling, you'll also see panic buying sometimes. Like 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. 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 Delewska, 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 rising, of course, in Snowflake's 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 was 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 2. This is going to hit Snowflake's revenue a net of about $100 million 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 Slutman on the earnings call made this very clear. He said, quote, this is not philanthropy. This stimulates demand, classic Slutman. 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 Snowflake, customers are 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 studies that are out there from competitors attacking Snowflake's 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 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 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 on to 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 and on-prem software estate during Ballmer's tenure. So I just don't see the comparison as relevant. Snowflake, 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's growth rates over time and superimposes the revenue in the red. In Q1 2018, AWS generated $5.4 billion 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 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 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 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, their TAM, which Snowflake's version that blue data cloud thing superimposed on the right. It shows the various layers of market opportunity that we came up with 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. There's just simply discoverable nodes on the mesh. You could have data bricks, data lakes, just three 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 it'll go to the out years, it gets a little fuzzy from edge locations and AI inference, but it becomes massive and decision-making occurs in real time where machines and machine data take over the world instead of cliques and keystrokes. Sounds out there, but it's real. How exactly Snowflake plays there at this point is unclear, but one thing's for sure is there'll be a lot of data and it's going to find its way into Snowflake. Snowflake's not a real-time engine. It's an analytical system. It's moving into the realm of data science and we've talked about the need for semantic layer between 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 got to look obviously at the markets and the tam which we just did, but you also want to understand customers and it's not hard to find Snowflake customers, Capital One, Disney, Micron, Allian, 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. Snowflake 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 of 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 the other criticism here is that Snowflake is not architected for real time inference where a lot of that edge activity 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 is 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 Databricks 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 becoming the super cloud and building this sort of PAS 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 Snowflake's customer spending momentum or net score on the top line that's the vertical axis and pervasiveness in the data or market share in that bottom brown line. Snowflake has unprecedented net scores and held them up for many, many quarters as you can see here going back 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 of the dataset. 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 I could see in one or more of the ETR surveys this year this starting to moderate as they get big. It has to happen. But I would again expect them to have a high spending velocity score. But I think we're going to see Snowflake maybe porpoise a bit here meaning it moderates, it comes back up. It's just really hard to sustain this pace of momentum and hire, train, retain and scale without absorbing some friction and some headwits. It'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 service now very successful, large and trench 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% growth. Yeah, that's the new definition of tepid, I guess. I like to look at some other metrics. The one that really caught my attention was the remaining performance obligations this last quarter, RPO. Snowflake is up to something like 2.6 billion and that is a forward looking indicator of future revenues. So I 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 Zscala, there's 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 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 Slutman, Mike Scarpelli and what they've accomplished in their years of working together. That's why the stock at IPO was so overvalued. I think they'd seen these guys do it before. Slutman just documented in all this in his book, Amp It Up, which gives great insight into the history of that pair and the teams that they've built, the companies that they've built, how he thinks about building companies and markets and how Total Avail market is super important but the whole philosophy and culture that he's building and 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? Actually, that's not a bad way of characterizing it. I think I am in it, you know, for the sport. You know, the only way to become the best version of yourself is to be under the gun and, you know, every single day. And that's certainly what we are. It sort of has its own rewards, building great products, building great companies, you know, regardless of, you know, what the spoils may be. It has its own rewards. It's hard for people like us to get off the field and, 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. My opinion, that's how Frank Slutman thinks about success. It's not about money. Money is 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 Slutman 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 Silicon Angle. And thanks to Ivana Dilevska of Spear Invest and my friend Chip Simington 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 D.Valante or david.valante at siliconangle.com. And this is Dave Valante for Cube Insights powered by ETR, be safe, stay well and we'll see you next time.