Ladies and gentlemen, thank you for standing by. And welcome to the Q4 FY ‘21 Snowflake’s Earnings Conference Call. At this time, all participants are in a listen-only mode. After the speakers’ presentation, there will be a question-and-answer session. [Operator Instructions] I would now like to hand the conference over to your speaker today, Jimmy Sexton, Head of Investor Relations. Thank you. Please go ahead, sir.

Good afternoon. And thank you for joining us on Snowflake’s Q4 fiscal 2021 earnings call. Joining me are Frank Slootman, our Chairman and Chief Executive Officer; and Mike Scarpelli, our Chief Financial Officer. During today’s call, we will review our financial results for fourth quarter fiscal 2021 and discuss our guidance for the first quarter and full year fiscal 2022. During today’s call, we will make forward-looking statements, including statements related to the expected performance of our business, future financial results, strategy, products and features, long-term growth, and overall future prospects. These statements are subject to risks and uncertainties, which could cause them to differ materially from actual results. Information concerning those risks is available in our earnings press release distributed after market close today and in our SEC filings, including our most recently filed Form 10-Q and the Form 10-K for the fiscal year ended January 31, 2021, that we will file with the SEC. We caution you to not place undue reliance on forward-looking statements and undertake no duty or obligation to update any forward-looking statements as a result of new information, future events, or changes in our expectations. We’d also like to point out that on today’s call we will report both GAAP and non-GAAP results. We use these non-GAAP financial measures internally for financial and operational decision-making purposes, and as a means to evaluate period-to-period comparisons. Non-GAAP financial measures are presented in addition to and not as a substitute for financial measures calculated in accordance with GAAP. To see the reconciliations of these non-GAAP financial measures, please refer to our earnings press release distributed earlier today and our investor presentation, which are posted at investors.snowflake.com. A replay of today’s call will also be posted on the website. With that, I would now like to turn the call over to Frank.

Thanks, Jimmy, and good afternoon, everybody. We finished our fiscal year with strong consumption across our customer base with 116% growth year-on-year to $178 million in fourth quarter product revenue. Remaining performance obligations of $1.3 billion grew 213% year-on-year, reflecting strengthened sales across the Board. Coupled with this rapid growth, we saw improving operating efficiency, while onboarding over 800 new employees for the year. Our growth is driven by long-term secular trends in data science and analytics, and enable by cloud scale computing and Snowflake’s cloud native software architecture. With the onslaught of digital transformation, data operations become the beating heart of the modern enterprise. Customers realize that to survive and thrive they need to step up their data game given what is now possible with technology. The Snowflake Data Cloud enables breakthrough data strategies. Capacity limitations are a thing of the past. There are virtually no constraints anymore on the number of workloads that can execute at the same time against the same data. The performance of individual workloads has increased by orders of magnitude while latency has been reduced at similar proportions. The only constraints left are budgets and our customer’s imagination and we believe those boundaries are shifting quickly as well. The Snowflake Data Cloud also breaks new ground in terms of data access, which is increasingly critical for data science, artificial intelligence and machine learning workloads. The days of mostly in silo analytics are numbered. The promise of data science is to discover and mobilize data relationships that can be glimpsed across a broad diversion -- diversity of data sources and data types. The physical boundaries between data sets dictated by technology legacies have no meaning or significance in data science. Science sees the world’s data as a single universe that is easily seamlessly and frictionless…

Thank you, Frank. Q4 was another quarter of exceptional execution and a strong finish to our first fiscal year as a publicly [Technical Difficulty]. Our Q4 product revenues were $178 million representing 116% year-over-year growth and remaining performance obligations were $1.3 billion. The outperformance of consumption spanned all verticals as we continue to see our customers deploy Snowflake across their organizations. Our strong RPO results continue to be driven by more multi-million dollar deals, as well as our customers’ willingness to engage in multiyear contracts up to $1.3 billion in RPO. We expect approximately 55% to be recognized as revenue in the next 12 months. As a reminder this number is an estimate and can fluctuate significantly due to our consumption business model. The strong performance reflects Snowflakes role as both a technology solution, offering superior execution across workloads and as a strategic partner enabling digital transformation through the data cloud. We continue to invest in growth opportunities and we are now benefiting from our maturing enterprise sales efforts. In Q4 we saw the number of customers with greater than $1 million in trailing 12 months product revenue increased to 77%, up from 65% last quarter, with 12 customers are now consuming over $5 million on a trailing 12 month basis. Internationally, we have expanded our sales force across relevant geographies. We are seeing promising traction in these markets, but remain in the early stages of this opportunity. Turning to margins, on a non-GAAP basis, our product gross margin was 70%, up 400 basis points from last year. Favorable cloud service agreements, growing scale across regions, our enterprise success and ongoing discounting discipline, all contribute to steady gross margin improvement. Our operating margin was negative 24%, benefiting from revenue outperformance and continued T&E savings. Our adjusted free cash flow margin…

Certainly. [Operator Instructions] Your first question comes from the line of Raimo Lenschow with Barclays. Your line is open.

Hey. Congrats. That was detailed amazing numbers. First one, Frank, this quarter we saw a little bit more noise around kind of market activity. I think it’s probably because of your success. Can you see -- if you explain pretty changes in the competitive dynamic out there and then I have a follow up for Mike?

Not really, Raimo, and things have been stable and certainly from the public cloud standpoint perfect, the course, there in terms of the comparisons with the legacy providers, no change there either. If I sort of take a global perspective on it, I would say, that I feel that our competitive position is gradually strengthening in anticipation that are the types of interactions we have with customers. We are operating far more at CEO level now than at the highest level of IT. So, there is definitely I feel an inflection there that is reflecting the relative position of the company, the marketplace, which we feel is very good.

Okay. Perfect. Hey. Thank you. Again, Mike, on the gross margins, I mean, we have seen the progress this year and you gave us guidance. Just talk a little bit about the drivers for the gross margin improvement we are going to expect in the coming year and what it is -- like is it more the contracts with the cloud providers or what’s driving it going forward and what led to do for you to reach the long-term goals? Thank you.

Yeah. I would say, the contracts with the cloud provider started kicking in Q3 and we had the full benefit in Q4. I don’t anticipate renegotiating our cloud contracts next year. We may be in a situation at the end of the year, but I am not expecting that. It’s really driven by getting more scale within our existing deployments. We have a number of deployments where we are not at scale and we see those ramping right now. As an example, like, Japan. Japan has been running at a negative gross margin, because we just don’t have very many customers but we are starting to ramp there that that will turn around and that’s just one example. We are in 20 deployments around the world and think of a deployment as a data center out places. But also as we move higher up into larger enterprises they tend to buy our higher addition our business critical. Yes, those big customers require more discounting, but the margin -- the contribution margin from those higher SKUs more than offset that discounting to drive gross margin, which gives us the confidence that we will get to those mid-70s, it’s not going to happen next year, but we see that continued gradual improvement.

Prefect. Thank you. Congrats.

Your next question comes from the line of Derrick Wood with Cowen. Your line is open.

Yeah. Great. Thanks and congrats as well on a very strong quarter. I guess, first for Frank, how are you feeling about the ability to onboard sales people at a good clip and keep up the demand trends out there, particularly kind of in this work-from-home environment? And then heading into the New Year, any go-to-market tweaks your planning that you would call out?

Yeah. So, in terms of sales people, I think, we are doing incredibly well and we are making a lots of changes and adjustments that are for strengthening our organization. I am sure you know that, year a half ago we separated our U.S. selling organization and enterprise, and what we call majors [ph] which are the largest 200 or so accounts and we really stepped up our staffing in that organization really, hiring the absolute best people available in the marketplace for this role. So I am really positive on that. In terms of what’s changing on our go-to-market, I referenced that in the prepared remarks. I mean, we are very aggressively verticalizing our selling merchants and our general posture in accounts and we find it’s very important that when we interact with customers. There’s always an industry context in the conversation. We are much more outcome oriented. Customers are sometimes interested in architecture and things of that sort and comparing workloads and all of that. But increasingly when you get higher up in larger enterprises they just want to know what it means to their business, what are other people doing. So that is a significant change and we are investing literally at every level in the organization, so starting with products, moving into marketing and moving into alliances, as well as into sales and so this is a very serious effort that started last year and that will continue underway this year.

Great. Thanks. And Mike maybe one for you, nice uptick in new customers in the quarter and then you called out to what’s helping drive that acceleration. Is it better productivity or more capacity or is it something you are starting to see on this viral networking effect from your data sharing. Is that something that can move the needle and starting to help lift the customer generation?

Well, I would say, there was definitely an increase in average productivity per rep in terms of the number of cap one deals that they brought in on average in terms of the data sharing. I don’t have any specific data on that but that is clearly a discussion point with every customer and one of the reasons why they choose to go with Snowflake. It helps the decision to go with Snowflake. That’s also the fact that we are ramping. We have been adding so many reps and we have been ramping those people.

Great. Well done. Thanks.

Thanks.

Your next question comes from the line of Patrick Colville with Deutsche Bank. Your line is open.

Hey. Thank you so much for taking the question and congrats on an extremely impressive set of numbers. I just want to touch on the capacity environment. I mean the earlier question from Raimo was around competition with the cloud native vendors. But one of the legacy, call it, on-prem vendors put up some pretty impressive cloud numbers a month ago. How dynamics with the incumbents shaping out and yeah maybe a comment on that please?

Yeah. Patrick, this is Frank. I can honestly say that in my almost two years here I have never seen the legacy provider being in -- they are running for a go forward destination for the platform, if you will. So and the competition it’s always moving off of legacy platforms and the competition has been very, very focused on the public cloud options. What I will say is that, we are seeing the public cloud vendors having significant struggles in terms of migrating successfully off of these legacy platforms, which of course, brings relative strength to these -- to some of these legacy providers. I think that Snowflake is really the only platform that is successfully and consistently and now at scale moving these workloads to the cloud. But to some degree your legacy providers are hanging in there longer, because if you are not going to Snowflake you are going to have a struggle on your hands. So that’s sort of my commentary on that topic.

Yeah. I mean that’s very helpful. And can I just ask a quick follow-on for Mike if possible? I -- it seems that implicit in guidance is that 1Q up margins looks like it will increase pretty materially year-on-year. Are you guys slowing up the pace of hiring or how should we think about that component?

No. We are absolutely not slowing hiring down. As we just mentioned, we are going to add 1,200 people next year. Actually Q1 is a very, very big onboarding quarter. It will be probably the largest quarter of the year, because we are onboarding a lot of people in the sales and marketing organization in advance of our sales kickoff that we just had. We are investing as quickly wellbeing efficient in our business as we can.

Fantastic. Thank you so much and congrats a very impressive results.

Thank you.

Your next question comes from the line of Brad Zelnick with Credit Suisse. Your line is open.

Excellent. And I echo the congrats as well. Well done guys. I have got one for Frank and maybe one for Mike. Frank, can you share more about BlakRock partnership with a lagging cloud on the Snowflake Data Cloud. Specifically can you talk about the economics of these types of relationships and the success criteria that you use for gauging the progress? And maybe as well, how many partnerships like this are out there to go after?

No. There’s a lot of partnerships out there to go after. I think that that announcement by itself triggered a whole rash of conversations both from the financial industry, as well as other industries. This whole conversation around customers building their own data cloud is really the center of their universe, the way they interact with their partners, their customers, their stakeholders is a huge idea and people are seeing the opportunity and the potential, and obviously, for BlackRock because they are the world’s largest asset manager with where they were leased $21 trillion, $22 trillion of assets under management. They realized that they needed to modernize and transform to be able to continue to be in a very dominant position and it was -- from an economic standpoint it’s really no different than what we are doing, in other words this is not a different line of business for us. The same product, same business practices and so on. But obviously these relationships are highly strategic to us. They come -- they become cornerstones to the Snowflake Data Cloud in the data universe, because there’s this is -- this induces network effect all over the place from people that need to have access to this data or provide access.

To say it in a simpler way, Brad, that all of those Aladdin customers that want data through Aladdin, if they want to get their data the most efficient way are going to have to be Snowflake customers.

Excellent. That makes perfect sense. And Mike, maybe just to follow up with you, it’s great to see net retention continues to be really strong. I think that’s in class of anything else we look at. But as we think about the cohort of customers that you have added in the last 12 months, how are they tracking relative to prior years? And maybe just ask differently, like, how do we think about the size of your lands today and how that might be changing and informs your view or our view on how we might think about that net retention rate going forward?

Yeah. So I do expect net retention rate this year to remain very high. It should be north of 160 throughout the year is what we are -- what we see right now. In terms of average deal size landing, that is not changing that much. What’s happening and because I want to stress, it takes customers especially if you are doing a legacy migration. It can take customers six months plus before we start to recognize any consumption revenue from those customers because they are doing the data migration. And what we find is so they consume very little in the first six months and then remaining six months they consume their entire contract they have. Then when we do a renewal that’s when most customers are doing the multiyear renewals once they have proven the use case on Snowflake. And so I haven’t seen much difference other than we are, as you know, when Frank came in here, he really started focusing more on enterprise customers. We are landing more Fortune 500 customers. We talked about we landed 19 in the quarter. But those 19 we landed, just to reiterate, we recognized virtually no revenue on those customers. That’s all in the RPO that will be in the next 12 months.

Awesome. Thanks so much gentlemen and stay well.

Thank you.

Your next question comes from the line of Patrick Walravens with JMP. Your line is open.

Oh! Great. Thank you and congratulations. Frank or Mike, can you double click on the migration. So why is it so hard to migrate legacy data warehouse? What are the steps you have to take that are so time consuming and then what is it about Snowflake platform to make it so much better suited do it than the cloud providers?

So that’s a great question. So, first of all, database migrations have been hard since time immemorial. They have never been easy. They have been lengthy. They have been expensive. They have been risky. And our customers are quite leery of them as well. One of the reasons is that, while we can analyze the data with the structures, we analyze the code, we can automatically convert a lot of it and usually there is no straightforward mapping of some of the data between these databases. Now for example, you take some of the legacy flavors out there, they have proprietary artifacts that just simply do not have a counterpart in Snowflake, because Snowflake is a completely standard NNC quote environment. So that means that we have to reengineer, we have to reach the structure, we have to optimize workloads, things of that sort. The integrity of the data is absolutely everything. When you do a data migration what makes customers fearful is. They want to make sure that when the systems land on the other side they are getting exactly the same results that they were getting before. So the integrity is 100% maintained and there is not a matter of this throw on a big switch and hoping for the best. So that’s a little bit of color and texture why these things are viewed as a sort of high friction. Now we are good at it, because we are experts at this. This is what we do. And we have a ton of experience doing it and that accumulated experience, as well as a lot of the tooling that we have to support these efforts, it’s resulting in a very good results, a very predictable results, time wise, cost wise and outcome, so that’s why.

All right. That’s very helpful. Thank you.

Thank you. Your next question comes from the line of Brent Thill with Jefferies. Your line is open.

Thanks. Frank, a lot of the customers are excited your journey to unstructured. I am just curious if you could update us on that journey and how far out our customer is going to have to wait. What are you starting to see in terms of the discussions around the commitment beyond the structured stance you already have?

Yeah. Well, so, Brent, first of all, I mean, we are 100% committed to that and it’s from a strategy standpoint it is something we absolutely have to do. When you think of data sciences, data relationships don’t just exist between like data. They exist between structured and unstructured data. That’s actually where a lot of the power is going to come from the type of signals that we can drive out of the data. And I think I said last time that, we are going to really substantially update the world on where we are with that as well as demonstrate at our June usual events. So, you should really expect the second half where you are going to see the real results of that strategy starting to become available in private previews and things of that sort.

And one of the other things that the customers keep talking through Frank just as it relates to some of the partnerships whether it’s with Tableau or Salesforce or ThoughtSpot, some of the other interfaces that’s making your data more consumable by the mass market and we have heard some incredible stories of customers moving faster with you because of those partnerships. Can you just bring us up to speed on what you hear anything from customers and what some of the deployments look like that you are hearing kind of common feedback on? Thanks.

Well, we have relationships literally with every single business intelligence BI, vendor Tableau is definitely the largest one. But we also have -- we are going gangbusters with Power BI which is the Microsoft product also and we are going to -- we expect to see a lot of growth in that area as well. So, we are -- those relationships are really, really solid. We have a product of our own called Snowsight, which is really not meant to be so much competitive with the likes of Power BI and many of the others. That’s really our homegrown if you will and better products really data analysts as opposed to for end user distribution. But listen there’s no doubt that Snowflake makes these product absolutely sing. It’s just a sheer scale of execution, the performance, the provisioning. So no without Snowflake it’s just very difficult for these products to really have the snappy dynamic performance that users are looking for. So combination of this technology Snowflake with the entire family of the BA products out there, very, very important to deliver a good sort of end result to the customer.

Thanks Frank.

Your next question comes from the line of Kash Rangan with Goldman Sachs. Your line is open.

Hey, guys. Thank you very much. Congratulations on a superb quarter. Two questions, Frank one for you, as you talked about how the decisions are increasingly being made by the C level, not just the CIA, but CEO level. Can you talk about how they are looking at Snowflake in relation to their digital transformation initiatives meet? Generally here customer experience, employee experience is fairly digital. Could you help us connect the dots what are your CEOs, customer CEOs thinking in regards to Snowflake and how Snowflake specifically drives the digital transformation. Maybe I will just at that? Thanks.

Yeah. So the angle they are taking is one of digital transformation. IT organizations are typically focused on what we call modernization. They are taking existing workloads. They want to move them from the on-premise environment to the cloud, but essentially take advantage of the utility model and all of that, but fundamentally running the same workloads on the platform like Snowflake. When you get to business people and CEOs, they are looking for new angles. They are looking for transformation, not just modernization. So it’s often very easy to determine in these conversations whether people are after doing things differently and looking for advantage. Digital transformation plays a big role. What that means here is that, they are looking to drive signals out of their data. They are trying to define data relationships through data models that they can take advantage of. And once I can describe the data relationship I can predict it and I can even make prescriptions out of that as well. And things are going to go end-to-end digital, lights out, light speed, so it’s the digital transformation is a big thing. You can think of things like really improving the efficiency and yield on marketing and sales outreach, improving service experiences, and obviously, very, very, very high scale and very, very high precision and very, very high economy on these type of processes compared to what they historically have done. The data cloud is central to these conversations. One of the things that we drive very hard is that, in future data operations are going to be very much dominated by data really moving in an orbit, where -- in other words data is flowing between partners and all kinds of stakeholders and people are able to not just analyze data in silos, but very effortlessly address data really across really a very broad orbit that includes their own data. But then external data sources data from partners, social media, IoT, structured unstructured. That’s really where people are looking for significant advantage from where they historically have been.

Yeah. Got it. Frank and also your biggest customers, what are the problem areas they pushing you into that could open up the opportunities and that’s it from me. Thank you so much.

Sorry, what was it.

Our biggest customers what are the opportunities that are pushing us into.

Well, the opportunities that are central to the conversations with our bigger customers are data cloud oriented. That means establishing data networking relationships, not just internally, but especially externally. I mean, we are well on our way in our journey. I mean where we disclosed some of the growth rates in our prepared remarks. But that conversation is front and center with every single customer, everybody’s trying to figure out. Historically, we have shared data through APIs and through file transfer processes copying and replicating. It’s been an enormous struggle. The opportunity with Snowflake is to make this zero latency, zero friction, completely seamless. So it is an enormous game changer to what people are used to and also that goes, of course, then.

Super. Thank you.

Your next question comes from the line of Brad Reback with Stifel. Your line is open.

Great. Thanks very much. Frank, early in the call you talked about the limit -- the limitlessness nature of the product set and that it’s only limited by the customer’s imagination. How do you help those clients manage budgeting issues, given the usage that they rack up on the system very quickly?

Yeah. That’s good question and certainly a topic that we discuss often. The big change in paradigm is that historically in on-premise data centers, people have to manage capacity. And now they don’t manage capacity anymore, but they need to manage consumption. And that’s a new thing for -- not for everybody but for most people -- and people that are in the public cloud. I have gotten used to the notion of consumption obviously because it applies equally to the infrastructure clouds. Now we do a lot, we have full blown chargeback capability, so that the consumers are -- of compute are and of our service and really accountable for what they do and don’t do. We have hard limits, we have soft limits, we have notifications, we have dashboards. So there’s a lot of ways to do this. But at the same time a very scares, people are really so motivated and inspired by the capabilities that they have. Sometimes they get a little bit out of control in terms of the amount of processing that they were planning to do and it’s a very, very blunt situation. I mean we have been bottled up literally for generations and now there’s a situation where there is no upper limit to how much you can do and that’s intoxicating quite honestly. And we also see organizations really getting used to managing consumption and how much do we really want to allow, because often times we are very compelling reasons, why they do need to consume these services as opposed to just looking at the amount they spend. So it’s manageable but it’s a new discipline and it’s a new mindset that everybody needs to get their head around and we provide the infrastructure and governance capabilities to do that.

Great. Thanks very much.

Your next question comes from the line of Brent Bracelin with Piper Sandler. Your line is open.

Good afternoon and thanks for taking the question. One quick for you, Mike, and then a follow-up for Frank. The dollar value of new contract signings exceeded -- in Q4 exceeded all of last year. And so my question is, there is some seasonality that drove that. Is this just improving sales productivity? Walk me through the drivers there of the RPO momentum on Q4 and then one quick follow up.

So, number of things. A, obviously you are always going to get seasonality because that’s a bookings number and obviously sales people in Q4 are going to try to maximize their acceleration there into. But it’s also a function of the number of reps that we have now are ramped up. And it’s also a function of the fact that we are getting into larger customers as well too and it’s not just the larger new customers, it’s the existing large customers with big renewals, because we are growing within those customers in the multiyear component of those customers. As I mentioned earlier, most initial what we call cap one customers are tend to be one year contracts and if the renewal and the follow on that tends to be the multiyear once they have proven they use cases. That’s not always the case. That’s just what we have been seeing historically. I do expect as we become a larger company, we will see more and more of those capacity when customers sign up for multiyear deals day one as well.

Got it. Helpful color there. And then, Frank, we have heard internal use case for data sharing inside of a corporation has the potential to become believe the killer app here. You have some great stats on data marketplace which is really around sharing data externally. But do you have any color for us around internal use cases for data sharing. Are you seeing any sort of material changes and customer interests for internal data sharing use cases?

Yeah. The interesting thing is most of the data sharing is actually externally, not internally. And one of the reasons is, if I look at some of our larger customers, they maintain a single copy of all their data and they allow their operating functions and departments and business units to execute clusters against the single copy of the data. So they are sharing data effectively because they having a single copy of the data, right? So they don’t have to take advantage of our data exchanges and data sharing because they are literally sitting on the same copy of the data and that’s probably will be the reason why we should have two modes of sharing. One is really tightly coupled where everybody sits on the same data and the other one is the more loosely coupled one, which is through our data sharing architecture and customers can actually mix and match. It depends on their culture and how much they want to have custody their own data and things of that sort, that sort of drives where they land on that, but the architecturally the tightest model out that we have is where there’s one copies of data for the entire enterprise and anybody that wants to process against that data, they fire up their own warehouses and their own clusters and they run their own workloads and that’s an extremely successful model for Snowflake and our customers.

Great. Thank you.

Your next question comes from the line of David Hynes with Canaccord Genuity. Your line is open.

Hey. Thanks guys. I think I will echo everyone else’s congrats, really impressive numbers. And just one for me, Frank, is there any way to think about a dollar spent with Teradata or when the legacy CW vendors turns into X amount of spend with Snowflake and I don’t know if you can think about it that way, but at sometimes did investors saying, hey, Teradata peaked out a little less than $3 billion in revenue and look, I realize they are not the only share donator and I realize this is not only replacement. But it’s gets at the question of like, how big can Snowflake really gets. So any thoughts to help us kind of frame that question?

Yeah. Interesting thing is that a lot of the Teradata migration we have done, customers are telling us we are spending half the money and we are doing 10 times the amount of work and that may not be what you want to hear, but obviously that’s a hell of a deal for them. What’s really expanding the marketplace is that, historically there have been fixed capacity limits on how much work you could do and those are gone under the Snowflake platform. You can run as many workloads concurrently and you can provision those individual workloads as much as you need to. So all of a sudden it’s like, hey, I don’t have to wait in line for 2 a.m. slot to run my little job. It’s like everything runs concurrently as much as you can possibly imagine that you want to do. Obviously, there is a financial consequence to running a ton of workloads, but there’s no operational limit on that. Now what does is, it really starts to inspire people to do things they never entertain because there was not a possibility for them to ever do that. So we are sort of in this period where we are unleashing all this imagination, as well as all the backlog that has already existed that people are just rushing towards. Now because data as a driver of digital transformation, it is really the signals that fuel digital processes. It’s just a very, very core component to how enterprises are evolving. So that’s -- I think this market can get. We have been told by a number of our customers that we are the second largest line item in their budget behind the public cloud and that may come as a shock to some. But I am telling you that that’s not going to be out of the ordinary going forward based on what we are seeing.

Perfect. Thank you, guys.

Your next question comes from the line of Mark Murphy with JPMorgan. Your line is open.

Thank you, Frank. At the Data Cloud Summit, Benoit had mentioned a goal to try to reduce end-to-end data latency by 10 times from where it is today, a pretty amazing goal. I was wondering if you could walk us through how long you think that might take and what types of new opportunities it could open up maybe for more complex analysis or larger AI models and so forth inside the Snowflake?

Yeah. Probably we should bring Benoit into -- in here, let him answer that question, one of the areas that we are investing in where we have extraordinary talent that we have attracted the company as where our event driven architecture is. Today our event latency is sort of seconds and minutes, right? But you want to drive that down to sub-seconds and dramatically sub-seconds. You start to open up use cases that are just very different. That are really not approachable by a platform approach today. They really require very single purpose optimizations, right? When you think about electronic trading and all these things the latency has to be approaching zero. That obviously -- that requires tremendous optimization on our part and we are working on that because we see that as a very, very critical part of the ongoing evolution of digital transformation. We are doing a lot of stuff that is where -- what our capabilities are today are totally adequate. But we are foreseeing a world where and this has been lost at where we have to become much, much faster than what we have done so far. And certainly we have that room up, we know how to do it. So again this is going to expand the marketplace in places where these technologies historically have not been.

Thank you. And that’s a good follow-up Mike, it sounds like you are moving up market in Beijing with more large enterprises pretty rapidly. Are you seeing a higher mix of Snowflake usage on Microsoft Azure or should we be pencil an AWS sticking around, I think, it’s been 85% of the usage. Do you think it would hang in there for this fiscal year?

I think AWS will continue to be our largest cloud for quite some time, but we are definitely seeing a lot of large enterprise customers choosing to go with Microsoft. But you -- there were -- as I mentioned, the revenue is lagging when we book deal. So it’s going to be second half of the year and even in 2020, our fiscal 2023, I think, you are going to see Azure kick up as a percentage, but we still think AWS will remain our number one cloud partner.

Thank you and congrats.

Your next question comes from the line of Tyler Radke with Citi. Your line is open.

Hey. Thanks very much for taking my questions and I appreciate the stats on data sharing. I wanted to ask you about that, the strength there, I wanted to see if that’s helping you accelerate the win of new logos, if you are able to land with that use case and maybe a customer where you hadn’t been successful before? And then, as I think about that going forward, I mean, do you think data sharing could get to a point where you start breaking out that revenue over time? Thank you.

Well, I am certainly hoping that we will break out that revenue over time. But obviously that’s -- we are not there and we don’t know when that will be, but you will be the first to know. What I will tell you, the data cloud conversation is so highly differentiated that’s even in accounts that are completely dominated by incumbents that it reopens the conversation and we have seen that over and over and over. And so it’s -- we love it, because it’s just the conversation goes from just modernizing existing workloads breaking through the cloud, doing POCs benchmarking to all of a sudden we are talking about complete innovation transformation and that’s inspiring for the customer, and obviously, it’s great for Snowflake.

Yeah.

I would just add to that Tyler that, I don’t anticipate breaking out data sharing revenue any time because it will be difficult. And the reason I say that is because, the whole data sharing is going to drive people to use Snowflake because they are going to have to consume their data, but that’s just a piece of their data. What they will then do is do everything on Snowflake where they are pulling their own data sources from other places. So it’s all mangled together. At the end of the day, what data sharing does is it drives stickiness and it drives consumption.

Got it. I think, Frank, got my hopes up around the disclosure there.

We have got the accountant.

Just a follow up, just as you are thinking about this year, curious how your assumptions are on close rates and what you are putting into the forecast relative to last year as you think about the macro environment? Thank you.

I would just say we gave guidance for next year and you are going to continue to see growth next year and we feel very good about what we are seeing right now, and we are not really seeing any impact on the macro in our business at all.

Thank you.

Your next question comes from the line of Mark Rende with Morgan Stanley. Your line is open.

Hi. Mark Rende on for Keith Weiss. Thanks for taking my question. Congrats on the strong quarter. I guess just one from me, with the evolution of the go-to-market towards vertical specific solutions as you better penetrate large customers. Is there anything to call out in terms of potential impact on the pace of large deals or execution more broadly? And then, I guess, generally what verticals are next after kind of financial services? Thank you.

In terms of verticals, media is -- media and tech are huge financial services, healthcare, life sciences, public sector and the whole replatforming going on in the software companies’ data applications. So there’s -- we have obviously retail consumer packaged goods is a very important vertical for us also. So we have a lot of concurrent activity going on. Most of that is really related to our customers understanding who else is on Snowflake inside their vertical. How are they using it. What are the use cases? What are the outcomes? How are they doing it? And for us to be very, very proficient. And then also in terms of what is the data marketplace and data context in that vertical data sources are they using on the outside, are they providing data, are they consuming data from the outside. So those -- that’s -- those are really the conversation that we are shifting towards. I mean what are they getting out of it in terms of business benefit and outcomes and it’s very, very specific to their business. So, this is a considerable shift because in the past there was always workload comparisons, POCs, benchmarks. How fast is this job running versus this query? Now, we are at a level where we are really fully engaged at the top at the house and the business itself. So, it’s very great for us, because the IP selling motion, while there is nothing wrong with that, that this brings another level of strength through to our outreach.

Great. Thank you.

Your final question comes from the line of Andrew Nowinski with D.A. Davidson. Your line is open.

Great. Thank you for squeezing me in. So, I just want to start with a question on the $1 million or more customers, really strong growth again this quarter and I know it’s a trailing 12 months calculation. So, I’d assume some of that is coming from your existing customers versus new customers. I am just wondering if you could provide any more color or maybe around what’s driving that.

Well. I would say 100% of that is coming from existing old customers. Because as I said, any customer we signed up in the current last fiscal year it takes them six plus months to ramp those significant customers. So, it’s really coming from our existing customers and we have a number of other customers that are on the cusp of that. So we think we will continue to see that growth in million dollar plus trailing 12-month revenue customers going into next year.

That’s great. Thanks, Mike. And then maybe just a quick follow up on your guidance. Q1 certainly looks -- I mean, coming off a great Q4, Q1 looked a little bit lower than expected, but then the annual outlook was fantastic across the Board, across all metrics. So it looks like you are expecting somewhat more of a stronger back half of the year? I am just wondering if you could provide any more color on kind of assumptions for Q1 near-term versus the back half of the year?

Yeah. I don’t think that’s correct, Andrew. Q1 is actually a very strong guide relative to where consensus is and -- we are seeing strength into Q1 in our business and I think the guidance for the full year is prudent, given this is the start of the fiscal year.

Okay. Very good. Thanks, Mike.

Ladies and gentlemen, this concludes today’s conference call. Thank you for participating. You may now disconnect.