 Good morning, live from Las Vegas at Snowflake Summit 22. Lisa Martin with Dave Vellante, Dave, it's great. We have three wall-to-wall days of coverage at Snowflake Summit 22 this year. Yeah, it's all about data and bringing data to applications and we got some big announcements coming this week, super exciting. Collaboration around data. We are excited to welcome our first two guests. Before the keynote, we have Sunil Sanan, SVP of Data and Analytics, Service Offering Head at Infosys. And Chris Degnan, alumni, is back with us, the Chief Revenue Officer at Snowflake. Guys, great to have you on the program. Thanks for having us. Thank you for having us. Sunil, tell us what's going on with Infosys and Snowflake and the partnership. Give us all that good stuff. Yeah, I think with the convergence of data, digital and computing economy, that convergence is creating so much possibilities for our customers. Snowflake and Infosys working together to help our customers realize the vision and these possibilities that are getting driven. We share a very strategic partnership where we are thinking ahead for our customers in terms of what we can do together in order to build solutions, in order to bring out the expertise that is needed for such transformations and also influencing the thinking and the point of view in the market together so that there is cohesive approach to doing these transformations and getting to those business outcomes. So it's a partnership that's very successful and it's strategic for our customers and we continue to invest for the market. Got some great customers, some of my favorite CVS, Nike, William Sonoma, gotta love that one. Chris, talk to us about the Snowflake data cloud. What makes it so unique and compelling in the market? Well, I think our customers really, are going through digital transformation today and they're moving from on-premise to the cloud and historically speaking, there just hasn't been the right tool set to help them do that. I think Snowflake brings to the table an opportunity for them to take all of their data and allow it to go from one cloud to the other so they can sit on AWS, it can sit on Azure, it can sit on GCP and it can move around from cloud to cloud and they can do analytics on top of that. So data has been traditionally really hard. We saw that in the big data movement but we learned a lot and AI has been challenging. So what are you seeing with customers? What are they struggling with and how are you guys helping them? Yeah, so if you look at the customer journey, they have invested in a number of technologies in the past and are now at a juncture where they need to transform that landscape. They have the challenges of legacy debt that they need to get rid of or transform. They have the challenges of really bringing a cohesive understanding within the enterprise as to what these possibilities are for their business given the strategy that they are pursuing. Business and IT cycles are not necessarily aligned. You have the challenge of very fragmented data landscape that they have created over a period of time. How do you put all these together and work with a specific outcome in mind so that you're not doing transformation for the purpose of transformation but to be able to actually drive new business models, new data-driven products and services, ability for you to collaborate with your partners and create unique competitive advantage in the market? And how do you bring those purposes together with the transformation that's really happening? And that's where our customers grapple with the challenges of bringing it together. So Chris, how do you see it? Because you know what I was talking about, legacy debt, I think technical debt, you kind of started out making the data warehouse easier and then this data cloud thing comes out and you're like, oh, that's an interesting vision and all of a sudden it's way more than vision. You get this huge ecosystem, you're extending, we're going to hear the announcements this morning, we won't spill the beans, but really expanding the data cloud. So it's hard to keep up with where you're at. So I think modernization, right? So how do you think about modernization? How are your customers thinking about it? And what's the scope of Snowflake? Well, I think historically you asked about AI and ML and in the AI world, historically they've lacked data and I think because we're the data cloud and we're bringing data and then making it available and democratizing it for everybody and then partners like Infosys are actually helping us bring applications and new business models to the table to our customers and they're innovating on top of the data that we already have in the Snowflake data cloud. Chris, can you talk about some of the verticals where you guys are successful with Infosys? The three that I mentioned are all retailers but I know that finance, healthcare and life sciences are huge for Snowflake. Talk to me, give us a perspective of the verticals that are coming to you guys saying help us out, we got to transform. Well, I'll give you just an example. So in the retail space, for example, Kraft Heinz is a joint customer of ours and they've been all in on Snowflake's data cloud and one of our big customers as well is Albertsons and Albertsons realizes, oh my gosh, I have all this information around the consumer in the grocery stores and Kraft Heinz, they want access to that and they actually can make supply chain decisions a lot faster if they have access to it. So with Snowflake's data sharing, we can actually allow them to share data, Albertsons share data directly with Kraft Heinz and Kraft Heinz can actually make supply chain decisions in real time. So these are some of the stuff that Infosys and Snowflake help our customers solve. So traditionally, the data pipeline goes through some very highly specialized individuals whether they're the data engineer, the data scientist, the data analyst. So that example that you just gave, our organization, you mentioned before democratization. So democratization is to me as a business person, I actually can get access to the data. So in that example that you gave between Kraft Heinz and Albertson, is it the highly hyper specialized teams sharing that data or is it actually extending into the line of business, folks? Well, so that's the interesting part for us is I think Snowflake, we just recently reorganized my sales team this year into verticals. And the reason we did that is customers no longer want to talk to us about speeds and feeds of how fast my database goes. They want to actually talk about business outcomes. Hey, how do I solve for demand forecasting? You know, how do I supply, fix my supply chain issues? Those are things, those are the, and that's how we're aligning with Infosys so well is they've been doing this for a long time. Can't really, we haven't. And so we need their help on getting us to the kind of next level of the sales motion and talking to our customers on solving these business challenges. So. In terms of that next level, Sunil, question for you. Where are the customer conversations happening at what level? I mean, we've seen such dramatic changes in the market in the last couple of years. Now we're dealing with inflation, rising interest rates, Ukraine. Are you seeing the conversations in terms of building data platforms rising up the C-suite as every company recognizes, we've got to be a data company. We're not going to be in business. Absolutely. And I think all the macroeconomic forces that you talked about that's working on the enterprises globally is actually leading them to think about how to future proof their business models, right? And there are tons of learning that they've had in the last two to three years in digitizing and embracing more digital models. The conversation with the customers have really pivoted towards business outcome. It is a C-suite conversation. It is no longer just an incremental change for the companies. They recognize that data has been doubted as a strategic asset for a long time, but I think it's taking a purpose and a meaning as to what it does for the customers. The conversations are around industry verticals, what are the specific challenges and opportunities that the enterprises have and how do you realize those? And this cuts across multiple different layers. We were talking about how you democratize data, which in our point of view is absolute must in terms of putting a foundation that doesn't take super specialized people to be able to run every operation and every bit of data that you process. We have invested in building autonomous data in AI state that can process data as it comes in without any manual intervention and take it all the way to consumption. But also investing in those industry solutions. Along with Snowflake, we launched the healthcare and life sciences solution. We launched the Omni Channel for retail and CPG. And these are great examples of how Snowflake Foundation enables democratization on one side, but also help solve business problems. In fact, with Snowflake, we have a very special partnership because our point of view on data economy is about how you connect with the network partners externally. And Snowflake brings native capabilities on this. We leverage that to drive exchanges for our customers. And one of the services company in the recycling business, we are actually building an exchange which will allow the data points from multiple different sources and partners to come together so they have a better understanding of their customers, their operations, the field operations and things like that. So they're building a data ecosystem? Yes. Are they, is it a two-sided marketplace where you guys are observers and providing the technology and the process, you know, guidance, what's your role in that? Yeah, so we are seeing that evolution come in two stages, maybe even more. Customers are comfortable building an ecosystem that's kind of private for them, which means that they know who they are sharing data with, they know what the data is getting used for and how do you really put governance on this so that on one side you can trust it and on the other side, there's a good use of that data and not, you know, compromise on data quality or privacy and some of the other regulations. But we do see this opening up to the two-sided marketplaces as well. Some of the industries lend themselves extremely well for that kind of play. We have seen that happening in trading area. We've seen that happen in, you know, the credit checks and things like that, which are usually open for, you know, those kind of ecosystem. But the conversations and the programs are really leading towards that in the market. You know, Lisa, one of the things that I thought about this weekend is I was excited to come to Snowflake Summit and see one of the, you know, thesis I have is that we're going to move not just beyond analytics, including analytics, but also building data products that can be monetized. And I'm hoping we're going to see some of that here. Are you seeing that, Chris, in the customer base? It's a great question, Dave. So we have, you know, I just thought of it as he was talking about it, that we have a customer who's a very large customer of ours who's in the financial services space and they handle roughly 40% of the credit card transactions that happen in the U.S. And they're coming to us and saying they want to go from zero in data business today to a $2 billion business over the next five years. And they're leaning on us to help them do that. And one of the things that's exciting for me is they're coming to us not saying, hey, how do you do it? You know, they're saying, hey, we want to build a consumption model on top of Snowflake. And we want to use you as the delivery mechanism and the billing mechanism to help us actually monetize that data. So yes, the answer is, you know, I used to sell to, you know, chief data officers and CIOs. Now I'm talking to VPs of sales and I'm talking to chief operating officers and I'm talking to CEOs about how do we actually create a new revenue stream? And that's just, I mean, it's exhilarating to have those conversations. That's data products and they don't have to worry about the infrastructure. That comes from the cloud. They don't have to worry about the governance. As Sonia was saying. Just put it in Snowflake. Just put it in Snowflake. There you go. I call the super cloud is kind of a, you know, funny little tongue in cheek, but it's happening. It's this layer that's not just multiple clouds. You see a lot of your, quote unquote competitors, adjacent competitors saying, hey, we're now running in Google or we're running in Azure. We've been running on AWS. This is different. This is different. Isn't it? It's a cloud that floats above the infrastructure of the hyperscalers and that's a new era, I think. Yeah. It's a new era. I think the hyperscalers want to, you know, keep us as a data warehouse and we're not, the customers are not letting them. So, I think that's, you know, where emphasis kind of saw the light early on and they were our innovation partner of the year, this past year and they're helping us and our customers innovate. But you're uniquely qualified to do that. Where it's, I don't think it's the hyperscalers agenda, at least that I never say never with the hyperscalers, but yeah, they have focus on providing infrastructure and yeah, they have databases and other tools, but that cross cloud that continuum to your point, talking to VPs of sales and how do you generate revenue? That maybe is a conversation that they have, but not explicitly as to how to actually do it in a data cloud. That's right. I mean, those are the fun conversations because you're saying, hey, we can actually create a new revenue stream and how can we actually help solve our joint customers' problems? So, yes, it is. Well, and that's competitive differentiation for businesses. I mean, these, as I mentioned, every company has to be a data company. If they're not, they're probably not going to be around much longer. They've got to be able to leverage a data platform, like Snowflake, to find insights, to be able to act on them and create value. New services, new products, to stay competitive, to stay ahead of the competition. That's no longer a nice to have, right? It's 100%. I mean, I think they're all scared. I mean, like if you look in the financial services space, they look at some of the fintechs as the giant, 800-pound gorillas look at the small fintechs as huge threats to the business and they're coming to us and saying, how can we innovate our business now? And they're looking at us as the innovator and they're looking at emphasis to help them do that. So I think these are incredible times. So the narrative on Wall Street, of course, this past earning season was consumption and who has best visibility and they were able to, Snowflake had a couple of large customers dialed down consumption, some consumer-facing. Here's the thing, if you're selling a data product for more than it cost you to make, if you dial down consumption in the future, you're going to dial down revenue. So it's going to become less and less discretionary over time and that, to me, is the next era that's really exciting. The key there is understanding the unit of measure. I think that's the number one question that we get from customers is, what is the unit of measure that we care about that we want to monetize? Because to your point, if it costs you more to make the product, you're not going to sell it, right? And so I think that those are the things that the energy that we're spending with customers today is advising them, jointly advising them on how to actually monetize the specific unit of measure that they care about. Because when they get the Amazon bill the snowflake bill, the CFO who starts knocking the door, the answer has to be, well, look at all the revenue that we generated and all the operating profit and the free cash flow that we drove. And then it's like, oh, I get it, keep doing it. Well, if I'm going on sales calls with the VPS sales and their sales team, fantastic, right? I'm helping them generate revenue, right? That's a great conversation. New dynamic. And I think the adoption is really driven through the value that they can drive in their ecosystem. Data products are similar to products and services that these companies sell. And if you're embedding data or insights or AI into your product services, that makes you that much more competitive in the market and drive value for your stakeholders. And that's essentially the future business model that we're talking about on one side. The other one is the agility. Things aren't remaining constant. They're constantly changing. And we talked about some of those forces earlier. All of this is changing. The landscape is changing the needs in the economy and things like that. And how you adapt to those kind of models in the future and pivot it on data capabilities that lets you identify new opportunities and create new value. Speaking of creating new value, last question, guys, before we wrap. What's the go-to-market approach here between the two companies? Where can customers go to get engaged, I imagine, both sides? Yeah, I mean, the way that partnership looks good to me is sell with, co-selling. So I think we look at developing joint solutions with Infosys. They've done a wonderful job of leaning into our partnership. So, you know, Sunil and I have a regular cadence where we talk every quarter. And our sales teams and our partner teams are all leaning in on co-selling. I don't know if you have- No, absolutely. We proactively identify the opportunities for our customers. And we work together at all levels between the two companies to be able to bring a cohesive solution and a proposition for the customer and really help them understand how to, what is it that they can get to and how you get that journey actually executed. And it's a partnership that works very seamlessly through that entire process, not just upstream when we are selling, but also downstream when we are executing. And we've had tremendous success together and look forward to more. Congratulations on that success, guys. Thank you so much for coming on, talking about new possibilities with data and AI and sharing some of the impact that the technologies are making. We appreciate your insights. Thank you. Thank you so much. For our guests and Dave Vellante, I'm Lisa Martin. You're watching theCUBE live in Las Vegas from Snowflake Summit 22. We'll be back after the keynote with more breaking news.