>>mhm. >>Good morning. Live from Las Vegas. That snowflake Summit 22. Lisa Martin With Day Volonte David'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've 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 seen Nielsen in S V. P of data and Analytics Service offering head at emphasis. And Chris Dignan alumni is back with us to chief revenue officer at stuff like guys. Great to have you on the programme. Thanks for having us. Thank you very much. So he'll tell us what's going on with emphasis and snowflake and the partnership. Give us all that good stuff. >>Yeah, No, I think with the convergence of, uh, data digital and computing economy, um, you know that convergence is creating so much possibilities for for customers, uh, snowflake and emphases working together to help our customers realise 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, uh, 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, Um, and the and the point of view in the market together so that, you know there is there is cohesive approach to doing this transformation and getting to those business outcomes. So it's a It's a partnership that's very successful and its strategic for for our customers, and we continue to invest for the market. >>Got some great customer. Some of my favourite CVS, Nike, William Sanoma. Gotta love that one. Chris talked to us about the snowflake data cloud. What makes it so unique and compelling in the market? >>Well, I think our customers, really they 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 take it and and allow it to go from one cloud to the other so they can sit on a W s it can sit on Azure can sit on G, C, P and I can move around from cloud to cloud, and they can do analytics on top of that. >>So data has been traditionally really hard. And we saw that in the big data movement. But we learned a lot. Uh, and AI has been, you know, challenging. So what are you seeing with 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, you know, get rid of or transform. They have the challenges of really bringing, you know, a cohesive understanding within the enterprise as to what these possibilities are for their business. Given the strategy that they are pursuing, um, business and I t cycles are not necessarily aligned. Um, you have the challenge of very fragmented data landscape that they have created over a period of time. How do you, you know, 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 that's really happening? And and that's where you know our our customers, um, you know, grapple with the challenges of bringing it together. So, >>Chris, how do you see? Because it was talking about, uh, legacy that I think technical debt. Um, you kind of started out making the data warehouse easier. Then this data cloud thing comes out. 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 gonna hear the announcements this morning. We won't. We won't spill the beans, but but really expanding the data cloud. So it's hard to keep up with with where you're at. So I think modernisation, right? So how do you think about modernisation? How are your customers thinking about it? And what's the scope of Snowflake. >>Well, you know, I think historically, you asked about AI and Ml and, you know, in the A I world historically, they've lacked data, and I think because we're the data cloud, we're bringing data, you know, and making it available and democratising it for everybody. And then, you know, partners like emphasis are actually helping us bring, you know, applications and new business models to to the table to our customers and their innovating on top of the data that we already have in the Snowflake Data Club. >>Chris, can you talk about some of the verticals where you guys are successful with emphasis that the three that I mentioned are retailers, But I know that finance, healthcare and life sciences are are huge for smooth, like talk to me, give us a perspective of the verticals that are coming to you. Guys saying help us out with transport. >>You know, I'll give you just an example. So So in the in the retail space, for example, Kraft Heinz is a is a joint customer of ours. And, you know, they've been all in on on snowflakes, Data Cloud and one of our big customers as well it is is Albertsons, and Albertans realises, Oh my gosh, I have all this information around the consumer in 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 snowflakes data sharing, we can actually allow them to share data. Albertans share data directly with Kraft, Heinz and Kraft. Heinz can actually make supply chain decisions in real time so that these are some of the stuff that emphasis and stuff like help our customers self. >>So traditionally, the data pipeline goes through some very highly specialised individuals, whether the data engineer, the data scientists and data analyst. So that example that you just gave our organisation you mentioned before democratisation. So democratisation needs to be as a businessperson, I actually can get access to the data. So in that example that you gave between Kraft, Heinz and and and Albertson, is it the the highly hyper specialised teams sharing that data? Or is it actually extending into the line of business focus? >>That's so that's the interesting part for us is I think, snowflake, we just recently reorganise 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. How do I solve for demand forecasting? How do I supply fix my supply chain issues? Those are things. Those are the. That's how we're aligning with emphasis. So well is they've been doing this for a long time, Can only we haven't. And so we need their help on getting us to the next level of of the sales motion and talking to our customers on solving these business challenges in >>terms of that next level. So no 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 recognises, we're going to be a data company. We're not gonna be a 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 tonnes of learning that they've hired in the last two or three years and digitising in 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 for the companies they recognise. That data has been touted 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 for the customers, the conversations are around industry verticals. You know, what are the specific challenges and opportunities that the the enterprises have, uh, and how you realise those and these cuts across multiple different layers. You know, we're talking about how your democratised data, which in our point of view, is absolute, must in terms of putting a foundation that doesn't take super specialised people to be able to run every operation and every bit of data that you process we have invested in building autonomous data and a 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 only channel for retail and CPG. And these are great examples of how Snowflake Foundation enables democratisation on one side but also help solve business problems. In fact, with Snowflake, we have a very, uh, 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 Dr Exchanges for our customers and one of the services company in the recycling business. Uh, we're actually building and in 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 building a data ecosystem. Yes. Alright, They they Is it a two sided market place where you guys are observers and providing the the technology and the process, you know, guidance. What's your role in that? >>Yeah. So, um, we were seeing their revolution coming? Uh, two stages. Maybe even more. Um, 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 on the other side. There is a good use of that data, Uh, and not, uh, you know, compromise on their quality or privacy and some of the other regulations. But we do see this opening up to the two sided market places as well. Uh, some of the industry's lend themselves extremely well for that kind of play. We have seen that happening in trading area. We've seen that happen. And, uh, 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 and the programmes are really leading towards towards that in the market. >>You know, Lisa, one of things I wrote about this weekend is I was decided to come to stuff like summit and 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 monetised and and I'm hoping we're going to see some of that here. Are you seeing that Christian in the customer? It's It's >>a great question, David. So So we have You know, I just thought of it as as he was talking about. 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 US 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 monetise that data. So yes, the answer is. You know, I I used to sell to, you know, chief Data Officers and and see IOS. 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. They don't have to worry about the infrastructure that comes from the cloud. They don't have to worry about the governance, as Senior was saying, Just put >>it in stuff like Just >>put stuff like that. So I call it The super cloud is kind of a, you know, a funny little tongue in cheek. But it's happening. It's this layer. It's not just multiple clouds. You see a lot of your critical competitors adjacent competitors saying, Hey, we're now running in 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 The infrastructure of the hyper scale is, and that's that's a new era. I think >>it's a new error. I think they're you know, I think the hyper scholars want to, you know, keep us as a as a data warehouse and and we're not. The customers are not letting them so 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, uh, this past year and they're helping us in our customers innovate, >>but you're uniquely qualified to do that where? I don't think it's the hyper scholars agenda. At least I never say never with the hyper scale is, but yeah, they have focused on providing infrastructure. And, yeah, they have databases and other tools. But that 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 and those are the Those are the fun conversations because you're you're saying, Hey, we can actually create a new revenue stream. And how can we actually help you solve our joint customers problems? So, yes, it is. Well, >>that's competitive differentiation for businesses. I mean, this is, 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 to leverage a data platform like snowflake, to find insights, 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 nice to have >>100%. I mean, I think they're they're all scared. I mean, you know, like if you look in the financial services space, they look at some of the fintech, as you know, the giant £800 gorillas look at the small fintech has huge threats to the business, and they're coming to us and say, How can we innovate our business now? And they're looking at us as the the innovator, and they're looking at emphasis to help them do that. So I think these are These are incredible times. >>So the narrative on Wall Street, of course, this past earnings season was consumption and who has best visibility and and they they were able to snowflake had a couple of large customers dial down consumption, some consumer facing. Here's the thing. If you're selling a data product for more than it costs you to make. If you dial down consumption in the future, you're gonna dial down revenue. So that's it's going to become less and less discretionary over time. And that, to me, is the next error. That's really exciting. >>The key, 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 monetise because to your point, 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 monetise the specific, you know, unit of measure that they care >>about because when they get the Amazon bill or the snowflake bill, the CFO 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 >>if I'm going on sales calls with the VP of sales and his their sales team, fantastic, right generated helping them generate revenue, right? That's a great conversation >>dynamic. And I think the adoption is really driven through the value, uh, that they can drive in their ecosystem. Their products are similar to products and services that these companies sell. And if you're embedding data inside Syria into your products 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 are constantly changing, and we talked about some of those forces earlier. All of this is changing. The landscape is changing the the needs in the economy and things like that, and how you adapt to those kind of models in the future and pivoted on data capabilities that lets you identify new opportunities and 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 working customers go to get engaged. I imagine both sides. >>Yeah. I mean, the way that partnership looks good to me is is sell with co selling. So So I think, you know, we look at developing joint solutions with emphasis. They've done a wonderful job of leading into our partnership. So, you know, Sue Neill and I have a regular cadence where we talked every quarter, and our sales teams and our partner teams are are all leaning in and co selling. I don't know if you >>have Absolutely, um, you know, we we proactively identify, you know, the opportunities for our customers. And we work together at all levels within, you know, between the two companies to be able to bring a cohesive solution and a proposition for the customers. Really help them understand how to, you know, what is it that they can, um, 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're selling, but also downstream and we're 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. Thank you So much >>for our guests and a Volonte. I'm Lisa Martin. You're watching the Cube live in Las Vegas from Snowflake Summit 22 back after the keynote with more breaking news. Mhm, mhm.