>>Hello from the show floor in Las Vegas. This is the snowflake summit 22 at Caesar's forum. We've been live the last day and a half. Lisa Martin here with Dave ante covering a lot of ground. We're so excited to have the chief marketing officer at snowflake. Join us next, Denise Pearson. And welcome back to the cube. >>Thank you so much. So great to be here with you. So great to have you here at SEL meets as well. Thank >>You. That's unreal. Isn't it? Yeah. I mean, everybody's so excited to be face to face and you know, Lisa and I have been doing a few of these shows, but we, we hear the same thing over and over. It's like, oh, so good to be back, right? Yeah. >>Well, even in the keynote yesterday, when we got in, we saw a standing room only there were overflows. People are ready to hear from snowflake in person. And as we were, you were just talking with Frank, I think the 2019 show had less than 2000 people. And now here we are at close to 10,000, this step leap factor in terms of the audience and also the momentum of the company, the capabilities, lot of growth in that timeframe. Yeah, >>No. Yeah. Two, three years ago we were about 1800 people out to Hilton and San Francisco. We had about 40 partners attending this week were close to 10,000 at this year, almost 10,000 people online as well. And over over 200 partners here on the show floor, >>Right? 250 plus sessions, breakouts, keynotes, technical certifications, developer zone, a lot going on here. The buzz has been enormous from yesterday morning. It still is today. Talk about the theme of the event, the world of data collaboration. We've been talking a lot about data collaboration. Yeah. But from Snowflake's perspective, as Dave you've pointed out, that really seems like quite a differentiation of where snowflake is versus the guys in the root view mirror. Yeah. Number >>One of the very unique capabilities with snowflake is that the ability to share data with each other within your ecosystem. So you can both collaborate now on, on with your data, but also collaborate on building in a new business opportunities set together. So I think it's really a message that we, we, we fully fully own. It' really unique differentiator as well. So >>You used to talk about, you still talk about data sharing, but just kind of evolve the messaging to collaboration, explain why and, and how is that a wider scope and more appealing to the ecosystem in your >>Customers? I mean, data sharing is a terminology used for, for years and years, sounds from any data sharing it's about using, you know, FTP or, you know, APIs, those things. And we of course do it in a very, very different way where, where you do it without, you know, APIs so that you can share data with anyone in your ecosystem, without the data actually ever leaving, ever leaving your, your instance. So it's in a very different way. And also the fact that you can, again, you know, build applications together with other companies, you know, in your ecosystem. And it's a, it's a true collaboration around, you know, data in a way we've never seen before >>The other subtle change was data marketplace to marketplace. Why that change explain kind of what's behind that. >>Yeah. One of our big announcements here this week is around building native, you know, data apps and all snowflakes. Now you can both, you know, build the apps and you can distribute them and monetizing them in our marketplace. So in the past, you know, we only really had data sets within our marketplace within the data marketplace at that time. So you could now, you know, we can publish your data, you could monetize your data, but again, now moving forward, you will also be able to again, build apps and distribute them in the marketplace and also monetize them. And for Mon many startups, right? The, the big challenge is just a monetization piece as well. You build your product. You also need to find a way to, to both distribute and, and monetize it, an invoice for that product. And we solve all that for, for our customers. Now, >>A lot of customer growth, I saw Frank's slide yesterday over 5,900. I think you have 500 plus in the Forbes global 2000, a tremendous amount of growth in customers with a million plus ARR. Yes. >>Where >>Are the customers and the ecosystem in terms of that, that what you just described in the, going from the data marketplace to the marketplace are customers and, and the ecosystem influential in saying, Hey, snowflake, we need to go in this direction. >>Yeah. And also one key thing also with larger companies, they have their own marketplaces built, you know, snowflake as well. So you don't have to publish your, your, your data or app on our marketplace. The many of our larger companies, they're building those own marketplaces around themselves, you know, to distribute their data, you know, to their partners. So there are many ways you can, again, distribute and monetize their data. >>What are the marketing challenges? You, you started out kind of better data where simpler data warehouse, cloud data, warehouse, zero to snowflake was kind of the, the messaging and then the rise of the data cloud. And now it's all about applications. You're obviously building on top of that, but how, how have you, how do you think about that sort of messaging architecture going, you know, where you've come from and going forward? >>Yeah. Obviously the capabilities of the data cloud is kind of building and building it every day. And it's also a positioning that we can, you know, grow with as well. The big difference, you know, for us over the past two years is really that we are more and more really talking to the, to the business side, you know, of our, our customers that that's really where the demand is coming from. And we're truly, you know, with the data cloud, we're truly, you know, build bringing the business side and the it side together to solve these, you know, problems. And also, also together with all our partners as well. >>And I was just gonna ask you what, what's the partners role in the data cloud narrative? How do they help accomplish that? >>I would say, I mean, the data cloud is all about the partners it's, and also this event here, this event is not about, you know, snowflake it's about really our partners, you know, and our customers, you know, coming together, the data cloud is really it's. The foundation is of course, you know, the core capabilities, our platform, but then it's also all, all the data that is in there that other companies can access from our customers, but then all the applications and capabilities that are built, you know, by our partners and also our partners like the, you know, or the SI partners that are here, they are the ones, you know, doing the work, you know, with our customers, they are the ones that are, you know, migrating the data to, to snowflake and the data cloud and helping these companies build this new, you know, business model. So snowflake is a very, very partner first company. And the only thing I really care about this week here is that all this, you know, 200 partners here that they're gonna be tremendous successful if they're successful. That means that, you know, all our customers are successful as well. >>So how is your digital strategy evolving and how do you include the partners in that? >>Yeah, I mean, we learned so much over the past, you know, three, three years in regards to that. So, I mean, we all had to just accelerate our, the, the digital growth, you know, of our marketing capabilities and how to do that in a, with our, our partners. So with many of them, you know, we started developing this joint account based digital, you know, marketing program. Some, we just all had to adapt and innovate really fast, and we're gonna continue, of course, a lot of those motions as well. But at the same time, there's nothing like being out and meeting, you know, customers, you know, face to face. And what's also so important is the alignment we have with our local sales organization and our partners as well. So all these marketing programs that we develop in the fields, those are us again, opportunities cannot build those relationships as well. >>Can you talk about the sales marketing alignment at snowflake? I think it seems to be pretty strong, but we've talked a lot in the last day and a half about the retail data cloud healthcare life sciences, media finance. Talk to us about the marketing sales element, how marketing is facilitating, maybe from a campaign perspective, some of those big sales plays in the S yeah, >>Maybe both unique here. Our C Chris Dham, I think has been here early on the show. I mean, we work together for over six years now and we truly work as one, one team. We, we don't really even see the lines between sort of sales and marketings. We truly share exactly, you know, the same objectives every day. We share the same focus on, on putting our customers and our partners, you know, first, every day, his priorities, you know, are my priorities, you know, vice versa. And I think the biggest challenges we see often in some companies between sales and marketing, is that they're just shifting or it's different, you know, priorities. It's so important just to align the priorities and for us to making sure that our teams are all around the world now, or as aligned, you know, as Chris and I are as well, >>Couple other, yeah. Milestones or events come up, you're doing like, you're doing a worldwide tour and you got the dev conference in November, start with the worldwide tour. What's that all about? >>So we get little break near now, here for, for a couple of weeks. And then we're taking all the best of content here for, from, from summits and also all in our partners on a worldwide tour. We're starting in, in Asia, in August, and we're gonna target over 20 cities around the world. So, and again, I think this year, the challenge was many of our European customers and our customers in Asia. They couldn't make it. So we have smaller numbers, you know, coming from those regions. So it's more, more important than ever that we just come out to them, you know, instead, and bring this content in to them. >>Is that all face to face or at Lisa is all face to face. Is there a digital component as well? Yeah, >>It's actually gonna be all face to face and there will be some, some digital components as well. We're ending the tour in San Francisco. And that's also where we go doing all our winter announcements, you know, as well. And also our build our developer conference. That will be all virtual. The big, the global one will be all virtual at the same time, you know, from San Francisco. >>Okay. Am I confusing that with the November developer conference or >>The, that is, that is the conference, but it, that one will be virtual this year. Okay. >>So dev the build is all virtual. >>Yeah. Build be all virtual. And it's just, so we have that opportunity to reach as many people as we possibly can. >>And then is the, is this, is the intent to eventually bring them in to one place? >>Absolutely. I mean, I think the dev conference, the plan is to really take that around the world, you know, as well. We're seeing markets like Israel, for instance, there's a massive developer community that is, that is looking at snowflake right now. Markets like Indonesia, big developer segment as well. So I think it's not about, you know, having people come to us, it's about we, you know, coming out to them. So markets like Israel and Indonesia. And >>Will you also in future summits include a, a development component. You probably have something here. I just haven't seen it yet, but, but like the conference within the conference, or is it more, Hey, we want to cater to the t-shirt crowd, you know, separately, what do you, yeah, >>I think we cater to them separately. And I said again, that we it's really about taking our content, you know, out, out to them. And when we're talking about the developer audience, we're talking about hundreds and thousands of people and they can't physically, you know, come here. So our plan is really to come out and meet them where they are. How >>Did you make the decision to do this summit fourth annual in person? I'm sure the attendance figures are probably blowing your mind, but that's a, that's a big decision and that's a challenging decision to make. How did they go about doing that? >>I think, I think if there was one thing we've learned during the past three years, it's really about that. Adaptability is the new superpower, you know, of bus business. So of course we've had to adapt, you know, you know, every month. And of course, even two months ago, we were not sure, you know, how, how many people that will be able to come here today, but we're incredibly happy. Were they, were they, were they with the number of people that, you know, came here and yeah, we're already storing planning for next year. >>I mean, it definitely must have exceeded your expectations. Is that fair? Or >>We set expectations high. Yeah. Okay. But again, it's that unknown that we all had to deal with, you know, every day. And I think we're gonna continue to have to, to live with that. >>Yeah. Well, this is, yeah, this is one of the largest shows we've done. Yeah. SIM it's a reinvent, obviously different. That was last year, but this year, this is the biggest event I think we've been to, and we've been to some big brand events, so yeah. Yeah. Punching above the weight as usual. >>Yeah. And again, I wanna just give a big shout out to our whole, you know, partner ecosystem, you know, here, because again, this is very much of an ecosystem, you know, partner you in a conference and it's really all our 200 plus partners here making this conference, what it is. I mean, today >>It's remarkable to pace at which you've been able to grow the ecosystem, but why do you think that is? What's the secret there? >>I think we fully understand that we don't solve all the problems ourselves, you know, for, for our customers. It's really an ecosystem of, of products and services that solve those problems and customers. They are looking for vendors that partner well with others. They're looking for vendors that integrate well, you know, with each other. So we always have an outside in view on things and that's something we challenge ourselves every morning. We wake up, how do we put ourselves in the customer's shoes in terms of, of, of their needs and their problems and how to solve those? We don't solve them alone. We, we solve them with these 200 plus in apart. Make >>It sound so simple. >>Speaking of challenges, you have something called the startup challenge. That's in its second annual >>Yes. Tomorrow we're kicking off the, the final of the second annual startup challenge. We have three finalists here, three very different, you know, companies. And we had a couple hundred applications this year and we have everything from a company that makes AI and ML more accessible to a company, focus on, you know, retail, you know, analytics. It's gonna be very exciting tomorrow, big price for the winner. The winner is going to win a million dollar of investment from, from snowflake ventures. So >>Very exciting. It's a nice incentive. It is a nice incentive, >>Very nice incentive. And also all the exposure you will get as well. We will put a lot of our marketing support, you know, behind this companies as well. >>Excellent. >>And now the data driver awards program, we've had a couple of data drivers on the program in the last day >>And a half. Yes. We announced to know those winners as well, you know, early in the week. So a lot of recognition for both our customers, but also we're gonna see, you know, the next interesting companies here to watch tomorrow during the startup challenge, you >>Get a little bit of something for everybody here, right? I mean the, the, the, the partner awards, right? These other little side opportunities for ecosystem to get recognition, sometimes funding it's >>Yeah. Everyone wants to be recognized, you know, for the great work they're doing. So, yeah. Yeah. >>So what's next for marketing, obviously, a break and then you start the, the road show. >>So of course yesterday we made an number of very, very large in announcements. Many of those, you know, we've been working on for years here at snowflake, like Unior, you know, for instance has been probably three years, you know, in the making. So our goal now is to take all those announcements to every customer around the world, both through, you know, local events really starting this week, and then also the world tour this fall. And it's gonna be a big, big focus on the developer segments. Obviously what our most exciting announcements is, the native apps, you know, capabilities. And that finally, you know, we can bring the work, you know, to the data and not again, taking the data to the work. And as you know, our mission has really been around breaking down the data silos. Cause those have been the biggest, you know, challenges companies have faced. That's really, what's been standing in the way for customers to become you a data Rav, and now bringing the work to the data from a developer's standpoint is gonna break down even further, those silos. So, >>Yeah. And it's good physics. >>Yeah. It good physics. Yeah. >>Yeah. Tremendous opportunity. Congratulations on a great successful event. It's not even done yet, but obviously we've seen so much success. Great news coming out. We'll be excited to be hearing some of the outcomes of the road show and the developer conference coming up in the fall. We appreciate your insights, your time and for having the cube here at the summit. >>Thank you for being here. Thank you. Thanks for having >>Me, our pleasure for Denise Pearson and Dave Valante I'm Lisa Martin. You're watching the cubes coverage of snowflake summit 22 live from Las Vegas, Dave and I will be back after a short break.

>>Hello. Everyone were here it the Data Cloud summit and we had a real treat for you. I call it the CMO Power Panel. We're gonna explore how data is transforming marketing, branding and promotion, and with me, a three phenomenal marketing pros and chief marketing officers. Denise Person is the CMO Snowflakes Kat Holden of Thought spot and Laura Langdon of Whip pro Folks. Great to see you. Thanks so much for coming on the Cube. >>Great to be with you, David. >>Awesome. Denise, let's let's start with you. I want to talk about the role and the changing role of the CMO. It's changed a lot, you know, sports, of course, with all this data, but I wonder what you're experiencing and can you share us share with us? Why marketing, especially, is being impacted by data? >>Well, data is really what has helped us marketers turn ourselves into revenue drivers instead instead of call centers, and that's definitely a much better place to be. We come today measure things that were never possible before. What a person most excited about is the rial time access to data we have today. In the past, we used to get stale reports, you know, weeks after a marketing program was over. Today we get data in real time as our campaigns are up and running. And this is really what enables us to make those riel time adjustments to our investments in real time. And that is really have a profound impact on the results were having. And also today, you know, more than ever, adaptability is truly the superpower or marketing today and day. That's really what allows us to adapt to our customers preferences in real time. And that's really critical at this time. >>That's interesting what you say because, you know, in tough times used to be okay. Sales and engineering put a brick wall around those and you know the name it. Marketing, Say Okay, cut. But now it's like you go to marketing and say, Okay, what's the data say? How do we have to pivot and Scott? I wonder what of data and cloud really brought to the modern marketer that you might not have had before this modern era? >>Well, it Z this era. I don't think there's ever been a better time to be a marketer than there is right now, and The primary reason is that we have access to data and insights like we've never had, and I'm not exaggerating. When I say that I have 100 times more access to data, then I had a decade. It's just phenomenal when you look at the power of cloud search, ai These new consumer experiences for analytics. We can do things in seconds that used to take days and so it's B comments did he said. Ah, superpower for us toe. Have access to so much data and it's, you know, Kobe has been hard. Ah, lot of our marketing teams who've never worked harder, making this pivot from the physical world to the virtual world. But there, you know, at least we're working, and three other part of it is that digital she's created this phenomenal opportunity for us because the beauty of digital and digital transformation is that everything now is trackable, which makes it measurable and means that we can actually get insights that we can act on in a smarter way. And you know, it's worth giving an example. If you just look at this show right, like this event that we're doing in a physical world, all of you watching at home, you'd be in front of us in a room and we'd be able to know if you're in the room, right? We tracking the scanners when you walked in. But that's basically it. At that point, we don't really get a good sense for how much you like what we're saying. Uh, maybe you filled out a survey, but only 5 to 10% of people ever do that in the digital world. We know how long you stick around, and as a result, like it's easy people could just with the click, you know, change the channel. And so the bar for content has gone way up as we do these events. But we know how long people are sticking around. And that's what's so special about it. You know Denise and her team as the host of this show, they're going to know how long people watch this segment and that knowing is powerful. I mean, it's simple as using a product like thought spot. You could just ask a question. How many you know, what's the average view? Time by session and boom and sharp pops up. You're gonna know what's working, what's not. And that's something that you could take and act on in the future. And that's what our That's what customers were doing. So you know, snowflake in the spot that we share a customer with Lulu and they're tracking programs. So what people are watching at home, how long they're watching what they're watching next, and they're able to do that in a super granular way and improve their content as a result. And that's the power of this new world we live in. Uh, that's made the cloud and data so accessible to folks like us. >>Well, thank you for that. And I want to come back to that notion to understand how you're bringing data into your marketing office. But I wanna bring Laura and Laura were pro You guys partner with a lot of brands, a lot of companies around the world. I mean, thousands of partners, obviously snowflake and thought spot are, too. How are you using data to optimize these co marketing relationships? You know specifically, what are the trends that you're seeing around around things like customer experience? >>So, you know, we used data for all of our marketing decisions our own as well as with our partners. And I think what's really been interesting about partner marketing data is we can we can feed that back to our sales team, right? So it's very directional for them as well in their efforts moving forward. So I think that's a place where specifically to partners, it's really powerful. We can also use our collective data to go out to customers to better effect. And then, you know, regarding these trends, we just did a survey on the state of the intelligent enterprise. We we interviewed 300 companies, US and UK, and there were three Interesting. I thought statistics relevant to this, um, Onley 22% of the companies that we interviewed felt that their marketing was where it needed to be from an automation standpoint. So lots of room for us to grow right. Lots of space for us to play. And 61% of them believed that it was critical that they implement this technology to become a more intelligent enterprise. But when they ranked readiness by function, marketing came in six right, so H R R and D finance were all ahead of marketing. It was followed by sales, you know, And then the final data point that I think was interesting was 40% of those agreed that while the technology was the most important thing, that thought leadership was critical, you know? And I think that's where marketers really could bring. You know, our tried and true experience to bear and merging with this technology. >>Great. Thank you. So so did he say I've been getting the Kool Aid injection this week around Data Cloud have been pushing people, But now that I have the CMO in front of me, I wanna ask about the data cloud and what it means specifically for the customers. And what are some of the learnings? Maybe that you've experienced that can support some of the things that that Laura and Scott were just discussing. >>Yeah. Scott said before, right, he had 100 times more data than he ever has before. And that's again, if you look at all the companies we talked to around the world, it's not about the amount of data that they have. That is the problem is the ability to access that data that data for most companies is trapped across Silas across the organization. It's It's in data applications, systems of records. Some of that data sits with your partners that you want access, and that's really what the data clouds camps in. Data Cloud is really mobilizing that data for you. It brings all that data together for you in one place so you can finally access that data and really provide ubiquitous access to that data to everyone in your organization that needs it and can truly unlock the value off that data. And from a marketing perspective, I mean, we are responsible for the customer experience, you know, we provide to our customers. And if you have access toe all the data on your customers, that's when you have that customer 3 60 that we've all been talking about for so many years. And if you have all that data, you can truly, you know, look at their, you know, buying behaviors, put all those dots together and create those exceptional customer experiences. You can do things such as the retailers do in terms of personal decision, for instance, rights and those are the type of experiences in our customers are expecting today. They are expecting a 100% personalized experience for them all the time. And if you don't have all the data, you can't really put those experiences together at scale. And that is really where the data cloud comes in again. The data cloud is not only about mobilizing your own data within your enterprise. It's also about having access to data from your partners or extending access to your own data in a secure way to your partners within your ecosystems. >>Yeah, So I'm glad you mentioned a couple of things. I've been writing about this a lot, and particularly the 3 60 that we would dying for but haven't really been able to tap. I didn't call it the Data Cloud. I don't have a marketing gene. I had another sort of boring name for it, but I think there's, you know, similar vectors there. So I appreciate that. Scott, I wanna come back to this notion of building data DNA in your marketing, you know, fluency on and how you put data at the core of your marketing ops. I've been working with a lot of folks in banking and manufacturing and other industries that air that are struggling to do this. How are you doing it? What are some of the challenges that you can share and maybe some advice for your peers out there? >>Yeah, sure, it's, um Well, you brought up this concept of data fluency and it zone important one. And there's been a lot of talking industry about data literacy and being able to read data. But I think it's more important to be able to speak data to be fluent. And as marketers, we're all storytellers. And when you combine data with storytelling, magic happens. And so getting a data fluency is a great goal for us toe have for all of the people in our companies. And to get to that end, I think one of the things that's happening is that people are hiring wrong and they're thinking about it. They're making some mistakes. And so a couple of things come to mind when, especially when I look at marketing teams that I'm familiar with, they're hiring a lot of data analysts and data scientists, and those folks are amazing and every team needs them. Uh, but if you go to big on that, you do yourself a disservice. The second key thing is that you're basically giving your front lines, focus your marketing managers or people on the front lines. An excuse not to get involved data. And I think that's a big mistake because it used to be really hard. But with the technologies available to us now, these new consumer like experiences for Data Analytics, anybody can do it. And so we as leaders have to encourage them to do it. And I'll give you just a you know, an example. You know, I've got about 32 people on my marketing team, and I don't have any data analysts on my team across our entire company. We have a couple of analysts and a couple of data engineers, and what's happening is the world is changing where those folks, their enablers, they architect the system, they bring in the different status forces they use. Technologies like snowflake has been so great at making it easier for people. The folks technology together, and they get data out of it quickly. But they're pulling it together, and then we'll simple things like, Hey, I just want to see this weekly instead of monthly. You don't need to waste your expensive data science talent. Gartner puts a stand out there that 50% of data scientists are doing basic visualization work. That's not a good use of their time. You The products are >>easy >>enough now that everyday marketing managers could do that. And when you have a marketing manager come to you and say, You know, I just figured out this this campaign, which looks great on the surface, is doing poorly. From our perspective, that's a magic moment. And so we all need to coach our teams to get there. And I would say, you know, lead by example, give them an opportunity Thio access data and turn it into a story that's really powerful. And then, lastly, praised people who do it, use it as something to celebrate inside our companies is a great way to kind of get this initiative. >>E love it. You're talking about democratizing data, making it self service. People feel ownership, you know, Laura did. He starts talking about the ecosystem, and you're kind of the ecosystem pro here. How does the ecosystem help marketers succeed? Maybe you could talk about the power of many versus the resource of of one. >>Sure, you know, I think it's a it's a game changer and it will continue to be. And I think it's really the next level for marketers to harness this. This power that's out there and use it. You know, it's something that's important to us. But it's also something we're starting to see our customers demand, you know, we went from a one size fits all solution, Thio. They want to bring the best in class to their organization. We all need to be really agile and flexible right now. And I think this ecosystem allows that, you know, you think about the power of a snow plate snowflake mining data for you, and then a thought spot really giving you the dashboard toe, have what you want. And then, of course, um, implementation partner like a whip Roh coming in and really being able to plug in whatever else you need, um, to deliver. And, uh, I think it's really super powerful. And I think it gives us, you know, it just gives us so much to play with. And so much room to grow is market. >>Thank you. Did he say why don't you bring us home? We're almost out of time here, but marketing, art, science both. What do you thoughts? >>Definite? Both. I think that's exciting. Part about marketing. It is a balancing act between art and science. Clearly, it's problem or science today than it used to be. But the art part is really about inspiring change. It's about changing people's people's behavior and challenging the status quo, right? That's the art part. The science part. That's about making the right decisions all the time, right? Making sure we are truly investing in what's gonna drive revenue for us. >>Guys, thanks so much for coming on the Cube. Great discussion. Really appreciate it. Thank you for watching everybody. We're here at the data clouds summit. A lot of great content, so keep it right there. We'll be right back right after this short break.

>> 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 Summit 2022 underscored that the ecosystem excitement which was once forming around Hadoop is being reborn, escalated and coalescing around Snowflake's data cloud. What was once seen as a simpler cloud data warehouse and good marketing with the data cloud is evolving rapidly with new workloads of vertical industry focus, data applications, monetization, and more. The question is, will the promise of data be fulfilled this time around, or is it same wine, new bottle? Hello, and welcome to this week's Wikibon CUBE Insights powered by ETR. In this "Breaking Analysis," we'll talk about the event, the announcements that Snowflake made that are of greatest interest, the major themes of the show, what was hype and what was real, the competition, and some concerns that remain in many parts of the ecosystem and pockets of customers. First let's look at the overall event. It was held at Caesars Forum. Not my favorite venue, but I'll tell you it was packed. Fire Marshall Full, as we sometimes say. Nearly 10,000 people attended the event. Here's Snowflake's CMO Denise Persson on theCUBE describing how this event has evolved. >> Yeah, two, three years ago, we were about 1800 people at a Hilton in San Francisco. We had about 40 partners attending. This week we're close to 10,000 attendees here. Almost 10,000 people online as well, and over over 200 partners here on the show floor. >> Now, those numbers from 2019 remind me of the early days of Hadoop World, which was put on by Cloudera but then Cloudera handed off the event to O'Reilly as this article that we've inserted, if you bring back that slide would say. The headline it almost got it right. Hadoop World was a failure, but it didn't have to be. Snowflake has filled the void created by O'Reilly when it first killed Hadoop World, and killed the name and then killed Strata. Now, ironically, the momentum and excitement from Hadoop's early days, it probably could have stayed with Cloudera but the beginning of the end was when they gave the conference over to O'Reilly. We can't imagine Frank Slootman handing the keys to the kingdom to a third party. Serious business was done at this event. I'm talking substantive deals. Salespeople from a host sponsor and the ecosystems that support these events, they love physical. They really don't like virtual because physical belly to belly means relationship building, pipeline, and deals. And that was blatantly obvious at this show. And in fairness, all theCUBE events that we've done year but this one was more vibrant because of its attendance and the action in the ecosystem. Ecosystem is a hallmark of a cloud company, and that's what Snowflake is. We asked Frank Slootman on theCUBE, was this ecosystem evolution by design or did Snowflake just kind of stumble into it? Here's what he said. >> Well, when you are a data clouding, you have data, people want to do things with that data. They don't want just run data operations, populate dashboards, run reports. Pretty soon they want to build applications and after they build applications, they want build businesses on it. So it goes on and on and on. So it drives your development to enable more and more functionality on that data cloud. Didn't start out that way, you know, we were very, very much focused on data operations. Then it becomes application development and then it becomes, hey, we're developing whole businesses on this platform. So similar to what happened to Facebook in many ways. >> So it sounds like it was maybe a little bit of both. The Facebook analogy is interesting because Facebook is a walled garden, as is Snowflake, but when you come into that garden, you have assurances that things are going to work in a very specific way because a set of standards and protocols is being enforced by a steward, i.e. Snowflake. This means things run better inside of Snowflake than if you try to do all the integration yourself. Now, maybe over time, an open source version of that will come out but if you wait for that, you're going to be left behind. That said, Snowflake has made moves to make its platform more accommodating to open source tooling in many of its announcements this week. Now, I'm not going to do a deep dive on the announcements. Matt Sulkins from Monte Carlo wrote a decent summary of the keynotes and a number of analysts like Sanjeev Mohan, Tony Bear and others are posting some deeper analysis on these innovations, and so we'll point to those. I'll say a few things though. Unistore extends the type of data that can live in the Snowflake data cloud. It's enabled by a new feature called hybrid tables, a new table type in Snowflake. One of the big knocks against Snowflake was it couldn't handle and transaction data. Several database companies are creating this notion of a hybrid where both analytic and transactional workloads can live in the same data store. Oracle's doing this for example, with MySQL HeatWave and there are many others. We saw Mongo earlier this month add an analytics capability to its transaction system. Mongo also added sequel, which was kind of interesting. Here's what Constellation Research analyst Doug Henschen said about Snowflake's moves into transaction data. Play the clip. >> Well with Unistore, they're reaching out and trying to bring transactional data in. Hey, don't limit this to analytical information and there's other ways to do that like CDC and streaming but they're very closely tying that again to that marketplace, with the idea of bring your data over here and you can monetize it. Don't just leave it in that transactional database. So another reach to a broader play across a big community that they're building. >> And you're also seeing Snowflake expand its workload types in its unique way and through Snowpark and its stream lit acquisition, enabling Python so that native apps can be built in the data cloud and benefit from all that structure and the features that Snowflake is built in. Hence that Facebook analogy, or maybe the App Store, the Apple App Store as I propose as well. Python support also widens the aperture for machine intelligence workloads. We asked Snowflake senior VP of product, Christian Kleinerman which announcements he thought were the most impactful. And despite the who's your favorite child nature of the question, he did answer. Here's what he said. >> I think the native applications is the one that looks like, eh, I don't know about it on the surface but he has the biggest potential to change everything. That's create an entire ecosystem of solutions for within a company or across companies that I don't know that we know what's possible. >> Snowflake also announced support for Apache Iceberg, which is a new open table format standard that's emerging. So you're seeing Snowflake respond to these concerns about its lack of openness, and they're building optionality into their cloud. They also showed some cost op optimization tools both from Snowflake itself and from the ecosystem, notably Capital One which launched a software business on top of Snowflake focused on optimizing cost and eventually the rollout data management capabilities, and all kinds of features that Snowflake announced that the show around governance, cross cloud, what we call super cloud, a new security workload, and they reemphasize their ability to read non-native on-prem data into Snowflake through partnerships with Dell and Pure and a lot more. Let's hear from some of the analysts that came on theCUBE this week at Snowflake Summit to see what they said about the announcements and their takeaways from the event. This is Dave Menninger, Sanjeev Mohan, and Tony Bear, roll the clip. >> Our research shows that the majority of organizations, the majority of people do not have access to analytics. And so a couple of the things they've announced I think address those or help to address those issues very directly. So Snowpark and support for Python and other languages is a way for organizations to embed analytics into different business processes. And so I think that'll be really beneficial to try and get analytics into more people's hands. And I also think that the native applications as part of the marketplace is another way to get applications into people's hands rather than just analytical tools. Because most people in the organization are not analysts. They're doing some line of business function. They're HR managers, they're marketing people, they're sales people, they're finance people, right? They're not sitting there mucking around in the data, they're doing a job and they need analytics in that job. >> Primarily, I think it is to contract this whole notion that once you move data into Snowflake, it's a proprietary format. So I think that's how it started but it's usually beneficial to the customers, to the users because now if you have large amount of data in paket files you can leave it on S3, but then you using the Apache Iceberg table format in Snowflake, you get all the benefits of Snowflake's optimizer. So for example, you get the micro partitioning, you get the metadata. And in a single query, you can join, you can do select from a Snowflake table union and select from an iceberg table and you can do store procedure, user defined function. So I think what they've done is extremely interesting. Iceberg by itself still does not have multi-table transactional capabilities. So if I'm running a workload, I might be touching 10 different tables. So if I use Apache Iceberg in a raw format, they don't have it, but Snowflake does. So the way I see it is Snowflake is adding more and more capabilities right into the database. So for example, they've gone ahead and added security and privacy. So you can now create policies and do even cell level masking, dynamic masking, but most organizations have more than Snowflake. So what we are starting to see all around here is that there's a whole series of data catalog companies, a bunch of companies that are doing dynamic data masking, security and governance, data observability which is not a space Snowflake has gone into. So there's a whole ecosystem of companies that is mushrooming. Although, you know, so they're using the native capabilities of Snowflake but they are at a level higher. So if you have a data lake and a cloud data warehouse and you have other like relational databases, you can run these cross platform capabilities in that layer. So that way, you know, Snowflake's done a great job of enabling that ecosystem. >> I think it's like the last mile, essentially. In other words, it's like, okay, you have folks that are basically that are very comfortable with Tableau but you do have developers who don't want to have to shell out to a separate tool. And so this is where Snowflake is essentially working to address that constituency. To Sanjeev's point, and I think part of it, this kind of plays into it is what makes this different from the Hadoop era is the fact that all these capabilities, you know, a lot of vendors are taking it very seriously to put this native. Now, obviously Snowflake acquired Streamlit. So we can expect that the Streamlit capabilities are going to be native. >> I want to share a little bit about the higher level thinking at Snowflake, here's a chart from Frank Slootman's keynote. It's his version of the modern data stack, if you will. Now, Snowflake of course, was built on the public cloud. If there were no AWS, there would be no Snowflake. Now, they're all about bringing data and live data and expanding the types of data, including structured, we just heard about that, unstructured, geospatial, and the list is going to continue on and on. Eventually I think it's going to bleed into the edge if we can figure out what to do with that edge data. Executing on new workloads is a big deal. They started with data sharing and they recently added security and they've essentially created a PaaS layer. We call it a SuperPaaS layer, if you will, to attract application developers. Snowflake has a developer-focused event coming up in November and they've extended the marketplace with 1300 native apps listings. And at the top, that's the holy grail, monetization. We always talk about building data products and we saw a lot of that at this event, very, very impressive and unique. Now here's the thing. There's a lot of talk in the press, in the Wall Street and the broader community about consumption-based pricing and concerns over Snowflake's visibility and its forecast and how analytics may be discretionary. But if you're a company building apps in Snowflake and monetizing like Capital One intends to do, and you're now selling in the marketplace, that is not discretionary, unless of course your costs are greater than your revenue for that service, in which case is going to fail anyway. But the point is we're entering a new error where data apps and data products are beginning to be built and Snowflake is attempting to make the data cloud the defacto place as to where you're going to build them. In our view they're well ahead in that journey. Okay, let's talk about some of the bigger themes that we heard at the event. Bringing apps to the data instead of moving the data to the apps, this was a constant refrain and one that certainly makes sense from a physics point of view. But having a single source of data that is discoverable, sharable and governed with increasingly robust ecosystem options, it doesn't have to be moved. Sometimes it may have to be moved if you're going across regions, but that's unique and a differentiator for Snowflake in our view. I mean, I'm yet to see a data ecosystem that is as rich and growing as fast as the Snowflake ecosystem. Monetization, we talked about that, industry clouds, financial services, healthcare, retail, and media, all front and center at the event. My understanding is that Frank Slootman was a major force behind this shift, this development and go to market focus on verticals. It's really an attempt, and he talked about this in his keynote to align with the customer mission ultimately align with their objectives which not surprisingly, are increasingly monetizing with data as a differentiating ingredient. We heard a ton about data mesh, there were numerous presentations about the topic. And I'll say this, if you map the seven pillars Snowflake talks about, Benoit Dageville talked about this in his keynote, but if you map those into Zhamak Dehghani's data mesh framework and the four principles, they align better than most of the data mesh washing that I've seen. The seven pillars, all data, all workloads, global architecture, self-managed, programmable, marketplace and governance. Those are the seven pillars that he talked about in his keynote. All data, well, maybe with hybrid tables that becomes more of a reality. Global architecture means the data is globally distributed. It's not necessarily physically in one place. Self-managed is key. Self-service infrastructure is one of Zhamak's four principles. And then inherent governance. Zhamak talks about computational, what I'll call automated governance, built in. And with all the talk about monetization, that aligns with the second principle which is data as product. So while it's not a pure hit and to its credit, by the way, Snowflake doesn't use data mesh in its messaging anymore. But by the way, its customers do, several customers talked about it. Geico, JPMC, and a number of other customers and partners are using the term and using it pretty closely to the concepts put forth by Zhamak Dehghani. But back to the point, they essentially, Snowflake that is, is building a proprietary system that substantially addresses some, if not many of the goals of data mesh. Okay, back to the list, supercloud, that's our term. We saw lots of examples of clouds on top of clouds that are architected to spin multiple clouds, not just run on individual clouds as separate services. And this includes Snowflake's data cloud itself but a number of ecosystem partners that are headed in a very similar direction. Snowflake still talks about data sharing but now it uses the term collaboration in its high level messaging, which is I think smart. Data sharing is kind of a geeky term. And also this is an attempt by Snowflake to differentiate from everyone else that's saying, hey, we do data sharing too. And finally Snowflake doesn't say data marketplace anymore. It's now marketplace, accounting for its application market. Okay, let's take a quick look at the competitive landscape via this ETR X-Y graph. Vertical access remembers net score or spending momentum and the x-axis is penetration, pervasiveness in the data center. That's what ETR calls overlap. Snowflake continues to lead on the vertical axis. They guide it conservatively last quarter, remember, so I wouldn't be surprised if that lofty height, even though it's well down from its earlier levels but I wouldn't be surprised if it ticks down again a bit in the July survey, which will be in the field shortly. Databricks is a key competitor obviously at a strong spending momentum, as you can see. We didn't draw it here but we usually draw that 40% line or red line at 40%, anything above that is considered elevated. So you can see Databricks is quite elevated. But it doesn't have the market presence of Snowflake. It didn't get to IPO during the bubble and it doesn't have nearly as deep and capable go-to market machinery. Now, they're getting better and they're getting some attention in the market, nonetheless. But as a private company, you just naturally, more people are aware of Snowflake. Some analysts, Tony Bear in particular, believe Mongo and Snowflake are on a bit of a collision course long term. I actually can see his point. You know, I mean, they're both platforms, they're both about data. It's long ways off, but you can see them sort of in a similar path. They talk about kind of similar aspirations and visions even though they're quite in different markets today but they're definitely participating in similar tam. The cloud players are probably the biggest or definitely the biggest partners and probably the biggest competitors to Snowflake. And then there's always Oracle. Doesn't have the spending velocity of the others but it's got strong market presence. It owns a cloud and it knows a thing about data and it definitely is a go-to market machine. Okay, we're going to end on some of the things that we heard in the ecosystem. 'Cause look, we've heard before how particular technology, enterprise data warehouse, data hubs, MDM, data lakes, Hadoop, et cetera. We're going to solve all of our data problems and of course they didn't. And in fact, sometimes they create more problems that allow vendors to push more incremental technology to solve the problems that they created. Like tools and platforms to clean up the no schema on right nature of data lakes or data swamps. But here are some of the things that I heard firsthand from some customers and partners. First thing is, they said to me that they're having a hard time keeping up sometimes with the pace of Snowflake. It reminds me of AWS in 2014, 2015 timeframe. You remember that fire hose of announcements which causes increased complexity for customers and partners. I talked to several customers that said, well, yeah this is all well and good but I still need skilled people to understand all these tools that I'm integrated in the ecosystem, the catalogs, the machine learning observability. A number of customers said, I just can't use one governance tool, I need multiple governance tools and a lot of other technologies as well, and they're concerned that that's going to drive up their cost and their complexity. I heard other concerns from the ecosystem that it used to be sort of clear as to where they could add value you know, when Snowflake was just a better data warehouse. But to point number one, they're either concerned that they'll be left behind or they're concerned that they'll be subsumed. Look, I mean, just like we tell AWS customers and partners, you got to move fast, you got to keep innovating. If you don't, you're going to be left. Either if your customer you're going to be left behind your competitor, or if you're a partner, somebody else is going to get there or AWS is going to solve the problem for you. Okay, and there were a number of skeptical practitioners, really thoughtful and experienced data pros that suggested that they've seen this movie before. That's hence the same wine, new bottle. Well, this time around I certainly hope not given all the energy and investment that is going into this ecosystem. And the fact is Snowflake is unquestionably making it easier to put data to work. They built on AWS so you didn't have to worry about provisioning, compute and storage and networking and scaling. Snowflake is optimizing its platform to take advantage of things like Graviton so you don't have to, and they're doing some of their own optimization tools. The ecosystem is building optimization tools so that's all good. And firm belief is the less expensive it is, the more data will get brought into the data cloud. And they're building a data platform on which their ecosystem can build and run data applications, aka data products without having to worry about all the hard work that needs to get done to make data discoverable, shareable, and governed. And unlike the last 10 years, you don't have to be a keeper and integrate all the animals in the Hadoop zoo. Okay, that's it for today, thanks for watching. Thanks to my colleague, Stephanie Chan who helps research "Breaking Analysis" topics. Sometimes Alex Myerson is on production and manages the podcasts. Kristin Martin and Cheryl Knight help get the word out on social and in our newsletters, and Rob Hof is our editor in chief over at Silicon, and Hailey does some wonderful editing, thanks to all. Remember, all these episodes are available as podcasts wherever you listen. All you got to do is search Breaking Analysis Podcasts. I publish each week on wikibon.com and siliconangle.com and you can email me at David.Vellante@siliconangle.com or DM me @DVellante. If you got something interesting, I'll respond. If you don't, I'm sorry I won't. Or comment on my LinkedIn post. Please check out etr.ai for the best survey data in the enterprise tech business. This is Dave Vellante for theCUBE Insights powered by ETR. Thanks for watching, and we'll see you next time. (upbeat music)

>> Hello everyone, we're here at the Data Cloud Summit, and we have a real treat for you. I call it the CMO Power Panel. And we're going to explore how data is transforming marketing, branding and promotion. And with me are three phenomenal marketing pros and chief marketing officers. Denise Persson is the CMO of Snowflake, Scott Holden of ThoughtSpot and Laura Langdon of Wipro. Folks, great to see you. Thanks so much for coming on "theCUBE." >> Great to be here with you David. >> Awesome, Denise, let's start with you. I want to talk about the role and the changing role of the CMOs, has changed a lot, you know, I suppose of course with all this data, but I wonder what you're experiencing and can you share with us why marketing especially is being impacted by data. >> Well data's really what has helped turn us marketers into revenue drivers, into call centers. And it's clearly a much better place to be. What I'm personally most excited about is the real time access we have to data today. In the past, I used to get a stale report a few weeks after a marketing program was over and at that time we couldn't make any changes to the investments we'd already made. Today, we get data in the midst of running a program. So it can reallocate investments at the time a program is up and running and that's really profound. Today as well, I would say that adaptability has truly become the true superpowers of marketing today and data is really what enables us to adapt to scale. We can adapt to customer's behavior and preferences at scale and that's truly a profound new way of working as well. >> That's interesting what you say cause you know, in tough times used to be okay, sales and engineering, put a brick wall around those and you know, you name it marketing, say, "Okay, cut." But now it's like, you go to marketing and say, "Okay, what's the data say, "how do we have to pivot?" And Scott, I wonder what have data and cloud really brought to the modern marketer that you might not have had before through to this modern era? >> Well, this era, I don't think there's ever been a better time to be a marketer than there is right now. And the primary reason is that we have access to data and insights like we've never had before and I'm not exaggerating when I say that I have a hundred times more access to data than I had a decade ago. It's just phenomenal. When you look at the power of cloud, search, AI, these new consumer experiences for analytics, we can do things in seconds that used to take days. And so it's become in us, as Denise said a super power for us to have access to so much data. And it's, you know, COVID has been hard. A lot of our marketing teams who never worked harder making this pivot from the physical world to the virtual world but they're, you know, at least we're working. And the other part of it is that digital has just created this phenomenal opportunity for us because the beauty of digital and digital transformation is that everything now is trackable, which makes it measurable and means that we can actually get insights that we can act on in a smarter way. And you know, it's worth giving an example. If you just look at this show, right? Like this event that we're viewing. In a physical world, all of you watching at home you'd be in front of us in a room and we'd be able to know if you're in the room, right? We'd track to the scanners when you walked in but that's basically it. At that point, we don't really get a good sense for how much you like, what we're saying. You know, maybe you filled out a survey, but only five to 10% of people ever do that. In a digital world, we know how long you stick around. And as a result, like it's easy, people can just with a click, you know, change the channel. And so the bar for content has gone way up as we do these events but we know how long people are sticking around. And that's, what's so special about it. You know, Denise and her team, as the host of this show they're going to know how long people watch this segment. And that knowing is powerful. I mean, it's simple as you know, using a product like ThoughtSpot, you could just ask a question, you know, how many, you know, what's the average view time by session and Bloomer chart pops up. You're going to know what's working and what's not. And that's something that you can take and act on in the future. And that's what our customers are doing. So, you know, Snowflake and ThoughtSpot, we share our customer with Hulu and they're tracking programs. So, what people are watching at home, how long they're watching, what they're watching next. And they're able to do that in a super granular way and improve their content as a result. And that's the power of this new world we live in that's made the cloud and data so accessible to folks like us. >> Well, thank you for that. And I want to come back to that notion and understand how you're bringing data into your marketing ops, but I want to bring Laura in. Laura, Wipro, you guys partner with a lot of brands, a lot of companies around the world. I mean, thousands of partners, obviously Snowflake in ThoughtSpot or two. How are you using data to optimize these co-marketing relationships? You know, specifically, what what are the trends that you're seeing around things like customer experience? >> So, you know, we use data for all of our marketing decisions, our own, as well as with our partners. And I think what's really been interesting about partner marketing data is we can feed that back to our sales team, right? So, it's very directional for them as well and their efforts moving forward. So, I think that's a place where specifically to partners, it's really powerful. We can also use our collected data to go out to customers to better effect. And then you know, regarding these trends, we just did a survey on the state of the intelligent enterprise. We interviewed 300 companies, US and UK, and there were three interesting I thought statistics relevant to this. Only 22% of the companies that we interviewed felt that their marketing was where it needed to be from an automation standpoint. So lots of room for us to grow, right? Lots of space for us to play. And 61% of them believe that it was critical that they implement this technology to become a more intelligent enterprise. But when they ranked on readiness by function, marketing came in six, right? So HR, RND, finance were all ahead of marketing followed by sales. You know, and then the final data point that I think was interesting was 40% of those agreed that the technology was the most important thing, that thought leadership was critical. You know, and I think that's where marketers really can bring our tried and true experience to bear and merge it with this technology. >> Great, thank you. So, Denise, I've been getting the Kool-Aid injection this week around Data Cloud. I've been pushing people but now that I have the CMO in front of me, I want to ask about the Data Cloud and what it means specifically for the customers and what are some of the learnings maybe that you've experienced that can support some of the things that that Laura and Scott were just discussing. >> Yeah, as Scott said before, idea of a hundred times more data than he ever has before. And that's again, if you look at all the companies we talked to around the world it's not about the amount of data that they have that is the problem, it's the ability to access that data. That data for most companies is trapped across silos, across the organization. It sits in data applications, systems or records. Some of that data sits with your partners that you want to access. And that's really what the data cloud comes in. Data cloud is really mobilizing that data for you. It brings all that data together for you in one place. So you can finally access that data and really provide ubiquitous access to that data to everyone in your organization that needs it and can truly unlock the value of that data. And from a marketing perspective, I mean, we are responsible for the customer experience you know, we provide to our customers and if you have access to all the data on your customers, that's when you have that to customer 360, that we've all been talking about for so many years. And if you have all that data, you can truly, you know, look at their, you know, buying behaviors, put all those dots together and create those exceptional customer experiences. You can do things such as the retailers do in terms of personal decision, for instance, right? And those are the types of experiences, you know, our customers are expecting today. They are expecting a 100% personalized experience for them you know, all the time. And if you don't have all the data, you can't really put those experiences together at scale. And that is really where the data cloud comes in. Again, the data cloud is not only about mobilizing your own data within your enterprise. It's also about having access to data from your partners or extending access to your own data in a secure way to your partners within your ecosystems. >> Yeah, so I'm glad you mentioned a couple of things. I've been writing about this a lot and in particularly the 360 that we were dying for, but haven't really been able to tap. I didn't call it the data cloud, I don't have a marketing gene. I had another sort of boring name for it, but I think there's similar vectors there. So I appreciate that. Scott, I want to come back to this notion of building data DNA in your marketing, you know, fluency and how you put data at the core of your marketing ops. I've been working with a lot of folks in banking and manufacturing and other industries that are that are struggling to do this. How are you doing it? What are some of the challenges that you can share and maybe some advice for your peers out there? >> Yeah, sure, you brought up this concept of data fluency and it's an important one. And there's been a lot of talk in the industry about data literacy and being able to read data. But I think it's more important to be able to speak data, to be fluent and as marketers, we're all storytellers. And when you combine data with storytelling, magic happens. And so, getting a data fluency is a great goal for us to have for all of the people in our companies. And to get to that end, I think one of the things that's happening is that people are hiring wrong and they're thinking about it, they're making some mistakes. And so a couple of things come to mind especially when I look at marketing teams that I'm familiar with. They're hiring a lot of data analysts and data scientists and those folks are amazing and every team needs them. But if you go too big on that, you do yourself a disservice. The second key thing is that you're basically giving your frontline folks, your marketing managers or people on the front lines, an excuse not to get involved with data. And then that's a big mistake because it used to be really hard. But with the technologies available to us now, these new consumer like experiences for data analytics, anybody can do it. And so we as leaders have to encourage them to do it. And I'll give you just a you know, an example, you know, I've got about 32 people on my marketing team and I don't have any data analysts on my team. Across our entire company, we have a couple of analysts and a couple of data engineers. And what's happening is the world is changing where those folks, they're enablers, they architect the system. They bring in the different data sources. They use technologies like Snowflake as being so great at making it easier for people to pull spectrum technology together and to get access to data out of it quickly, but they're pulling it together and then simple things like, "Hey I just want to see this "weekly instead of monthly." You don't need to waste your expensive data science talent. You know, Gardener puts a stat out there that 50% of data scientists are doing basic visualization work. That's not a good use of their time. The products are easy enough now that everyday marketing managers can do that. And when you have a marketing manager come to you and say, you know, "I just figured out "this campaign which looks great on the surface "is doing poorly from an ROI perspective. That's a magic moment. And so we all need to coach our teams to get there. And I would say, you know, lead by example, give them an opportunity to access data and turn it into a story, that's really powerful. And then lastly, praise people who do it, like, use it as something to celebrate inside our companies is a great way to kind of get this initiative. >> I love it. And talking about democratizing data and making it self service, people feel ownership. You know, Laura, Denise was talking about the ecosystem and you're kind of the ecosystem pro here. How does the ecosystem help marketers succeed? Maybe you can talk about the power of many versus the resource of one. >> Sure, you know, I think it's a game changer and it will continue to be. And I think it's really the next level for marketers to harness this power that's out there and use it, you know, and it's something that's important to us, but it's also something we're starting to see our customers demand. You know, we went from a one size fits all solution to they want to bring the best in class to their organization. We all need to be really agile and flexible right now. And I think this ecosystem allows that, you know, you think about the power of Snowflake, Snowflake mining data for you and then a ThoughtSpot really giving you the dashboard to have what you want. And then an implementation partner like a Wipro coming in, and really being able to plug in whatever else you need to deliver. And I think it's really super powerful and I think it gives us you know, it just gives us so much to play with and so much room to grow as marketers. >> Thank you, Denise, why don't you bring us home. We're almost out of time here, but marketing, art, science, both? What are your thoughts? >> Definitely both, I think that's the exciting part about marketing. It is a balancing act between art and science. Clearly, it's probably more science today than it used to be but the art part is really about inspiring change. It's about changing people's behavior and challenging the status quo, right? That's the art part. The science part, that's about making the right decisions all the time, right? It's making sure we are truly investing in what's going to drive revenue for us. >> Guys, thanks so much for coming on "theCUBE." Great discussion, I really appreciate it. Okay, and thank you for watching. Keep it right there. Wall-to-wall coverage of the Snowflake Data Cloud Summit on "theCUBE."