>> Hello everybody. And welcome back to, theCUBE coverage of the Snowflake Data Cloud Summit 2020. We're tracking the rise of the Data Cloud, and fresh off the keynotes here, Frank Slootman, the Chairman and CEO of Snowflake and Anita Lynch, the Vice President of data governance at Disney streaming services. Folks Welcome. >> Thank you >> Thanks for having us Dave. >> Anita Disney plus awesome. You know, we signed up early, watched all the Marvel movies, Hamilton, the new Pixar movie soul. I haven't gotten it to the Mandalorian yet, your favorite. But really appreciate you guys coming on. Let me start with Frank. I'm glad you're putting forth this vision around the Data Cloud, because I never liked the term enterprise data warehouse. What you're doing is so different from the sort of that legacy world that I've known all these years. But start with why the Data Cloud? What problems are you trying to solve? And maybe some of the harder challenges you're seeing. >> Yeah, you know, we have a, we've come a long way in terms of workload execution. Right? In terms of scale and performance, and concurrent execution. We've really taken the lid off, sort of the physical constraints that have existed on these type of operations. But there's one problem that we're not yet solving, and that is the siloing and bunkering of data. And essentially, data is locked in applications, it's locked in data centers, it's locked in cloud, cloud regions. Incredibly hard for data science teams to really unlock the true value of data, when you can't address patterns that exist across data sets. So where we perpetuate a status we've had for forever since the beginning of computing. If we don't start to crack that problem now we have that opportunity. But the notion of a Data Cloud is like basically saying, "Look folks, we have to start on siloing and unlocking the data, and bring it into a place, where we can access it across all these perimeters, and boundaries that have historically existed. It's very much a step level function. Like the customers have always looked at things, one workload at a time, that mentality really has to go. You really have to have a Data Cloud mentality, as well as a workload orientation towards managing data. >> Anita, it was great hearing your role at Disney and in your keynote, and the work you're doing, the governance work. and you're serving a great number of stakeholders, enabling things like data sharing. You got really laser focused on trust, compliance, privacy. This idea of a data clean room is really interesting. Maybe you can expand on some of these initiatives here, and share what you're seeing as some of the biggest challenges to success, and of course, the opportunities that you're unlocking. >> Sure. In my role leading data governance, it's really critical to make sure that all of our stakeholders not only know what data is available and accessible to them. They can also understand really easily and quickly, whether or not the data that they're using is for the appropriate use case. And so that's a big part of how we scale data governance, and a lot of the work that we would normally have to do manually is actually done for us through the data clean rooms. >> Thank you for that. I wonder if you could talk a little bit more about the role of data and how your data strategy has evolved and maybe discuss some of the things that Frank mentioned about data silos. And I mean, obviously you can relate to that having been in the data business for a while, but I wonder if you can elucidate on that. >> Sure. I mean, data complexities are going to evolve over time in any traditional data architecture simply because you often have different teams at different periods and time trying to analyze and gather data across a whole lot of different sources. And the complexity that just arises out of that is due to the different needs of specific stakeholders. There are time constraints and quite often, it's not always clear how much value they're going to be able to extract from the data at the outset. So what we've tried to do to help break down those silos is allow individuals to see upfront how much value they're going to get from the data by knowing that it's trustworthy right away. By knowing that it's something that they can use in their specific use case right away. And by ensuring that essentially as they're continuing to kind of scale the use cases that they're focused on, they're no longer required to make multiple copies of the data, do multiple steps to reprocess the data. And that makes all the difference in the world. >> Yeah, for sure. I'm a copy Creek because it'd be the silent killer. Frank I followed you for a number of years, you're a big thinker, you and I have had a lot of conversations about the near-term, mid-term and long-term, I wonder if you could talk about, in your keynote you're talking about eliminating silos and connecting across data sources. Which is really powerful concept but really only if people are willing and able to connect and collaborate. Where do you see that happening? Maybe what are some of the blockers there? >> Well, there's certainly a natural friction there. I still remember when we first started to talk to, Salesforce, you know, they had discovered that we were a top three destination of Salesforce data and they were wondering why that was, and the reason is of course, that people take Salesforce data push it to snowflake because they want to overlay it with what data outside of Salesforce. Whether it's Adobe or any other marketing dataset. And then they want to run very highly scaled processes on it. But the reflexes in the world of SaaS is always like no, we're an Island, we're a planet down to ourselves. Everybody needs to come with us, as opposed to we go to a different platform to run these types of processes. It's no different for the public cloud vendor. They didn't only, they have massive moats around their storage to really prevent data from leaving their orbit. So there is natural friction in terms for this to happen. But on the other hand there is an enormous need. We can't deliver on the power and potential of data unless we allow it to come together. Snowflake is the platform that allows that to happen. We were pleased with our relationship with Salesforce because they did appreciate why this was important and why this was necessary. And we think, other parts of the industry will gradually come around to it as well. So the idea of a Data Cloud has really come, right. When people are recognizing why this matters now. It's not going to happen overnight. It is a step while will function a very big change in mentality and orientation. >> Yeah. It's almost as though the the SaaS suffocation of our industry sort of repeated some of the application silos and you build a hardened top around it, all the processes are hardened around it and okay, here we go. And you're really trying to break that, aren't you? >> Yep, exactly. >> Anita, again, I want to come back to this notion of governance. It's so it's so important. It's the first role in your title and it really underscores the importance of this. You know, Frank was just talking about some of the hurdles and this is a big one. I mean, we saw this in the early days of big data where governance was just afterthought. It was like bolted on the kind of wild wild West. I'm interested in your governance journey. And maybe you can share a little bit about what role snowflake has played there in terms of supporting that agenda and kind of what's next on that journey. >> Sure. Well, I've led data teams in numerous ways over my career. This is the first time that I've actually had the opportunity to focus on governance and what it's done is allowed for my organization to scale much more rapidly. And that's so critically important for our overall strategy as a company. >> Well, I mean, a big part of what you were talking about at least my inference in your talk was really that the business folks didn't have to care about, you know, wonder about they cared about it, but they don't have to wonder about, and about the privacy concerns, et cetera. You've taken care of all that it's sort of transparent to them. Is that right?| >> Yea That's right absolutely. So we focus on ensuring compliance across all of the different regions where we operate. We also partner very heavily with our legal and information security teams. They're critical to ensuring that we're able to do this. we don't do it alone. But governance includes not just the compliance and the privacy, it's also about data access, and it's also about ensuring data quality. And so all of that comes together under the governance umbrella. I also lead teams that focus on things like instrumentation, which is how we collect data. We focus on the infrastructure and making sure that we've architected for scale and all of these are really important components of our strategy. >> I got a...So I have a question maybe each of you can answer. I sort of see this, our industry moving from products, to then, to platforms and platforms even evolving into ecosystems. And then there's this ecosystem of data. You guys both talked a lot about data sharing but maybe Frank, you can start, Anita you can add on to Frank's answer. You're obviously both passionate about the use of data and trying to do so in a responsible way. That's critical but it's also going to have business impact. Frank, where's this passion come from on your side. And how are you putting into action in your own organization? >> Well, you know I'm really going to date myself here, but many, many years ago, I saw the first glimpse of multidimensional databases that were used for reporting really on IBM mainframes. And it was extraordinarily difficult. We didn't even have the words back then in terms of data warehouses and business. All these terms didn't exist. People just knew that they wanted to have a more flexible in way of reporting and being able to pivot data dimensionally and all these kinds of things. And I just bought whatever this predates windows 3.1, which really, set off the whole sort of graphical, way of dealing with systems which there's now a whole generations of people that don't know any different right? So I've lived the pain of this problem and sort of had a front row seat to watching this transpire over a very long period of time. And that's one of the reasons, why I'm here, because I finally seen, a glimpse of, I also, as an industry fully, fully just unleashing and unlocking to potential. We're now in a place where the technology is ahead of people's ability to harness it. Which we've never been there before. It was always like, we wanted to do things that technology wouldn't let us. It's different now. I mean, people are just, their heads are spinning with what's now possible, which is why you see markets evolve, very rapidly right now we were talking earlier about how you can't take past definitions and concepts and apply them to what's going on in the world. because the world's changing right in front of your eyes right now. >> So Anita maybe you could add on to what Frank just said and share some of the business impacts and outcomes that are notable since you've really applied your your love of data and maybe, maybe touch on, on culture. Data culture, any words of wisdom for folks in the audience who might be thinking about embarking on a Data Cloud journey, similar to what you've been on. >> Yeah sure. I think for me, I fell in love with technology first and then I fell in love with data. And I fell in love with data because of the impact that data can have on both the business and the technology strategy. And so it's sort of that nexus, between all three. And in terms of my career journey and some of the impacts that I've seen. I mean, I think with the advent of the cloud, before, well, how do I say that. Before the cloud actually became so prevalent and such a common part of the strategy that's required it was so difficult, you know, so painful. It took so many hours to actually be able to calculate the volumes of data that we had. Now we have that accessibility, and then on top of it, with the snowflake Data Cloud it's much more performance oriented from a cost perspective because you don't have multiple copies of the data, or at least you don't have to have multiple copies of the data. And I think moving beyond some of the traditional mechanisms for for measuring business impact, has only been possible with the volumes of data that we have available to us today. And it's just, it's phenomenal to see the speed at which we can operate. And really, truly understand our customer's interests and their preferences and then tailor the experiences that they really want and deserve for them. It's, been a great feeling to get to this point in time. >> That's fantastic. So, Frank, I got to ask you this. So in your spare time you decided to write a book, I'm loving it. I don't have a signed copy so I'm going to have to send it back and have you sign it. But, and you're, I love the inside baseball. It's just awesome. So really appreciate that. So, but why did you decide to write a book? >> Well, there were a couple of reasons, obviously we thought of as an interesting tale to tell for anybody, who is interested in what's going on, how did this come about? Who are the characters behind the scenes and all this stuff. But from a business standpoint because this is such a step function it's so non incremental, we felt like, we really needed quite a bit of real estate to really lay out what the full narrative and context is. And, we thought, the books titled the "Rise of the Data Cloud." That's exactly what it is. And we're trying to make the case for that mindset, that mentality, that strategy because all of us, I think as an industry, were at risk of, persisting, perpetuating where we've been since the beginning of computing. So we're really trying to make a pretty forceful case for a look. There's an enormous opportunity out there but there's some choices you have to make along the way. >> Guys, we got to leave it there. Frank, I know you and I are going to talk again Anita, I hope we have a chance to meet face to face and talk in theCUBE live someday. You're phenomenal guests and what a great story. Thank you both for coming on. And thank you for watching. Keep it right there. You're watching the, Snowflake Data Cloud Summit, on theCUBE.

>>Hello, buddy. And welcome back to the cubes. Coverage of Snowflake Data Cloud Summer 2020. We're tracking the rise of the data cloud and fresh off the keynotes. Hear Frank's Luqman, the chairman and CEO of Snowflake, and Anita Lynch, the vice president of data governance at Disney Streaming Services. Folks. Welcome E Need a Disney plus. Awesome. You know, we signed up early. Watched all the Marvel movies. Hamilton, the new Pixar movie Soul. I haven't gotten to the man DeLorean yet. Your favorite, but I really appreciate you guys coming on. Let me start with Frank. I'm glad you're putting forth this vision around the data cloud because I never liked the term Enterprise Data Warehouse. What you're doing is is so different from the sort of that legacy world that I've known all these years. But start with why the data cloud? What problems are you trying to solve? And maybe some of the harder challenges you're seeing? >>Yeah. You know, we have We've come a long way in terms of workload, execution, right? In terms of scale and performance and concurrent execution. We really taking the lid off. Sort of the physical constraints that that have existed on these types of operations. But there's one problem, uh, that were not yet, uh solving. And that is the silo ing and bunkering of data essentially in the data is locked in applications. It's locked in data centers. It's locked in cloud cloud regions incredibly hard for for data science teams to really unlock the true value of data when you when you can address patterns that that exists across data set. So we're perpetuate, uh, status we've had for for ever since the beginning off computing. If we don't start Thio, crack that problem now we have that opportunity. But the notion of a data cloud is like basically saying, Look, folks, you know, we we have to start inside, lowing and unlocking the data on bring it into a place where we can access it. Uh, you know, across all these parameters and boundaries that have historically existed, it's very much a step level function. Customers have always looked at things won't workload at that time. That mentality really has to go. You really have to have a data club mentality as well as a workload orientation towards towards managing data. >>Anita is great here in your role at Disney and you're in your keynote and the work you're doing the governance work and you're you're serving a great number of stakeholders, enabling things like data sharing. You got really laser focused on trust, compliance, privacy. This idea of a data clean room is really interesting. You know, maybe you can expand on some of these initiatives here and share what you're seeing as some of the biggest challenges to success. And, of course, the opportunities that you're unlocking. >>Sure, I mean, in my role leading data to governance, it's really critical to make sure that all of our stakeholders not only know what data is available and accessible to them, they can also understand really easily and quickly whether or not the data that they're using is for the appropriate use case. And so that's a big part of how we scale data governance. And a lot of the work that we would normally have to do manually is actually done for us through the data Clean rooms. >>Thank you for that. I wonder if you could talk a little bit more about the role of data and how your data strategy has evolved and maybe discuss some of the things that Frank mentioned about data silos. And I mean, obviously you can relate to that having been in the data business for a while, but I wonder if you could elucidate on that. >>Sure, I mean data complexities air going to evolve over time in any traditional data architecture. Er, simply because you often have different teams at different periods in time trying thio, analyze and gather data across Ah, whole lot of different sources. And the complexity that just arises out of that is due to the different needs of specific stakeholders, their time constraints. And quite often, um, it's not always clear how much value they're gonna be able to extract from the data at the outset. So what we've tried to do to help break down the silos is allow individuals to see up front how much value they're going to get from the data by knowing that it's trustworthy right away. By knowing that it's something that they can use in their specific use case right away, and by ensuring that essentially, as they're continuing to kind of scale, the use cases that they're focused on their no longer required Thio make multiple copies of the data, do multiple steps to reprocess the data. And that makes all the difference in the world, >>for sure. I mean, copy creep, because it be the silent killer. Frank, I've followed you for a number of years. Your big thinker. You and I have had a lot of conversations about the near term midterm and long term. I wonder if you could talk about you know, when you're Kino. You talk about eliminating silos and connecting across data sources, which really powerful concept. But really only if people are willing and able to connect and collaborate. Where do you see that happening? Maybe What are some of the blockers there? >>Well, there's there's certainly, ah, natural friction there. I still remember when we first started to talk to to Salesforce, you know, they had discovered that we were top three destination off sales first data, and they were wondering why that was. And the reason is, of course, that people take salesforce data, push it to snowflake because they wanna overlay it with what data? Outside of Salesforce, you know, whether it's adobe or any other marketing data set and then they want to run very highly skilled processes, you know, on it. But the reflexes in the world of SAS is always like, No, we're an island were planning down to ourselves. Everybody needs to come with us as opposed to we We go, you know, to a different platform to run these type of processes. It's no different for the for the public club. Better day didn't mean they have, you know, massive moats around there. Uh, you know, their stories to, you know, really prevent data from from leaving their their orbit. Eso there is natural friction in, uh, in terms off for this to happen. But on the other hand, you know, there is an enormous need, you know, we can't deliver on on the power and potential of data unless we allow it to come together. Uh, snowflake is the platform that allows that to happen. Uh, you know, we were pleased with our relationship with Salesforce because they did appreciate you know why this was important and why this was necessary. And we think you know, other parts of the industry will gradually come around to it as well. So the the idea of a data cloud has really come, right? Uh, people are recognizing, you know, why does this matter now? It's not gonna happen overnight. There's a step global function of very big change in mentality and orientation. >>Yeah. It's almost as though the SAS ification of our industry sort of repeated some of the application silos and you build a hardened top around it. All the processes are hard around. OK, here we go. And you're really trying to break that, aren't you? Yeah, Exactly. Anita. Again, I wanna come back to this notion of governance. It's so it's so important. It's the first role in your title, and it really underscores the importance of this. Um, you know, Frank was just talking about some of the hurdles, and this is this is a big one. I mean, we saw this in the early days of big data. Where governance was this after thought it was like, bolted on kind of wild, Wild West. I'm interested in your governance journey. And maybe you could share a little bit about what role snowflake has played there in terms of supporting that agenda. Bond. Kind of What's next on that journey? >>Sure. Well, you know, I've I've led data teams in a numerous, uh, in numerous ways over my career. This is the first time that I've actually had the opportunity to focus on governance. And what it's done is allowed for my organization to scale much more rapidly. And that's so critically important for our overall strategy as a company. >>Well, I mean a big part of what you were talking about. At least my inference in your talk was really that the business folks didn't have to care about, you know, wonder about they cared about it. But they're not the wonder about and and about the privacy, the concerns, etcetera. You've taken care of all that. It's sort of transparent to them. Is that >>yeah, right. That's right. Absolutely So we focus on ensuring compliance across all of the different regions where we operate. We also partner very heavily with our legal and information security teams. They're critical to ensuring, you know, that were ableto do this. We don't we don't do it alone. But governance includes not just, you know, the compliance and the privacy. It's also about data access, and it's also about ensuring data quality. And so all of that comes together under the governance umbrella. I also lead teams that focus on things like instrumentation, which is how we collect data. We focus on the infrastructure and making sure that we've architected for scale and all of these air really important components of our strategy. >>I got. So I have a question. Maybe each of you can answer. I I sort of see this our industry moving from, you know, products toe, then two platforms and platforms, even involving into ecosystems. And then there's this ecosystem of data. You guys both talked a lot about data sharing, But maybe Frank, you could start in Anita. You can add on to Frank's answer. You're obviously both both passionate about the use of data and trying to do so in a responsible way. That's critical, but it's also gonna have business impact. Frank, where's this passion come from? On your side. And how are you putting in tow action in your own organization? >>Well, you know, I'm really gonna date myself here, but, you know, uh, many, many years ago, uh, I saw the first glimpse off, uh, multidimensional databases that were used for reporting really on IBM mainframes on git was extraordinarily difficult. We didn't even have the words back then in terms of data, warehouses and all these terms didn't exist. People just knew that they wanted to have, um, or flexible way of reporting and being able Thio pivot data dimensionally and all these kinds of things. And I just whatever this predates, you know, Windows 3.1, which really set off the whole sort of graphical in a way of dealing with systems which there's not a whole generations of people that don't know any different, Right? So I I've lived the pain off. This problem on sort of had a front row seat to watching this this transpire over a very long period of time. And that's that's one of the reasons you know why I'm here. Because I finally seen a glimpse off. You know, I also as an industry fully fully just unleashing and unlocking the potential were not in a place where the technology is ahead of people's ability to harness it right, which we've never been there before, right? It was always like we wanted to do things that technology wouldn't let us. It's different now. I mean, people are just heads are spinning with what's now possible, which is why you see markets evolved very rapidly right now. We were talking earlier about how you can't take, you know, past definitions and concepts and apply them to what's going on the world. The world's changing right in front of your eyes right now. >>Sonita. Maybe you could add on to what Frank just said and share some of the business impacts and and outcomes that are notable since you're really applied your your love of data and maybe maybe touch on culture, data, culture, any words of wisdom for folks in the audience who might be thinking about embarking on a data cloud journey similar to what you've been on? >>Yeah, sure, I think for me. I fell in love with technology first, and then I fell in love with data, and I fell in love with data because of the impact the data can have on both the business and the technology strategy. And so it's sort of that nexus, you know, between all three and in terms of my career journey and some of the impacts that I've seen. I mean, I think with the advent of the cloud you know before. Well, how do I say that before the cloud actually became, you know, so prevalent and such a common part of the strategy that's required It was so difficult, you know, so painful. It took so many hours to actually be able to calculate, you know, the volumes of data that we had. Now we have that accessibility, and then on top of it with the snowflake data cloud, it's much more performance oriented from a cost perspective because you don't have multiple copies of the data, or at least you don't have toe have multiple copies of the data. And I think moving beyond some of the traditional mechanisms for for measuring business impact has has only been possible with the volumes of data that we have available to us today. And it's just it's phenomenal to see the speed at which we can operate and really, truly understand our customers, interests and their preferences, and then tailor the experiences that they really want and deserve for them. Um, it's it's been a great feeling. Thio, get to this point in time. >>That's fantastic. So, Frank, I gotta ask you if you're still in your spare time. You decided to write a book? I'm loving it. Um, I don't have a signed copy, so I'm gonna have to send it back and have you sign it. But your love, the inside baseball, it's just awesome. Eso really appreciate that. So but why did you decide to write a book? >>Well, there were a couple of reasons. Obviously, uh, we thought it was an interesting tale to tell for anybody who's interested in, you know what's going on. How did this come about, You know, where the characters behind the scenes and all this kind of stuff. But, you know, from a business standpoint, because this is such a step function, it's so non incremental. We felt like, you know, we really needed quite a bit of real estate to really lay out what the full narrative in context is on. Do you know, we thought books titled The Rise of the Data Cloud. That's exactly what it iss. And we're trying to make the case for that mindset, that mentality, that strategy. Uh, because all of us, you know, I think it's an industry were risk off, you know, persisting, perpetuating. Uh, you know, where we've been since the beginning off computing. So we're really trying to make a pretty forceful case for Look, there's an enormous opportunity out there. The different choices you have to make along the way. >>Guys, we got to leave it there. Frank. I know you and I are gonna talk again. Anita. I hope we have a chance to meet face to face and and talking the Cube live someday. You're phenomenal guests. And what a great story. Thank you both for coming on. Thank you. All right, you're welcome. And keep it right there, buddy. We'll be back for the next guest right after this short break and we're clear. All right. Not bad.

>> Hello everybody and welcome back to the cubes coverage of the Snowflake Data Cloud Summit 2020. We're tracking the rise of the Data Cloud, and fresh off the keynotes here, Frank Slootman, the chairman and CEO of Snowflake and Anita Lynch, the vice president of Data Governance at Disney Streaming Services. Folks, welcome. >> Thank you Thanks for having us, Dave, >> I need a Disney plus awesome. You know, we signed up early, watched all the Marvel movies, Hamilton, the new Pixar Movie saw, I haven't gotten into the Mandalorian yet, your favorite, but, (woman laughing) really appreciate you guys coming on. Let me start with Frank. I'm glad you're putting forth this vision around the data cloud, because I never liked the term Enterprise Data Warehouse, what you're doing is so different from the sort of that legacy world that I've known all these years, but start with why the Data Cloud, what problems are you trying to solve? And maybe some of the harder challenges you're seeing. >> Yeah I know, you know we've come a long way in terms of workload execution, right? In terms of scale and performance, you know, concurrent execution, we really taken the lid off sort of the physical constraints that have existed on these types of operations. But there's one problem, that we're not yet solving. And that is the siloing and bunkering of data. And especially in a data is locked in application it is locked data centers, is locked in cloud regions, incredibly hard for data science teams to really, you know, unlock the true value of data. When you can address patterns that exist across a data set. So we're perpetuate, a status we've had forever since the beginning of computing. If we don't start to crack that problem now we have that opportunity. But the notion of a Data Cloud is like basically saying, look folks, you know, we have to start unsiloing and unlocking the data, and bring it into a place, you know, where we can access it, you know, across all these parameters and boundaries that have historically existed. It's very much a step level function. Now the customers have always looked at things one workload at a time, that mentality really has to go. You really have to have a Data Cloud mentality, as well as a workload orientation towards managing data. >> Anita was great hearing your role at Disney, and your keynote, and the work you're doing, the governance work, and you're serving a great number of stakeholders, enabling things like data sharing, you got really laser focused on trust, compliance, privacy. Is this idea of a data clean room is really interesting. You maybe you can expand on some of these initiatives here and share what you're seeing as some of the biggest challenges to success. And of course, the opportunities that you're unlocking. >> Sure. I mean, in my role, leading Data Governance, it's really critical to make sure that all of our stakeholders, not only know what data is available and accessible to them, they can also understand really easily and quickly, whether or not the data that they're using is for the appropriate use case. And so, that's a big part of how we scale data governance, and a lot of the work that we would normally have to do manually, is actually done for us through the data clean rooms. >> Thank you for that. I wonder if you could talk a little bit more about the role of data and how your data strategy has evolved and maybe discuss some of the things that Frank mentioned about data silos, and obviously you can relate to that, having been in the data business for awhile, but wonder if you can elucidate on that. >> Sure. I mean, data complexities are going to evolve over time in any traditional data architecture, simply because you often have different teams at different periods in time, trying to analyze and gather data across a whole lot of different sources. And the complexity that just arises out of that, is, due to the different needs of specific stakeholders. There are time constraints, and quite often it's not always clear, how much value they're going to be able to extract from the data at the outset. So what we've tried to do to help break down those silos, is, allow individuals to see upfront how much value they're going to get from the data, by knowing that it's trustworthy right away . By knowing that it's something that they can use in their specific use case right away. And by ensuring that essentially, as they're continuing to kind of scale the use cases that they're focused on, they're no longer required to make multiple copies of the data, do multiple steps to reprocess the data. And that makes all the difference in the world. >> Yeah, for sure. I mean copy creek, cause it'd be the silent killer. Frank I followed you for a number of years. You're a big thinker. You and I have had a lot of conversations about the near term, mid term and long term. I wonder if you could talk about, you know, when your keynote, you talked about eliminating silos, and connecting across data sources, which really powerful concept, but it really only, if people are willing and able to connect and collaborate, where do you see that happening? Maybe what are some of the blockers there? >> Well, there's certainly a natural friction there. I still remember when we first started to talk to Salesforce, you know, they had, discovered that we were a top three destination of Salesforce data and they were wondering, you know, why that was? And the reason is of course that people take Salesforce data, push it to Snowflake, because they want to overlay it with data outside of Salesforce. You know what it is Adobe or any 6other marketing dataset. And then they want to run very highly skilled processes, you know, on it. But the reflexes in the world of SAS, is always like, no, we're an Island, we're a planet onto ourselves. Everybody needs to come with us as opposed to, we go to a different platform to run these types of processes. It's no different for thee public cloud vendor. They did only, they have, you know, massive moats around, you know, their storage to, you know, to really prevent data from leaving their orbit. So there is natural friction in terms of for this to happen. But on the other hand, you know, there is an enormous need, you know, we can't deliver on the power and potential of data, unless we allow it to come together. Snowflake is the platform that allows that to happen. You know, we were pleased with our relationship with Salesforce because they did appreciate, you know, why this was important and why this was necessary. And we think, you know, other parts of the industry will gradually come around to it as well. So the idea of a Data Cloud has really come. Right, people are recognizing, you know, why does this matters now. It's not going to happen overnight. It is a step what will function a very big change in mentality and orientation. You know? >> Yeah. It's almost as though the sussification of our industry sort of repeated some of the application silos, and build a heart on to and all the processes of(mummers) Okay, here we go. And you're really trying to break that aren't you? >> Yep, exactly. >> Anita, again, I want to come back to this notion of governance. It's so important. It's the first rule in your title, and it really underscores the importance of this. You know, Frank was just talking about some of the hurdles and this is a big one. I mean we saw this in the early days of big data where governance was this afterthought. It was like bolted on kind of wild west. I'm interested in your governance journey. And maybe you can share a little bit about what role Snowflake has played there in terms of supporting that agenda, and kind of what's next on that journey. >> Sure. Well, you know, I've led data teams, in numerous ways over my career, this is the first time, that I've actually had the opportunity to focus on governance. And what it's done, is allowed for my organization to scale much more rapidly. And that's so critically important for our overall strategy as a company. >> Well, I mean, a big part of what you were talking about, at least my inference in your talk, was really that the business folks didn't have to care about, your wonder about they cared about it, but they don't have to wonder about, and about the privacy concerns, et cetera, you've taken care of all that. It's sort of transparent to them. >> Yeah, that's right. Absolutely. So we focus on ensuring compliance across all of the different regions where we operate. We also partner very heavily with our legal and information security teams. They're critical, to ensuring you know, that we're able to do this. We don't do it alone. But governance includes not just, you know, the compliance and the privacy. It's also about data access. And it's also about ensuring data quality. And so all of that comes together under the governance umbrella. I also lead teams that focus on things like instrumentation, which is how we collect data, we focus on the infrastructure, and making sure that we've architected for scale , and all of these are really important components of our strategy. >> So I have a question maybe each of you can answer it. I sort of see this, our industry moving from products to then, to the platforms and platforms even evolving into ecosystems. And then there's this ecosystem of data. You guys both talked a lot about data sharing, but, but maybe Frank, you can start and Anita you can add onto Frank's answer. You obviously both passionate about the use of data and trying to do so in a responsible way, that's critical, but it's also going to have business impact. Frank, where's this passion come from on your side? And how are you putting into action in your own organization? >> Well, you know, I'm really going to date myself here, but you know many years ago, you know, I saw the first glimpse of multidimensional databases that were used for reporting really on IBM mainframes. And it was extraordinarily difficult. We didn't even have the words back then in terms of data, warehouses and business, all these terms didn't exist. People just knew that they want to have a more flexible way of reporting and being able to pivot data, dimensionally, all these kinds of things. And I just by whatever this predates, you know, windows 3.1, which really, you know, set off the whole sort of graphical, you know, way of dealing with systems, which there's not whole generations of people that don't know any different. Right? So I've lived the pain of this problem, and sort of had a front row seat, to watching this transpire over a very long period of time. And that's one of the reasons, you know, why I'm here because I finally seen, you know, a glimpse of, you know, I also, as an industry fully, just unleashing and unlocking the potential. We're not at a place where the technology is ahead of people's ability to harness it. Right. Which we'd never been there before. Right. It was always like we wanted to do things and technology wouldn't let us, it's different now. I mean, people are just, heads are spinning with what's now possible, which is why you see Marcus evolve, you know, very rapidly right now, we were talking earlier about how you can't take, you know, past definitions and concepts and apply them to what's going on in the world. The world's changing right in front of your eyes right now, >> So Anita maybe you could add on to what Frank just said and share some of the business impacts, and outcomes that are notable since you've really applied your love of data and maybe touch culture, data culture. Any words of wisdom for folks in the audience who might be thinking about embarking on a Data Cloud journey, similar to what you've been on. >> Yeah Sure. I think for me, I fell in love with technology first, and then I fell in love with data and I fell in love with data because of the impact that data can have, on both the business, and the technology strategy. And so it's sort of that nexus between all three. And in terms of my career journey and some of the impacts that I've seen. I think with the advent of the Cloud, you know, before, well, how do I say this? Before the cloud actually became so prevalent and such a common part of the strategy that's required, it was so difficult, you know, so painful. It took so many hours to actually, be able to calculate, you know, the volumes of data that we had. Now we have that accessibility. And then on top of it, with the Snowflake Data Cloud, it's much more performance oriented from a cost perspective because you don't have multiple copies of the data, or at least you don't have to have multiple copies of the data. And I think, moving beyond some of the traditional mechanisms for measuring business impact, has only been possible with the volumes of data that we have available to us today. And it's just, it's phenomenal to see the speed at which we can operate and really, truly understand our customer's interests and their preferences, and then tailor the experiences that they really want and deserve for them. It's been a great feeling to get to this point in time. >> That's fantastic. So, Frank, I got to ask you to do so in your spare time you decided to write a book am loving it. I have a signed copy, so I'm going to have to send it back and have you sign it. But, and I love the inside baseball. It's just awesome. So really appreciate that. So, but why did you decide to write a book? >> Well, there were a couple of reasons. Obviously we thought it was an interesting tale to tell for anybody, you know, who is interested in, you know, what's going on? How did this come about? You know, or the characters behind the scenes and all this kind of stuff. But, you know, from a business standpoint, you know, because this is such a step function, it's so non incremental, we felt like we really needed quite a bit of real estate to really lay out, what the full narrative and context is. And, you know, we thought, you know, books titled the rise of the Data Cloud. That's exactly what it is. And we're trying to make the case for that mindset, that mentality, that strategy, because all of us, you know, I think as an industry we're at risk of, you know, persisting, perpetuating, you know, where we've been since the beginning of computing. So we're really trying to make a pretty forceful case for look, you know, there's an enormous opportunity out there, but there's some choices you have to make along the way. >> Guys, we got to leave it there. Frank. I know you and I are going to talk again, Anita, I hope we have a chance to meet face to face and in the cube live someday, your phenomenal guest and what a great story. Thank you both for coming on. Thanks Dave, >> Thank you >> You're welcome to keep it right there, buddy. We'll be back with the next guest right after this short break. (upbeat music)

>>Hello, buddy. And welcome back to the cubes. Coverage of Snowflake Data Cloud Summer 2020. We're tracking the rise of the data cloud and fresh off the keynotes. Hear Frank's Luqman, the chairman and CEO of Snowflake, and Anita Lynch, the vice president of data governance at Disney Streaming Services. Folks. Welcome E Need a Disney plus. Awesome. You know, we signed up early. Watched all the Marvel movies. Hamilton, the new Pixar movie Soul. I haven't gotten to the man DeLorean yet. Your favorite, but I really appreciate you guys coming on. Let me start with Frank. I'm glad you're putting forth this vision around the data cloud because I never liked the term Enterprise Data Warehouse. What you're doing is is so different from the sort of that legacy world that I've known all these years. But start with why the data cloud? What problems are you trying to solve? And maybe some of the harder challenges you're seeing? >>Yeah, I know. You know, we have We've come a long way in terms of workload execution, right? In terms of scale and performance and, you know, concurrent execution. We really taking the lid off sort of the physical constraints that that have existed on these types of operations. But there's one problem, uh, that were not yet, uh solving. And that is the silo ing and bunkering of data. Essentially, you know, data is locked in applications. It's locked in data centers that's locked in cloud cloud regions incredibly hard for for data science teams to really, you know, unlocked the true value of data. When you when you can address patterns that that exists across data set. So we're perpetuate, Ah, status we've had for for ever since the beginning off computing. If we don't start Thio, crack that problem now we have that opportunity. But the notion of a data cloud is like basically saying, Look, folks, you know, we we have to start inside, lowing and unlocking the data on bring it into a place where we can access it. Uh, you know, across all these parameters and boundaries that have historically existed, it's It's very much a step level function. Customers have always looked at things won't workload at that time. That mentality really has to go. You really have to have a data cloud mentality as well as a workload orientation towards towards managing data. Yeah, >>Anita is great here in your role at Disney, and you're in your keynote and the work. You're doing the governance work, and you're you're serving a great number of stakeholders, enabling things like data sharing. You got really laser focused on trust, compliance, privacy. This idea of a data clean room is really interesting. You know, maybe you can expand on some of these initiatives here and share what you you're seeing as some of the biggest challenges to success. And, of course, the opportunities that you're unlocking. >>Sure. I mean, in my role leading data to governance, it's really critical to make sure that all of our stakeholders not only know what data is available and accessible to them, they can also understand really easily and quickly whether or not the data that they're using is for the appropriate use case. And so that's a big part of how we scale data governance. And a lot of the work that we would normally have to do manually is actually done for us through the data. Clean rooms. >>Thank you for that. I wonder if you could talk a little bit more about the role of data and how your data strategy has evolved and maybe discuss some of the things that Frank mentioned about data silos. And I mean, obviously you can relate to that having been in the data business for a while, but I wonder if you could elucidate on that. >>Sure, I mean data complexities air going to evolve over time in any traditional data architecture. Er, simply because you often have different teams at different periods in time trying thio, analyze and gather data across Ah, whole lot of different sources. And the complexity that just arises out of that is due to the different needs of specific stakeholders, their time constraints. And quite often, um, it's not always clear how much value they're going to be able to extract from the data at the outset. So what we've tried to do to help break down the silos is allow individuals to see up front how much value they're going to get from the data by knowing that it's trustworthy right away. By knowing that it's something that they can use in their specific use case right away, and by ensuring that essentially, as they're continuing to kind of scale the use cases that they're focused on. They're no longer required. Thio make multiple copies of the data, do multiple steps to reprocess the data. And that makes all the difference in the world, >>for sure. I mean, copy creep, because it be the silent killer. Frank, I followed you for a number of years. You know, your big thinker. You and I have had a lot of conversations about the near term midterm and long term. I wonder if you could talk about you know, when you're Kino. You talk about eliminating silos and connecting across data sources, which really powerful concept. But really only if people are willing and able to connect and collaborate. Where do you see that happening? Maybe What are some of the blockers there? >>Well, there's there's certainly, ah natural friction there. I still remember when we first started to talk to to Salesforce, you know, they had discovered that we were top three destination off sales first data, and they were wondering, you know why that was. And and the reason is, of course, that people take salesforce data, push it to snowflake because they wanna overlay it with what data outside of Salesforce. You know, whether it's adobe or any other marketing data set. And then they want to run very highly skilled processes, you know, on it. But the reflexes in the world of SAS is always like, no, we're an island were planning down to ourselves. Everybody needs to come with us as opposed to we We go, you know, to a different platform to run these type of processes. It's no different for the for the public club. Venter Day didn't mean they have, you know, massive moats around there. Uh, you know, their stories to, you know, really prevent data from from leaving their their orbit. Eso there is natural friction in in terms off for this to happen. But on the other hand, you know, there is an enormous need, you know, we can't deliver on on the power and potential of data unless we allow it to come together. Uh, snowflake is the platform that allows that to happen. You know, we were pleased with our relationship with Salesforce because they did appreciate you know why this was important and why this was necessary. And we think you know, other parts of the industry will gradually come around to it as well. So the the idea of a data cloud has really come, right? People are recognizing, you know, why does this matters now? It's not gonna happen overnight, And there's a step global function of very big change in mentality and orientation. You know, >>it's almost as though the SAS ification of our industries sort of repeated some of the application silos, and you build a hardened top around it. All the processes are hardened around it, and Okay, here we go. And you're really trying to break that, aren't you? Yeah, Exactly. Anita. Again, I wanna come back to this notion of governance. It's so it's so important. It's the first role in your title, and it really underscores the importance of this. Um, you know, Frank was just talking about some of the hurdles, and and this is this is a big one. I mean, we saw this in the early days of big data. Where governance was this after thought it was like, bolted on kind of wild, Wild West. I'm interested in your governance journey, and maybe you can share a little bit about what role Snowflake has played there in terms of supporting that agenda. Bond. Kind of What's next on that journey? >>Sure. Well, you know, I've I've led data teams in a numerous, uh, in numerous ways over my career. This is the first time that I've actually had the opportunity to focus on governance. And what it's done is allowed for my organization to scale much more rapidly. And that's so critically important for our overall strategy as a company. >>Well, I mean a big part of what you were talking about, at least my inference in your your talk was really that the business folks didn't have to care about, you know, wonder about they cared about it. But they're not the wonder about and and about the privacy, the concerns, etcetera. You've taken care of all that. It's sort of transparent to them. Is that >>yeah, right. That's right. Absolutely. So we focus on ensuring compliance across all the different regions where we operate. We also partner very heavily with our legal and information security teams. They're critical to ensuring, you know, that we're able Thio do this. We don't We don't do it alone. But governance includes not just, you know, the compliance and the privacy. It's also about data access, and it's also about ensuring data quality. And so all of that comes together under the governance umbrella. I also lead teams that focus on things like instrumentation, which is how we collect data. We focus on the infrastructure and making sure that we've architected for scale and all of these air really important components of our strategy. >>I got. So I have a question. Maybe each of you can answer. I I sort of see this our industry moving from, you know, products. So then the platforms and platforms even involving into ecosystems. And then there's this ecosystem of of data. You guys both talked a lot about data sharing. But maybe Frank, you could start in Anita. You can add on to Frank's answer. You're obviously both both passionate about the use of of data and trying to do so in a responsible way. That's critical, but it's also gonna have business impact. Frank, where's this passion come from? On your side. And how are you putting in tow action in your own organization? >>Well, you know, I'm really gonna date myself here, but, you know, many, many years ago, you know, I saw the first glimpse off, uh, multidimensional databases that were used for reporting. Really, On IBM mainframes on debt was extraordinarily difficult. We didn't even have the words back then. In terms of data, warehouses and business. All these terms didn't exist. People just knew that they wanted to have, um, or flexible way of reporting and being able Thio pivot data dimensionally and all these kinds of things. And I just whatever this predates, you know, Windows 3.1, which, really, you know, set off the whole sort of graphical in a way of dealing with systems which there's not a whole generations of people that don't know any different. Right? So I I've lived the pain off this problem on sort of been had a front row seat to watching this This transpire over a very long period of time. And that's that's one of the reasons um, you know why I'm here? Because I finally seen, you know, a glimpse off, you know, also as an industry fully fully just unleashing and unlocking the potential were not in a place where the technology is ahead of people's ability to harness it right, which we've We've never been there before, right? It was always like we wanted to do things that technology wouldn't let us. It's different now. I mean, people are just heads are spinning with what's now possible, which is why you see markets evolved very rapidly right now. Way we were talking earlier about how you can't take, you know, past definitions and concepts and apply them to what's going on the world. The world's changing right in front of your eyes right now. >>Sonita. Maybe you could add on to what Frank just said and share some of the business impacts and and outcomes that air notable since you're really applied your your love of data and maybe maybe touch on culture, your data culture. You know any words of wisdom for folks in the audience who might be thinking about embarking on a data cloud journey similar to what you've been on? >>Yeah, sure, I think for me. I fell in love with technology first, and then I fell in love with data, and I fell in love with data because of the impact the data can have on both the business and the technology strategy. And so it's sort of that nexus, you know, between all three and in terms of my career journey and and some of the impacts that I've seen I mean, I think with the advent of the cloud, you know before, Well, how do I say that before the cloud actually became, you know, so prevalent in such a common part of the strategy that's required? It was so difficult, you know, so painful. It took so many hours to actually be able to calculate, you know, the volumes of data that we had. Now we have that accessibility, and then on top of it with the snowflake data cloud, it's much more performance oriented from a cost perspective because you don't have multiple copies of the data, or at least you don't have toe have multiple copies of the data. And I think moving beyond some of the traditional mechanisms for for measuring business impact has has only been possible with the volumes of data that we have available to us today. And it's just it's phenomenal to see the speed at which we can operate and really, truly understand our customers, interests and their preferences, and then tailor the experiences that they really want and deserve for them. Um, it's It's been a great feeling. Thio, get to this point in time. >>That's fantastic. So, Frank, I gotta ask you if you're still in your spare time, you decided to write a book? I'm loving it. Um, I don't have a signed copy, so I'm gonna have to send it back and have you sign it. But you're I love the inside baseball. It's just awesome. Eso really appreciate that. So But why did you decide to write a book? >>Well, there were a couple of reasons. Obviously, we thought it was an interesting tale to tell for anybody you know who is interested in, You know what's going on. How did this come about, You know, where the characters behind the scenes and all this kind of stuff. But, you know, from a business standpoint, because this is such a step function, it's so non incremental. We felt like, you know, we really needed quite a bit of real estate to really lay out what the full narrative and context is on. Do you know we thought books titled The Rise of the Data Cloud. That's exactly what it ISS and We're trying to make the case for that mindset, that mentality, that strategy. Because all of us, you know, I think is an industry or were risk off persisting, perpetuating, You know, where we've been since the beginning off computing. So we're really trying to make a pretty forceful case for Look, you know, there is an enormous opportunity out there, The different choices you have to make along the way. >>Guys, we got to leave it there. Frank. I know you and I are gonna talk again. Anita. I hope we have a chance to meet face to face and and talking the Cube live someday. You're phenomenal, guest. And what a great story. Thank you both for coming on. And thank you for watching. Keep it right there. You're watching the Snowflake Data Cloud Summit on the Cube.

>>Hi, I'm Frank's Luqman CEO of Snowflake. And welcome to the Snowflake Data Cloud Summit. I'd like to take the next few minutes to introduce you to >>the data cloud on why it matters to the modern enterprise. As an industry, we have struggled to mobilize our data, meaning that has been hard to put data into service of our enterprises. We're not living in a data economy and for most data central how we run our lives, our businesses and our institutions, every single interaction we have now, whether it's in social media, e commerce or any other service, engagement generates critical data. You multiply this out with the number of actors and transactions. The volume is overwhelming, growing in leaps and bounds every day. There was a time when data operations focused mostly on running reports and populating dashboards to inform people in the enterprise of what had happened on what was going on. And we still do a ton of that. But the emphasis is shifting to data driving operations from just data informing people. There is such a thing as the time value off data meaning that the faster data becomes available, the more impactful and valuable it ISS. As data ages, it loses much of its actionable value. Digital transformation is an overused term in our industry, but the snowflake it means the end to end automation of business processes, from selling to transacting to supporting to servicing customers. Digital processes are entirely disinter mediated in terms of people. Involvement in are driven into end by data. Of course, many businesses have both physical and digital processes, and they are >>intertwined. Think of retail, logistics, delivery services and so on. So a data centric operating discipline is no longer optional data operations Air now the beating heart >>of the modern enterprise that requires a massively scalable data platform talented data engineering and data science teams to fully exploit the technology that now is becoming available. Enter snowflake. Chances are that, you know, snowflake as a >>world class execution platform for a diverse set of workloads. Among them data warehousing, data engineering, data, lakes, data, science, data applications and data sharing. Snowflake was architected from scratch for cloud scale computing. No legacy technology was carried forward in the process. Snowflake reimagined many aspects of data management data operations. The result was a cloud data platform with massive scale, blistering performance, superior economics and world class data governance. Snowflake innovated on a number of vectors that wants to deliver this breakthrough. First scale and performance. Snowflake is completely designed for cloud scale computing, both in terms of data volume, computational performance and concurrent workload. Execution snowflake features numerous distinct innovations in this category, but none stands up more than the multi cluster shared stories. Architectural Removing the control plane from the individual cluster led to a dramatically different approach that has yielded tremendous benefits. But our customers love about Snowflake is to spin up new workloads without limitation and provisioned these workloads with his little or as much compute as they see fit. No longer do they fear hidden capacity limits or encroaching on other workloads. Customers can have also scale storage and compute independent of each other, something that was not possible before second utility and elasticity. Not only can snowflake customer spin up much capacity for as long as they deem necessary. Three. Utility model in church, they only get charged for what they consumed by the machine. Second, highly granular measurement of utilization. Ah, lot of the economic impact of snowflake comes from the fact that customers no longer manage capacity. What they do now is focused on consumption. In snowflake is managing the capacity. Performance and economics now go hand in hand because faster is now also cheaper. Snowflake contracts with the public cloud vendors for capacity at considerable scale, which then translates to a good economic value at the retail level is, well, third ease of use and simplicity. Snowflake is a platform that scales from the smallest workloads to the largest data estates in the world. It is unusual in this offer industry to have a platform that controversy the entire spectrum of scale, a database technology snowflake is dramatically simple fire. To compare to previous generations, our founders were bent on making snowflake, a self managing platform that didn't require expert knowledge to run. The role of the Deba has evolved into snowflake world, more focused on data model insights and business value, not tuning and keeping the infrastructure up and running. This has expanded the marketplace to nearly any scale. No job too small or too large. Fourth, multi cloud and Cross Cloud or snowflake was first available on AWS. It now also runs very successfully on mark yourself. Azure and Google Cloud Snowflake is a cloud agnostic platform, meaning that it doesn't know what it's running on. Snowflake completely abstracts the underlying cloud platform. The user doesn't need to see or touch it directly and also does not receive a separate bill from the cloud vendor for capacity consumed by snowflake. Being multi cloud capable customers have a choice and also the flexibility to change over time snowflakes. Relationships with Amazon and Microsoft also allow customers to transact through their marketplaces and burned down their cloud commit with their snowflakes. Spend Snowflake is also capable of replicating across cloud regions and cloud platforms. It's not unusual to see >>the same snowflake data on more than one public cloud at the time. Also, for disaster recovery purposes, it is desirable to have access to snowflake on a completely different public cloud >>platform. Fifth, data Security and privacy, security and privacy are commonly grouped under the moniker of data governance. As a highly managed cloud data platform, snowflake designed and deploys a comprehensive and coherent security model. While privacy requirements are newer and still emerging in many areas, snowflake as a platform is evolving to help customers steer clear from costly violations. Our data sharing model has already enabled many customers to exchange data without surrendering custody of data. Key privacy concerns There's no doubt that the strong governance and compliance framework is critical to extracting you analytical value of data directly following the session. Police Stay tuned to hear from Anita Lynch at Disney Streaming services about how >>to date a cloud enables data governance at Disney. The world beat a >>path to our door snowflake unleashed to move from UN promised data centers to the public cloud platforms, notably AWS, Azure and Google Cloud. Snowflake now has thousands of enterprise customers averaging over 500 million queries >>today across all customer accounts, and it's one of the fastest growing enterprise software companies in a generation. Our recent listing on the New York Stock Exchange was built is the largest software AIPO in history. But the data cloth conversation is bigger. There is another frontier workload. Execution is a huge part of it, but it's not the entire story. There is another elephant in the room, and that is that The world's data is incredibly fragmented in siloed, across clouds of old sorts and data centers all over the place. Basically, data lives in a million places, and it's incredibly hard to analyze data across the silos. Most intelligence analytics and learning models deploy on single data sets because it has been next to impossible to analyze data across sources. Until now, Snowflake Data Cloud is a data platform shared by all snowflake users. If you are on snowflake, you are already plugged into it. It's like being part of a Global Data Federation data orbit, if you will, where all other data can now be part of your scope. Historically, technology limitations led us to build systems and services that siloed the data behind systems, software and network perimeters. To analyze data across silos, we resorted to building special purpose data warehouses force fed by multiple data sources empowered by expensive proprietary hardware. The scale limitations lead to even more silos. The onslaught of the public cloud opened the gateway to unleashing the world's data for access for sharing a monetization. But it didn't happen. Pretty soon they were new silos, different public clouds, regions within the and a huge collection of SAS applications hoarding their data all in their own formats on the East NC ations whole industries exist just to move data from A to B customer behavior precipitated the silo ing of data with what we call a war clothes at a time mentality. Customers focused on the applications in isolation of one another and then deploy data platforms for their workload characteristics and not much else, thereby throwing up new rules between data. Pretty soon, we don't just have our old Silas, but new wants to content with as well. Meanwhile, the promise of data science remains elusive. With all this silo ing and bunkering of data workload performance is necessary but not sufficient to enable the promise of data science. We must think about unfettered data access with ease, zero agency and zero friction. There's no doubt that the needs of data science and data engineering should be leading, not an afterthought. And those needs air centered on accessing and analyzing data across sources. It is now more the norm than the exception that data patterns transcend data sources. Data silos have no meaning to data science. They are just remnants of legacy computing. Architectures doesn't make sense to evaluate strictly on the basis of existing workloads. The world changes, and it changes quickly. So how does the data cloud enabled unfettered data access? It's not just a function of being in the public cloud. Public Cloud is an enabler, no doubt about it. But it introduces new silos recommendation by cloud, platform by cloud region by Data Lake and by data format, it once again triggered technical grandstands and a lot of programming to bring a single analytical perspective to a diversity of data. Data was not analytics ready, not optimized for performance or efficiency and clearly lacking on data governance. Snowflake, address these limitations, thereby combining great execution with great data >>access. But, snowflake, we can have the best of both. So how does it all work when you join Snowflake and have your snowflake account? You don't just >>avail yourself of unlimited stories. And compute resource is along with a world class execution platform. You also plug into the snowflake data cloud, meaning that old snowflake accounts across clouds, regions and geography are part of a single snowflake data universe. That is the data clouds. It is based on our global data sharing architectures. Any snowflake data can be exposed and access by any other snowflake user. It's seamless and frictionless data is generally not copied. Her moves but access in place, subject to the same snowflake governance model. Accessing the data cloth can be a tactical one on one sharing relationship. For example, imagine how retailer would share data with a consumer back. It's good company, but then it easily proliferate from 1 to 1. Too many too many. The data cloud has become a beehive of data supply and demand. It has attracted hundreds of professional data listings to the Snowflake Data Marketplace, which fuels the data cloud with a rich supply of options. For example, our partner Star Schema, listed a very detailed covert 19 incident and fatality data set on the Snowflake Data Marketplace. It became an instant hit with snowflake customers. Scar schema is not raw data. It is also platform optimize, meaning that it was analytics ready for all snowflake accounts. Snowflake users were accessing, joining and overlaying this new data within a short time of it becoming available. That is the power of platform in financial services. It's common to see snowflake users access data from snowflake marketplace listings like fax set and Standard and Poor's on, then messed it up against for example. Salesforce data There are now over 100 suppliers of data listings on the snowflake marketplace That is, in addition to thousands of enterprise and institutional snowflake users with their own data sets. Best part of the snowflake data cloud is this. You don't need to do or buy anything different. If your own snowflake you're already plugged into the data clouds. A whole world data access options awaits you on data silos. Become a thing of the past, enjoy today's presentations. By the end of it, you should have a better sense in a bigger context for your choices of data platforms. Thank you for joining us.

(lively music) >> Thank you, Frank, for kicking us off, setting the stage, and providing the vision for the Snowflake Data Cloud. Hi, everyone, I hope you're all doing well and staying safe. Thank you for joining me at the Snowflake Summit today to dive into the role of the Data Cloud in mobilizing data at Disney Streaming. Together, we're going to discuss data governance and how to leverage some of the unique benefits of Snowflake's data platform to unlock business value for better customer experiences. I am Anita Lynch, Vice President of Data Governance at Disney Streaming, home of Disney+. I fell in love with technology at an early age. My family is originally from Chicago and we came to the Bay Area when my dad's sales career led him to Silicon Valley. Because of the exciting advancements he saw in the devices he sold and the engineers he worked with, I am so fortunate that my father created the early opportunities for me to learn about technology, like starting to code when I was 10. Decades later, over the course of my career spanning tech startups, business school, strategy consulting, and leading data at global enterprises, I have learned it is not enough to create a technology solution. It takes a real understanding of what problems your customers are trying to solve, and what resources or capabilities they can mobilize to do it. Today, this is the focus of my career in data. At Disney Streaming, we pride ourselves on delighting our customers. We commit each day to bringing beloved characters, timeless stories, and epic sporting events to a global audience. I am one member of a global data team at Disney Streaming, continuing to work through these challenging times for our world. We are deeply appreciative to be able to continue doing our part to deliver the entertainment people love on Disney+, including my new, personal favorite series, "The Mandalorian." It is important to all of us that we maintain our viewers' highest level of trust. As our data volume grows continuously on a daily basis, we need to ensure data is compliant, secure, and well-governed. Therefore, how we execute is critical. Our work ensures our business is guiding decisions with high-quality data. Doing this empowers us to challenge convention and innovate, which brings us to the role of the organization I lead at Disney Streaming. I lead data governance, which includes instrumentation, compliance, integrations, and data architecture. Collectively, we are responsible for the value, protection, and mobilization of data for Disney+. With data volumes in the thousands of petabytes after just one year and global teams depending on us to be able to perform their analysis, data science modeling, and machine learning, it is critical to maintain compliance protocols and governance standards. However, our approach to locking down the data and limiting access without becoming a blocker to critical information needs is key. Poorly informed business decisions could ultimately lead to suboptimal customer experiences. Recognizing this, I've established eight operating principles to maintain a balance between technology, people, and process. Data lifecycle, stewardship, and data quality together define the mechanisms by which we maintain, measure, and improve the value of data as an asset. Regulatory compliance and data access establish key partnerships with our legal and information security to help us ensure data complies with internal and external legal guidelines in each region. Auditability, traceability, and risk management ensure we monitor, educate, influence, and enforce best practices. And lastly, data sharing, which serves to socialize valuable datasets and shared definitions in a secure, easy way that allows us to keep pace with the fast-moving and rapidly changing nature of our world today. Principles serve only as guardrails. In real practice, we measure the value data governance delivers based on these six, quantifiable goals for the teams we serve. Underpinning all of them is the Snowflake Data Cloud. It is our platform to store, secure, integrate, and mobilize data across the organization. It enables us to make compliant data accessible for teams to collaborate without copying, moving, or reprocessing. Going beyond the notion of a single source of truth, Snowflake's Data Cloud allows us to truly have a single copy of the data, plus the ability to scale to support a near-unlimited number of concurrent users without contention for resources, and the flexibility to prioritize or deprioritize compute workloads where concurrency matters less than our ability to manage cost. What does this mean to me? Put simply, it means the ability to support business intelligence, analytics, data science, and machine learning use cases on-demand, exceeding expectations for speed and performance where they matter without sacrificing anything on governance. And that is how we deliver value through data governance for Disney+. Data sharing is at the heart of how we make this work. We'll look at three important use cases, data clean rooms that enable restricted data sharing, data discovery that ensures data is easily found and understood, and partner data management for collaboration outside of our team. Data sharing creates the opportunity to access the power of the integrated dataset in an environment that ensures both quality and compliance. Let's start with data clean rooms and the example of restricted data sharing. Better understanding the interests and preferences of our audience through analysis is how we improve experiences for our customers, such as in-app personalization or making a recommendation on what to watch. The challenge is to mobilize the right data as it is needed while blocking distribution of any data that is not required, preventing the disclosure of sensitive information and prohibiting the merging of data that should not be combined. Simultaneously, while we seek to deliver compliance, we also want to avoid the typical process delays and enormous manual repetitive work that often comes with it. Data clean rooms enable the secure sharing of data, again, without creating copies, the combining of datasets without PII or sensitive information, and the restricting of queries by use of parameterized inputs and filtered query outputs, so only permissible data can be extracted. Outlining in advance how data will be used properly ensures consistency and execution of our compliance workflows and improves transparency on constraints, so teams don't waste their valuable time. This accelerates our ability to act on data insights. Decisions can be made for the benefit of our customers. For example, for me on Disney+, I would see right away the season two trailer for "The Mandalorian," including exciting scenes with Baby Yoda, more formerly known to some of you as the Child. Sometimes unintended data silos arise due to architectural complexities. In a traditional model for data infrastructure, complexity can evolve over time as various teams need to access, integrate, and transform data from different data sources in ways that uniquely serve their specific stakeholders. This proliferation in the analytical supply chain could result in multiple instances of copying, loading, and transforming the same data and introduce significant risks to data quality throughout the system, such as a lack of traceability. For example, changing one data pipeline may create unforeseen consequences in the calculations that occur in downstream tables and reports with no clear resolution. In the spirit of challenging convention to innovate, we knew we had to do better. With the Snowflake Data Cloud, our teams are able to discover the data sources they need through a centrally organized platform for data management and data sharing. Each user knows the data visible to them is available to them. They know they can trust it, and they know how it can properly be used to drive broader customer insights. And if a team wants to share their insights for further collaboration, they can easily publish those datasets to the Data Cloud, where they benefit from the protection of our managed platform, making sure all governance protocols are in place, including who can access for what purpose and at what level of granularity. This facilitates data sharing without the administration worry that comes with sharing files. And since there is one single copy, future updates happen at once for all consumers of the data, keeping it fresh for everyone without sacrificing business continuity. Finally, data sharing improves the performance of our partner relationships with the same degree of simplicity. In this model, our partner teams can also participate in the Data Cloud by invitation to access data specifically shared to them. Or conversely, a partner can request to share their data, and upon authorization for quality and compliance, we can safely publish that data, making it simultaneously available to all the right teams who need it. As a thought exercise, one way for us to envision making it easier to work with partners is in the way we collect and analyze data from media serving and content distribution networks. Today, customer stream Disney+ on more than 13 different types of devices. Their streaming is made possible through a collection of services that vary by geography and consumer choice. Better understanding the experience for an individual client may require integration of data collected across the unique combination of services available to that customer. To better serve our content and delight our customers, data-driven analysis to detect anomalies and service impacts might benefit from a data management platform for partner data that requires a high level of data governance similar to what we do today through our Snowflake Data Cloud. Now in closing, data is at the core of our mission at Disney Streaming to delight our customers. And when it comes to data governance, we strive to always hold ourselves to the highest standard. With the Data Cloud, we power our business with a single source of truth. As we grow, it enables data sharing with data governance at massive scale and performance. I will also leave you with this often quoted African proverb I like. "If you want to go fast, go alone. But if you want to go far, go together." We share an important cultural value. Commitment to innovation accelerated our ability to address unique use cases and the successful growth of Disney+. It was both the technology and the commitment to meet our data governance needs that has resulted in more than just another cloud data platform. We have a solution that works for us. Thank you for joining me on this journey, and thank you to Snowflake for the ongoing partnership. With the product keynote coming up next, I'm excited to see how future innovation will continue to enable us to challenge convention going forward.