>> We're here at the Data Cloud Summit 2020, tracking the rise of the data cloud. And we're talking about the ecosystem powering the next generation of innovation in cloud, you know, for decades, the technology industry has been powered by great products. Well, the cloud introduced a new type of platform that transcended point products and the next generation of cloud platforms is unlocking data-centric ecosystems where access to data is at the core of innovation, tapping the resources of many versus the capabilities of one. Casey McGee is here. He's the vice president of global ISV sales at Microsoft, and he's joined by Colleen Kapase, who is the VP of partnerships and global alliances at Snowflake. Folks, welcome to theCUBE. It's great to see you. >> Thanks Dave, good to see you. Thank you. >> Thanks for having us here. >> You're very welcome. So, Casey, let me start with you please. You know, Microsoft's got a long heritage, of course, working with partners, you're renowned in that regard, built a unbelievable ecosystem, the envy of many in the industry. So if you think about as enterprises, they're speeding up their cloud adoption, what are you seeing as the role and the importance of ecosystem, the ISV ecosystem specifically, in helping make customers' outcomes successful? >> Yeah, let me start by saying we have a 45 year history of partnership, so from our very beginning as a company, we invested to build these partnerships. And so let me start by saying from day one, we looked at a diverse ecosystem as one of the most important strategies for us, both to bring innovation to customers and also to drive growth. And so we're looking to build that environment even today. So 45 years later, focused on how do we zero in on the business outcomes that matter most to customers, usually identified by the industry that they're serving. So really building an ecosystem that helps us serve both the customers and the business outcomes they're looking to drive. And so we're building that ecosystem of ISVs on the Microsoft cloud and focused on bringing that innovation as a platform provider through those companies. >> So Casey, let's stay on that for a moment, if we can. I mean, you work with a lot of ISVs and you got a big portfolio of your own solutions. Now, sometimes they overlap with the ISV offerings of your partners. How do you balance the focus on first party solutions and third-party ISV partner solutions? >> Yeah, first and foremost, we're a platform company. So our whole intent is to bring value to that partner ecosystem. Well, sometimes that means we may have offers in market that may compliment one another. Our focus is really on serving the customer. So anytime we see that, we're looking at what is the most desired outcome for our customer, driving innovation into that specific business requirement. So for us, it's always focusing on the customer, and really zeroing in on making sure that we're solving their business problems. Sometimes we do that together with partners like Snowflake. Sometimes that means we do that on our own, but the key for us is really deeply understanding what's important to the customer and then bringing the best of the Microsoft and Snowflake scenarios to bear. >> You know, Casey, I appreciate that. A lot times people say "Dave, don't ask me that question. It's kind of uncomfortable." So Colleen, I want to bring you into the discussion. How does Snowflake view this dynamic, where you're simultaneously partnering and competing sometimes with some of the big cloud companies on the planet? >> Yeah, Dave, I think it's a great question, and really in this era of innovation, so many large companies like Microsoft are so diverse in their product set, it's almost impossible for them to not have some overlap with most of their ecosystem. But I think Casey said it really well, as long as we stay laser focused on the customer, and there are a lot of very happy Snowflake customers and happy Azure customers, we really win together. And I think we're finding ways in which we're working better and better together, from a technology standpoint, and from a field standpoint. And customers want to see us come together and bring best of breed solutions. So I think we're doing a lot better, and I'm looking forward to our future, too. >> So Casey, Snowflake, you know, they're really growing, they've got a pretty large footprint on Azure. You're talking hundreds of customers here that are active on that platform. I wonder if you could talk about the product integration points that you kind of completed initially, and then kind of what's on the horizon that you see as particularly important for your joint customers? >> You have to say, so one of the things that I love about this partnership is that, well, we start with what the customer wants. We bring that back into the engineering-level relationship that we have between the two companies. And so that's produced some pretty incredibly rich functionality together. So let me start by saying, you know, we've got eight Azure regions today with nine coming on soon. And so we have a geographic diversity that is important for many of our customers. We've also got a series of engineering-level integrations that we've already built. So that's functionality for Azure Private Link, as well as integration between Power BI, Azure Data Factory, and Azure Data Lake, all of this back again to serve the business outcomes that are required for our customers. So it's this level of integration that I think really speaks to the power of the partnership. So we are intently focused on the democratization of data. So we know that Snowflake is the premier partner to help us do that. So getting that right is key to enabling high concurrency use cases with large numbers of businesses, users coming together, and getting the performance they expect. >> Yeah, I appreciate that Casey, because a lot of times I'll, you know, I'll look at the press release. Sometimes we laugh, we call them Barney deals. You know, "I love you. You love me." But I listen for the word engineering and integration. Those are sort of important triggers. Colleen, or Casey too, but I want to start with Colleen. I mean, anything you would add to that, are there things that you guys have worked on together that you're particularly proud of, or maybe that have pushed the envelope and enabled new capabilities for customers where they've given you great feedback? Any examples you can share? >> Great question. And we're definitely focusing on making sure stability is a core value for both of us, so that what we offer, that our customers can trust, is going to work well and be dependable, so that's a key focus for us. We're also looking at how can we advance into the future, what can we do around machine learning, it's an area that's really exciting for a lot of the CXO-level leadership at our customers, so we're certainly focused on that. And also looking at Power BI and the visualization of how do we bring these solutions together as well. I'd also say at the same time, we're trying to make the buying experience frictionless for our customers, so we're also leveraging and innovating with Azure's Marketplace, so that our customers can easily acquire Snowflake together with Azure. And even that is being helpful for our customers. Casey, what are your thoughts, too? >> Yeah, let me add to that. I think the work that we've done with Power BI is pretty, pretty powerful. I mean, ultimately, we've got customers out there that are looking to better visualize the data, better inform decisions that they're making. So as much as AI and ML and the inherent power of the data that's being stored within Snowflake is important in and of itself, Power BI really unlocks that and helps drive better decisions, better visualization, and help drive to decision outcomes that are important to the customer. So I love the work that we're doing on Power BI and Snowflake. >> Yeah, and you guys both mentioned, you know, machine learning. I mean, they really are an ecosystem of tools. And the thing to me about Azure, it's all about optionality. You mentioned earlier, Casey, you guys are a platform. So, you know, customer A may want to use Power BI. Another customer might want to use another visualization tool, fine, from a platform perspective, you really don't care, do you? So I wonder Colleen, if we could, and again, maybe Casey can chime in afterwards. You guys, obviously everybody these days, but you in particular, you're focused on customer outcomes. That's the sort of starting point, and Snowflake for sure has built pretty significant experience working with large enterprises and working alongside of Microsoft to get other partners. In your experience, what are customers really looking for out of the two joint companies when they engage with Snowflake and Microsoft, so that one plus one is, you know, much bigger than two. Maybe Colleen, you could start. >> Yeah, I definitely think that what our customers are looking for is both trust and seamlessness. They just want the technology to work. The beauty of Snowflake is our ease of use. So many customers have questions about their business, more so now in this pandemic world than ever before. So the seamlessness, the ease of use, the frictionless, all of these things really matter to our joint customers, and seeing our teams come together, too, in the field, to show here's how Snowflake and Azure are better together, in your local area, and having examples of customers where we've had win-wins, which I'd say Casey, we're getting more and more of those every day, frankly, so it's pretty exciting times. And having our sales teams work as a partnership, even though we compete, we know where we play well together, and I see us doing that over and over again, more and more, around the world, too, which is really important as Snowflake pushes forward, beyond the North America geographies into stronger and stronger in the global regions, where frankly, Microsoft's had a long, storied history at. That's very exciting, especially in Europe and Asia. >> Casey, anything you'd add to that? >> Yeah. Colleen, it's well said. I think ultimately, what customers are looking for is that when our two companies come together, we bring new innovation, new ideas, new ways to solve old problems. And so I think what I love about this partnership is ultimately when we come together, whether it's engineering teams coming together to build new product, whether it's our sales and marketing teams out in front of the customers, across that spectrum, I think customers are looking for us to help bring new ideas. And I love the fact that we've engineered this partnership to do just that. And ultimately we're focused on how do we come together and build something new and different. And I think we can solve some of the most challenging problems with the power of the data and the innovation that we're bringing to the table. >> I mean, you know, Casey, I mean, everybody's really quite in awe and amazed at Microsoft's transformation, and really openness and willingness to really, change and lean into some of the big waves. I wonder if you could talk about your multi-platform strategy and what problems that you're solving in conjunction with Snowflake. >> Yeah, let me start by saying, you know, I think as much as we appreciate that feedback on the progress that we've been striving for, I mean, we're still learning every day, looking for new opportunities to learn from customers, from partners, and so a lot of what you see on the outside is the result of a really focused culture, really focusing on what's important to our customers, focusing on how do we build diversity and inclusion to everything we do, whether that's within Microsoft, with our partners, our customers, and ultimately, how do we show up as one Microsoft, I call one Microsoft kind of the partner's gift. It's ultimately how do our companies show up together? So I think if you look multi-platform, we have the same concept, right? We have the Microsoft cloud that we're offering out in the marketplace. The Microsoft cloud consists of what we're serving up as far as the platform, consists of what we're serving up for data and AI, modern workplace and business applications. And so this multi-cloud strategy for us is really focused on how do we bring innovation across each of the solution areas that matter most to customers. And so I see really the power of the Snowflake partnership playing in there. >> Awesome. Colleen, are there any examples you can share where, maybe this partnership has unlocked the customer opportunity or unique value? >> Yeah, I can't speak about the customer-specific, but what I can do and say is, Casey and I play very corporate roles in terms of we're thinking about the long-term partnership, we're driving the strategy. But hey, look, we'll get called in, we're working a deal right now, it's almost close of the quarter for us, we're literally working on an opportunity right now, how can we win together, how can we be competitive, the customers, the CIO has asked us to come together, to work on that solution. Very large, well-known brand. And we're able to get up to the very senior levels of our companies very quickly to make decisions on what do we need to do to be better and stronger together. And that's really what a partnership is about, you can do the long-term plans and the strategics and you can have great products, but when your executives can pick up the phone and call each other to work on a particular deal, for a particular customer's need, I think that's where the power of the partnership really comes together, and that's where we're at. And that's been a growth opportunity for us this year, is, wasn't necessarily where we were at, and I really have to thank Casey for that. He's done a ton, getting us the right glue between our executives, making sure the relationships are there, and making sure the trust is there, so when our customers need us to come together, that dialogue and that shared diction of putting customers first is there between both companies. So thank you, Casey. >> Oh, thanks, Colleen, the feeling's mutual. >> Well, I think this is key because as I said up front, we've gone from sort of very product-focused to platform-focused. And now we're tapping the power of the ecosystem. That's not always easy to get all the parts moving together, but we live in this API economy. You could say "Hey, I'm a company, everything's going to be homogeneous. Everything is going to be my stack." And maybe that's one way to solve the problem, but really that's not how customers want to solve the problem. Casey, I'll give you the last word. >> Yeah, let me just end by saying, you know, first off the cultures between our two companies couldn't be more well aligned. So I think ultimately when you ask yourself the question, "What do we do to best show up in front of our customers?" It is, focus on their business outcomes, focus on the things that matter most to them. And this partnership will show up well. And I think ultimately our greatest opportunity is to tap into that need, to that interest. And I couldn't be happier about the partnership and the fact that we are so well aligned. So thank you for that. >> Well guys, thanks very much for coming on theCUBE and unpacking some of the really critical aspects of the ecosystem. It was really a pleasure having you. >> Thank you so much for having us. >> Okay, and thank you for watching. Keep it right there. We've got more great content coming your way at the Data Cloud Summit.

>> 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.

>>Okay, >>listen, we're gearing up for the start of the snowflake Data Cloud Summit, and we wanna go back to the early roots of Snowflake. We've got some of the founding engineers here. Abdul Monir, Ashish Motive, Allah and Alison Lee There three individuals that were at snowflake in the early years and participated in many of the technical decisions that led to the platform and is making snowflake famous today. Folks, great to see you. Thanks so much for taking some time out of your busy schedules. Hey, it's gotta be really gratifying. Thio, See this platform that you've built, you know, taking off and changing businesses. So I'm sure it was always smooth sailing. Right? There were. There were no debates. Wherever. >>I've never seen an engineer get into the bed. >>Alright, So seriously so take us back to the early days. You guys, you know, choose whoever wants to start. But what was it like early on? We're talking 2013 here, right? >>When I think back to the early days of Snowflake, I just think of all of us sitting in one room at the time. You know, we just had an office that was one room with, you know, 12 or 13 engineers sitting there clacking away on our keyboards, uh, working really hard, turning out code, uh, punctuated by you know, somebody asking a question about Hey, what should we do about this, or what should we do about that? And then everyone kind of looking up from their keyboards and getting into discussions and debates about the work that we're doing. >>So so Abdul it was just kind of heads down headphones on, just coating or e think there was >>a lot of talking and followed by a lot of typing. Andi, I think there were periods of time where where you know, anyone could just walk in into the office and probably out of the office and all the here is probably people, uh, typing away at their keyboards. And one of my member vivid, most vivid memories is actually I used to sit right across from Alison, and there's these huge to two huge monitor monitors between us and I would just here typing away in our keyboard, and sometimes I was thinking and and and, uh and all that type and got me nervous because it seemed like Alison knew exactly what what, what she needed to do, and I was just still thinking about it. >>So she she was just like bliss for for you as a developer engineer was it was a stressful time. What was the mood? So when you don't have >>a whole lot of customers, there's a lot of bliss. But at the same time, there was a lot of pressure on us to make sure that we build the product. There was a time line ahead of us. We knew we had to build this in a certain time frame. Um, so one thing I'll add to what Alison and Abdulle said is we did a lot of white boarding as well. There are a lot of discussions, and those discussions were a lot of fun. They actually cemented what we wanted to build. They made sure everyone was in tune, and and there we have it. >>Yes, so I mean, it is a really exciting time doing any start up. But when you know when you have to make decisions and development, invariably you come to a fork in the road. So I'm curious as to what some of those forks might have been. How you guys decided You know which fork to take. Was there a Yoda in the room that served as the Jedi master? I mean, how are those decisions made? Maybe you could talk about that a little bit. >>Yeah, that's an interesting question. And I think one of a Zai think back. One of the memories that that sticks out in my mind is is this, uh, epic meeting and one of our conference rooms called Northstar. Many of our conference rooms are named after ski resorts because the founders, they're really into skiing. And that's why that's where the snowflake name comes from. So there was this epic meeting and I'm not even sure exactly what topic we were discussing. I think it was It was the sign up flow and and there were a few different options on the table and and and one of the options that that people were gravitating Teoh, one of the founders, didn't like it and and on, and they said a few times that there's this makes no sense. There's no other system in the world that does it this way, and and I think one of the other founders said, uh, that's exactly why we should do it this way. And or at least seriously, consider this option. So I think there was always this, um, this this, uh, this tendency and and and this impulse that that we needed to think big and think differently and and not see the world the way it is but the way we wanted it to be and then work our way backwards and try to make it happen. >>Alison, Any fork in the road moments that you remember. >>Well, I'm just thinking back to a really early meeting with sheesh! And and a few of our founders where we're debating something probably not super exciting to a lot of people outside of hardcore database people, which was how to represent our our column metadata. Andi, I think it's funny that you that you mentioned Yoda because we often make jokes about one of our founders. Teary Bond refer to him as Yoda because he hasn't its tendency to say very concise things that kind of make you scratch your head and say, Wow, why didn't I think of that? Or you know, what exactly does that mean? I never thought about it that way. So I think when I think of the Yoda in the room, it was definitely Terry, >>uh, excuse you. Anything you can add to this, this conversation >>I'll agree with Alison on the you're a comment for short. Another big fork in the road, I recall, was when we changed. What are meta store where we store our own internal metadata? We used >>to use >>a tool called my sequel and we changed it. Thio another database called Foundation TV. I think that was a big game changer for us. And, you know, it was a tough decision. It took us a long time. For the longest time, we even had our own little branch. It was called Foundation DB, and everybody was developing on that branch. It's a little embarrassing, but, you know, those are the kind of decisions that have altered altered the shape of snowflake. >>Yeah. I mean, these air, really, you know, down in the weeds, hardcore stuff that a lot of people that might not be exposed to What would you say was the least obvious technical decision that you had to make it the time. And I wanna ask you about the most obvious to. But what was the what was the one that was so out of the box? I mean, you kind of maybe mentioned it a little bit before, but what if we could double click on that? >>Well, I think one of the core decisions in our architectures the separation of compute and storage on Do you know that is really court architecture. And there's so many features that we have today, um, for instance, data sharing zero copy cloning that that we couldn't have without that architecture. Er, um and I think it was both not obvious. And when we told people about it in the early days, there was definitely skepticism about being able to make that work on being able Thio have that architecture and still get great performance. >>Anything? Yeah, anything that was, like, clearly obvious, that is, Maybe that maybe that was the least and the most that that separation from computing story because it allowed you toe actually take advantage of cloud native. But But was there an obvious one that, you know, it's sort of dogma that you, you know, philosophically lived behind. You know, to this day, >>I think one really obvious thing, um is the sort of no tuning, no knobs, ease of use story behind snowflake. Andi and I say it's really obvious because everybody wants their system to be easy to use. But then I would say there are tons of decisions behind that, that it's not always obvious three implications of of such a choice, right, and really sticking to that. And I think that that's really like a core principle behind Snowflake that that led to a lot of non obvious decisions as a result of sticking to that principle. So, yeah, I >>think to add to that now, now you've gotten us thinking I think another really interesting one was was really, um, should we start from scratch or or should we use something that already exists and and build on top of that? And I think that was one of these, um, almost philosophical kind of stances that we took that that a lot of the systems that were out there were the way they were because because they weren't built for the for the platforms that they were running on, and the big thing that we were targeting was the cloud. And so one of the big stances we took was that we were gonna build it from scratch, and we weren't gonna borrow a single line of code from many other database out there. And this was something that really shocked a lot of people and and many times that this was pretty crazy and it waas. But this is how you build great products. >>That's awesome. All right. She should give you the last word. We got, like, just like 30 seconds left to bring us home >>Your till date. Actually, one of those said shocks people when you talk to them and they say, Wow, you're not You're not really using any other database and you build this entirely yourself. The number of people who actually can build a database from scratch are fairly limited. The group is fairly small, and so it was really a humongous task. And as you mentioned, you know, it really changed the direction off how we design the database. What we what does the database really mean? Tow us right the way Snowflake has built a database. It's really a number of organs that come together and form the body and That's also a concept that's novel to the database industry. >>Guys, congratulations. You must be so proud. And, uh, there's gonna be awesome watching the next next decade, so thank you so much for sharing your stories. >>Thanks, dude. >>Thank you.

>> Okay, listen, we're gearing up for the start of the Snowflake Data Cloud Summit and we want to go back to the early roots of Snowflake. We got some of the founding engineers here, Abdul Muneer, Ashish Modivala, and Alison Lee. They're three individuals that were at Snowflake in the early years and participated in many of the technical decisions that led to the platform that is making Snowflake famous today. Folks, great to see you. Thanks so much for taking some time out of your busy schedules. >> Than you for having us. >> Same. >> Hey, it's got to be really gratifying to see this platform that you've built, you know, taking off and changing businesses. So, I'm sure it was always smooth sailing, right? There were no debates, were there ever? >> Never. >> Now, I've never seen an engineer get into a debate. (laughter) >> All right, so seriously though, so take us back to the early days, you guys, you know, choose whoever wants to start but, what was it like early on? We're talking 2013 here, right? >> That's right. >> When I think back to the early days of Snowflake, I just think of all of us sitting in one room at the time you know, we just had an office that was one room with you know, 12 or 13 engineers sitting there, clacking away at our keyboards, working really hard, churning out code, punctuated by, you know, somebody asking a question about, "Hey, what should we do about this? Or what should we do about that?" And then everyone kind of looking up from their keyboards and getting into discussions and debates about, about the work that we were doing. >> So Abdul, it was just kind of heads down, headphones on, just coding, or >> I think there was a lot of talking and followed by a lot of typing. And, and I think there were periods of time where, you know, anyone could just walk in into the office and probably out of the office and all they'd hear is probably people typing away at their keyboards. And one of my vivid, most vivid memories is is actually I used to sit right across from Alison and there's these huge two, two huge monitors monitors between us. And I would just hear her typing away at our keyboard. And sometimes I was thinking and and all that typing got me nervous because it seemed like Alison knew exactly what, what she needed to do, and I was just still thinking about it. >> So Ashish was this like bliss for you as a developer, an engineer, or was it, was it a stressful time? What was the mood? >> When you don't have a whole lot of customers there's a lot of bliss, but at the same time, there's a lot of pressure on us to make sure that we build the product. There was a timeline ahead of us, we knew we had to build this in a certain timeframe. So one thing I'll add to what Alison and Abdul said is we did a lot of white boarding as well. There were a lot of discussions and those discussions were a lot of fun. They actually cemented what we wanted to build. They made sure that everyone was in tune and there we have it. >> (Dave) Yeah, so, I mean, it is a really exciting time doing any startup. When you have to make decisions in development and variably you come to a fork in the road. So I'm curious as to what some of those forks might've been, how you guys decided, you know, which fork to take. Was there a Yoda in the room that served as the Jedi master? I mean, how are those decisions made? Maybe you could talk about that a little bit. >> Yeah. That's an interesting question. And I think one of, as I think back, one of the memories that, that sticks out in my mind is this epic meeting in one of our conference rooms called North star. And many of our conference rooms are named after ski resorts because the founders are really into skiing and that's why, that's where the Snowflake names comes from. So there was this epic meeting and and I'm not even sure exactly what topic we were discussing. I think it was, it was the signup flow and there were a few different options on the table. and one of the options that, that people were gravitating to one of the founders didn't like it. And they said a few times that there's this makes no sense, there's no other system in the world that does it this way. And I think one of the other founders said that's exactly why we should do it this way. And, or at least seriously considered this option. So I think there was always this this tendency and this impulse that that we needed to think big and think differently and not see the world the way it is but the, the way we wanted it to be and then work our way backwards and try to make it happen. >> Alison, any fork in the road moments that you remember? >> Well, I'm just thinking back to a really early meeting with Ashish and a few of our founders where we were debating something, probably not super exciting to a lot of people outside of hardcore database people which was how to represent our column metadata. And I think it's funny that you, that you mentioned Yoda because we often make jokes about one of our founders Terry and referred to him as Yoda, because he has this tendency to say very concise things that kind of make you scratch your head and say, "Wow why didn't I think of that?" Or, you know, what exactly does that mean? I never thought about it that way. So I think when I think of the Yoda in the room, it was definitely Terry. >> Ashish, anything you can add to this conversation? >> I'll agree with Alison on the Yoda comment, for sure. Another big fork in the road I recall was when we changed one of our meta store where we store our on internal metadata. We used to use a tool called MySQL and we changed it to another database called FoundationDB, I think that was a big game changer for us. And, you know, it was a tough decision, it took us a long time. For the longest time we even had our own little branch it was called FoundationDB and everybody who was developing on that branch. It's a little embarrassing, but, you know, those are the kinds of decisions that alter the shape of Snowflake. >> Yeah, I mean, these are really, you know, down in the weeds hardcore stuff that a lot of people might not be exposed to. What would you say was the least obvious technical decision that you had to make at the time? And I want to ask you about the most obvious too, but what was the one that was so out of the box? I mean, you kind of maybe mentioned it a little bit before but I wonder if we could double click on that? >> Well, I think one of the core decisions in our architecture is the separation of compute and storage. And, you know, that is really core to our architecture, and there are so many features that we have today for instance, data sharing, zero copy cloning, that we couldn't have without that architecture. And I think it was both not obvious, and when we told people about it in the early days there was definitely skepticism about being able to make that work and being able to have that architecture and still get great performance. >> Exactly. >> Yeah. Anything that was like clearly obvious that maybe that, maybe that was the least and the most that, that separation from compute and store, because it allowed you to actually take advantage of Cloud native. But was there an obvious one that you know, is it sort of dogma that you, you know philosophically live by, you know, to this day? >> I think one really obvious thing is the sort of no tuning, no knobs, ease of use story behind Snowflake. And I say, it's really obvious because everybody wants their system to be easy to use. But then I would say there were tons of decisions behind that, that it's not always obvious, the implications, of such a choice, right? And really sticking to that. And I think that that's really like a core principle behind Snowflake, that led to a lot of non-obvious decisions as a result of sticking to that principle. >> So >> I think, to add to that, now you've grabbed us thinking. I think another really interesting one was really, should we start from scratch or should we use something that already exists and build on top of that? And I think that was one of these almost philosophical kind of stances that we took, that a lot of the systems that were out there were the way they were, because, because they weren't built for the, for the platforms that they were running on. And the big thing that we were targeting was the Cloud. And so one of the big stances we took was that we were going to build from scratch. And we weren't going to borrow a single line of code from many other database out there. And this was something that really shocked a lot of people and many times that this was pretty crazy, and it was, but this is how you build great products. >> That's awesome. All right Ashish, I should give you the last word. We got like just like 30 seconds left, bring us home. >> Till date, actually one of those said shocks people when you talk to them and they say, "Wow, you are naturally using any other database, and you build this entirely yourself." The number of people who actually can build a database from scratch are fairly limited, the group is fairly small. And so it was really a humongous task, and as you've mentioned, you know, it really changed the direction of how we designed a database. What we, what does the database really mean to us, right? The way Snowflake has built a database, it's really a number of organs that come together and form the body. And that's also a concept that's novel to the database industry. >> Guys, congratulations, you must be so proud and it's going to be awesome watching the next decade. So thank you so much for sharing your stories. >> Thanks too. >> Thank you. >> Thank you.

>> Hello everyone, and welcome back to The Data Cloud Summit 2020. We're going to dig into the all-important ecosystem, and focus in little bit on the intersection of the data cloud and trust. And with me are Ann-Christel Graham, AKA A.C., she's the CRO of Talend, and Chris Degnan is the CRO of Snowflake. We have the go-to-market heavies on this section, folks. Welcome to theCUBE. >> Thank you. >> Thanks for having us. >> Yeah, it's our pleasure. And so let's talk about digital transformation, right? Everybody loves to talk about it. It's an overused term, I know, but what does it mean? Let's talk about the vision of the data cloud for Snowflake and digital transformation. A.C., we've been hearing a lot about digital transformation over the past few years. It means a lot of things to a lot of people. What are you hearing from customers? How are they thinking about what I sometimes call DX? And what's important to them, maybe address some of the challenges even that they're facing? >> Dave, that's a great question. To our customers, digital transformation literally means staying in business or not. It's that simple. The reality is most agree on the opportunity to modernize data management infrastructure, that they need to do that to create the speed, and efficiency, and cost savings that digital transformation promises. But now it's beyond that. What's become front and center for our customers is the need for trusted data supported by an agile infrastructure that can allow a company to pivot operations as they need. Let me give you an example of that. One of our customers, a medical device company, was on their digital journey when COVID hit. They started last year in 2019. And as the pandemic hit, at the earlier part of this year, they really needed to take a closer look at their supply chain, and went through an entire supply chain optimization, having been completely disrupted in the, you think about the logistics, the transportation, the location of where they needed to get parts, all those things, when they were actually facing a need to increase production by about 20 times in order to meet the demand. And so you can imagine what that required them to do, and how reliant they were on clean, compliant, accurate data that they could use to make extremely critical decisions for their business. And in that situation, not just for their business, but decisions that would be about saving lives. So the stakes have gotten a lot higher and that's just one industry, it's really across all industries. So when you think about that, really, when you talk to any of our customers, digital transformation really means now having the confidence in data to support the business at critical times with accurate, trusted information. >> I mean, if you're not a digital business today, you're kind of out of business. Chris, I've always said a key part of digital transformation is really putting data at the core of everything. You know, not the manufacturing plant at the core and the data around it, but putting data at the center. And it seems like that's what Snowflake is bringing to the table. Can you comment? >> Yeah, I mean, I think if I look across what's happening, especially as A.C. said, you know, through COVID, is customers are bringing more and more data sets. They want to make smarter business decisions based on making data-driven decisions. And we are seeing acceleration of data moving to the cloud because there's just an abundance of data, and it's challenging to actually manage that data on-premise. And as we see those customers move those large data sets, I think what A.C. said is spot on, is that customers don't just want to have their data in the cloud, but they actually want to understand what the data is, understand who's has access to that data, making sure that they're actually making smart business decisions based on that data set. And I think that's where the partnership between both Talend and Snowflake are really tremendous, where, you know, we're helping our customers bring their data assets to to the cloud, really landing it, and allowing them to do multiple different types of workloads on top of this data cloud platform in Snowflake. And then I think, again, what Talend is bringing to the table is really helping the customer make sure that they trust the data that they're actually seeing. And I think that's a really important aspect of digital transformation today. >> Awesome, and I want to get into the partnership, but I don't want to leave the pandemic just yet. A.C., I want to ask you how it's affected customer priorities and timelines with regard to modernizing their data operations. And what I mean to that, I think about the end-to-end life cycle of going from kind of raw data to insights and how they're approaching those life cycles. Data quality is a key part of it. If you don't have good data quality, I mean, obviously you want to iterate, and you want to move fast, but if it's garbage out, then you got to to start all over again. So what are you seeing in terms of the effect of the pandemic and the urgency of modernizing those data operations? >> Yeah, well, like Chris just said, it accelerated things. For those companies that hadn't quite started their digital journey, maybe it was something that they had budgeted for, but hadn't quite resourced completely, many of them, this is what it took to really get them off the dime from that perspective, because there was no longer the opportunity to wait. They needed to go and take care of this really critical component within their business. So, you know, what COVID I think has taught companies, taught all of us, is how vulnerable even the largest companies and most robust enterprises can be. Those companies that had already begun their digital transformation, maybe even years ago, had already started that process and were in a great position in their journey, they fared a lot better, and we're able to be agile, were able to, you know, shift priorities, were able to go after what they needed to do to run their businesses better and be able to do so with real clarity and confidence. And I think that's really the second piece of it is for the last six months, people's lives have really depended on the data. People's lives have really depended on certainty. The pandemic has highlighted the importance of reliable and trustworthy information, not just the proliferation of data. And as Chris mentioned, just data being available. It's really about making sure that you can use that data as an asset. And that the greatest weapon we all have really there is the information and good information to make great business decisions. >> And, of course, Chris, the other thing we've seen is the acceleration to the cloud, which is obviously you (indistinct) born in the cloud. It's been a real tailwind. What are you seeing in that regard from your, I was going to say in the field, but from your Zoom vantage point. >> (laughs) Yeah, well, I think, you know, A.C. talked about supply chain analytics in her previous example. And I think one of the things that we did is we hosted a dataset, the COVID data set, COVID-19 dataset within Snowflake's data marketplace. And we saw customers that were, you know, initially hesitant to move to the cloud really accelerate their usage of Snowflake in the cloud with this COVID data set. And then we had other customers that are, you know, in the retail space, for example, and use the COVID data set to do supply chain analytics and accelerated, you know, it helped them make smarter business decisions on that. So, I'd say that, you know, COVID has made customers that were maybe hesitant to start their journey in the cloud move faster. And I've seen that, you know, really go at a blistering pace right now. >> You know, A.C., you just talked about value, 'cause it's all about value, but you know, the old days of data quality and the early days of chief data officer, all the focus was on risk avoidance, how do I get rid of data, how long do I have to keep it? And that has flipped dramatically, you know, sometime during the last decade. I wonder if you could talk about that a little bit. 'Cause I know you talk to a lot of CDOs out there, and have you seen that flip, where the value piece is really dwarfing that risk piece? And not that you can ignore the risk, but that's almost table stakes. What are your thoughts? >> You know, that's interesting, saying it's almost table stakes. I think you can't get away too much from the need for quality data and governed data. I think that's the first step, you can't really get to trust the data without those components. And, but to your point, the chief data officer's role, I would say, has changed pretty significantly. And in the round tables that I've participated in over the last, you know, several months, it's certainly a topic that they bring to the table that they'd like to, you know, chat with their peers about in terms of how they're navigating through the balance, that they still need to manage to the quality, they still need to manage to the governance, they still need to ensure that they're delivering that trusted information to the business. But now on the flip side as well, they're being relied upon to bring new insights and it's really requiring them to work more cross-functionally than they may have needed to in the past, where that's become a big part of their job is being that evangelist for data, the evangelist for those insights, and being able to bring in new ideas for how the business can operate. And identify, you know, not just operational efficiencies, but revenue opportunities, ways that they can shift. All you need to do is take a look at, for example, retail. You know, retail was heavily impacted by the pandemic this year, and it shows how easily an industry can be just kind of thrown off its course simply by just a significant change like that. And they need to be able to adjust. And this is where, when I've talked to some of the CDOs of the retail customers that we work with, they've had to really take a deep look at how they can leverage the data at their fingertips to identify new and different ways in which they can respond to customer demands. So it's a whole different dynamic, for sure. It doesn't mean that you walk away from the other end, the original part of the role or the areas in which they were maybe more defined a few years ago when the role of the chief data officer became very popular. I do believe it's more of a balance at this point, and really being able to deliver great value to the organization with the insights that they can bring. >> Well A.C., stay on that for a second. So you have this concept of data health, and I guess what I'm kind of getting at is that the early days of big data, Hadoop, it was just a lot of rogue efforts going on. People realized, wow, there there's no governance. And what's what seems like with Snowflake and Talend are trying to do is to make that so the business doesn't have to worry about it, build that in, don't bolt it on. But what's this notion of data health that you talk about? >> Well, it's interesting. Companies can measure and do measure just about everything, every aspect of their business health. Except what's interesting is they don't have a great way to measure the health of their data. And this is an asset that they truly rely on. Their future depends on is that health of their data. And so if we take a little bit of a step back, maybe let's take a look at an example of a customer experience just to kind of make a little bit of a delineation between the differences of data quality, data trust, and what data health truly is. We work with a lot of hotel chains, and like all companies today, hotels collect a ton of information. There's mountains of information, private information about their customers, through the loyalty clubs, and all the information that they collect from their the front desk, the systems that store their data. You can start to imagine the amount of information that a hotel chain has about an individual. And frequently, that information has errors in it, such as duplicate entries, you know, is it A.C. Graham, or is it Ann-Christel Graham? Same person, slightly different, depending on how I might've looked, or how I might've checked in at the time. And sometimes the data's also mismanaged, where because it's in so many different locations, it could be accessed by the wrong person, if someone that wasn't necessarily intended to have that kind of visibility. And so these are examples of when you look at something like that, now you're starting to get into, you know, privacy regulations, and other kinds of things that can be really impactful to a business if data's in the wrong hands or if the wrong data is in the wrong hands. So, you know, in a world of misinformation and mistrust, which is around us every single day, Talend has really invented a way for businesses to verify the veracity, the accuracy of their data. And that's where data health really comes in is being able to use a trust score to measure the data health. And that's what we've recently introduced is this concept of the trust score, something that can actually provide and measure the accuracy and the health of the data, all the way down to an individual report. And we believe that that truly provides the explainable trust, issue resolution, the kinds of things that companies are looking for in that next stage of overall data management. >> Thank you. Chris, bring us home. So one of the key aspects of what Snowflake is doing is building out the ecosystem. It's very, very important. Maybe talk about how you guys are partnering and adding value, in particular things that you're seeing customers do today within the ecosystem or with the help of the ecosystem and Snowflake, that they weren't able to do previously? >> Yeah, I mean, I think, you know, A.C. mentioned it, you mentioned it. I spend a lot of my Zoom days talking to chief data officers. And as I'm talking to these chief data officers, they are so concerned, their responsibility on making sure that the business users are getting accurate data, so that they view that as data governance, as one aspect of it. But the other aspect is the circumference of the data, of where it sits, and who has access to that data, and making sure it's super secure. And I think, you know, Snowflake is a tremendous landing spot, being a data warehouse or a cloud data platform as a service. You know, we take care of all the securing that data. And I think where Talend really helps our customer base is helps them exactly what A.C. talked about, is making sure that myself as a business user, someone like myself, who's looking at data all the time, trying to make decisions on how many salespeople I want to hire, how's my forecast coming, you know, how's the product working, all that stuff. I need to make sure that I'm actually looking at good data. And I think the combination of it all sitting in a single repository like Snowflake, and then layering a tool like Talend on top of it where I can actually say, yeah, that is good data, it helps me make smarter decisions faster. And ultimately, I think that's really where the ecosystem plays an incredibly important role for Snowflake and our customers >> Guys, two great guests. I wish we had more time, but we got to go. And so thank you so much for sharing your perspectives, a great conversation. >> Thank you for having us, Dave. >> Thanks Dave. >> All right, and thank you for watching. Keep it right there. We'll be back with more from The Data Cloud Summit 2020.

(upbeat music) >> From the CUBE studios in Palo Alto, in Boston, connecting with thought leaders all around the world. This is a CUBE conversation. >> Hi everyone, this is Dave Vellante from the CUBE. And we're getting ready for the Snowflake Data cloud summit four geographies, eight tracks more than 40 sessions for this global event. Starts on November 17th, where we're tracking the rise of the Data cloud. You're going to hear a lot about that, now, by now, you know, the story of Snowflake or you know, what maybe you don't but a new type of cloud native database was introduced in the middle part of last decade. And a new set of analytics workloads has emerged that is powering a transformation within organizations. And it's doing this by putting data at the core of businesses and organizations. You know, for years we marched to the cadence of Moore's law. That was the innovation engine of our industry, but now that's changed it's data plus machine intelligence plus cloud. That's the new innovation cocktail for the technology industry and industries overall. And at the Data cloud summit we'll hear from Snowflake executives, founders, technologists, customers, and ecosystems partners. And of course, you going to hear from interviews on the CUBE. So, let's dig in a little bit more and help me are two Snowflake experts. Felipe Hoffa is a data cloud advocate and Kent Graziano is a chief technical evangelist post at Snowflake. Gents, great to see you. Thanks for coming on. >> Yeah, thanks for having us on, this is great. >> Thank you. >> So guys first, I got to congratulate you on getting to this point. You've achieved beyond escape velocity and obviously one of the most important IPOs of the year, but you got a lot of work to do. I know that what, what are the substantive aspects behind the Data cloud? >> I mean, it's a new concept right? We've been talking about infrastructure clouds and SaaS applications living in application clouds and Data cloud is the ability to really share all that data that we've been collected. You know, we've spent what how many a decade or more with big data now but have we been able to use it effectively? And that's really where the Data cloud is coming in and Snowflake and making that a more seamless, friendly, easy experience to get access to the data. I've been in data warehousing for nearly 30 years now. And our dream has always been to be able to augment an organization's analytics with data from outside their organization. And that's just been a massive pain in the neck with having to move files around and replicate the data and maybe losing track of where it came from or where it went. And the Data cloud is really giving our customers the ability to do that in a much more governed way, a much more seamless way and really make it push button to give anyone access to the data they need and have the performance to do the analytics in near real time. It's total game changer is as you already know and just it's crazy what we're able to do today compared it to what we could do when I started out in my career. >> Well, I'm going to come back to that 'cause I want to tap your historical perspective, but Felipe let me ask you, So, why did you join Snowflake? You're you're the newbie here? What attracted you? >> Exactly? I'm the newbie, I used to work at Google until August. I was there for 10 years. I was a developer advocate there also for data you might have heard about the BigQuery. I was doing a lot of that. And then as time went by Snowflake started showing up more and more in my feeds within my customers in my community. And it came the time, well, I felt that like, you know, when wherever you're working, once in a while you think I should leave this place I should try something new, I should move my career forward. While at Google, I thought that so many times, as anyone would do, and it was only when Snowflake showed up, like where Snowflake is going now, why Snowflake is being received by all the customers that I saw this opportunity. And I decided that moving to Snowflake would be a step forward for me. And so far I'm pretty happy, like the timing has been incredible, but more than the timing and everything, it's really, really a great place for data. What I love first is data, sharing data, analyzing data and how Snowflake is doing it's for me to mean phenomenal. >> So, Kent, I want to come back to you and I say tap maybe your historical perspective here. And you said it's always been a dream that you could do these other things bringing in external data. I would say this, that I don't want to push a little bit on this because I have often said that the EDW marketplace really never lived up to its promises of 360 degree views of the customer real time or near real time analytics. And, and it really has been as you kind of described are a real challenge for a lot of organizations. When Hadoop came in we got excited that it was going to actually finally live up to that vision and, and duped it a lot and don't get me wrong, I mean, the whole concept of bring that compute to data and lowering the cost and so forth. But it certainly didn't minimize complexity. And, and it seems like, feels like Snowflake is on the cusp of actually delivering on that promise that we've been talking about for 30 years. I wonder, if you could share your perspective is it, are we going to get there this time? >> Yeah. And as far as I can tell working with all of our customers some of them are there. I mean, they thought through those struggles that you were talking about that I saw throughout my career and now with getting on Snowflake they're delivering customer 360 they're integrating weblogs and IOT data with structured data from their ERP systems or CRM systems, their supply chain systems. And it really is coming to fruition. I mean, the industry leaders, you know, Bill Inman and Claudia Imhoff, they've had this vision the whole time but the technology just wasn't able to support it. And the cloud, as we said about the internet, changed everything. And then Ben wine teary, and they're in their vision and building the system, taking the best concepts from the Hadoop world and the data Lake world and the enterprise data warehouse world and putting it all together into this, this architecture that's now Snowflake and the Data cloud solve it. I mean, it's the classic benefit of hindsight is 2020 after years in the industry, they'd seen these problems and said like, how can we solve them? Does the Cloud let us solve these problems? And the answer was yes, but it did require writing everything from scratch and starting over with, because the architecture of the Cloud just allows you to do things that you just couldn't do before. >> Yeah. I'm glad you brought up you know, some of the originators of the data warehouse because it really wasn't their fault. They were trying to solve a problem. It was the marketers that took it and really kind of made promises that they couldn't keep. But, the reality is when you talk to customers in the so old EDW days and this is the other thing I want to tap you guys' brains on. It was very challenging. I mean, one customer one time referred to it as a snake, swallowing a basketball. And what he meant by that is every time there's a change Sarbanes Oxley comes and we have to ingest all this new data. It's like, Oh, it's to say everything slows down to a grinding halt. Every time Intel came out with a new microprocessor, they would go out and grab a new server as fast as they possibly could. He called it chasing the chips and it was this endless cycle of pain. And so, you know, the originators of the data whereas they didn't have the compute power they didn't have the Cloud. And so, and of course they didn't have the 30, 40 years of pain to draw upon. But I wonder if you could, could maybe talk a little bit about the kinds of things that can be done now that we haven't been able to do here to form. >> Well, yeah. I remember early on having a conversation with Bill about this idea of near real time data warehousing and saying, is this real, is this something really people need? And at the time he was a couple of decades ago, he said now to them they just want to load their data sooner than once a month. That was the goal. And that was going to be near real time for them. And, but now I'm seeing it with our customers. It's like, now we can do it, you know, with things like the Kafka technology and snow pipe in Snowflake that people are able to get that refresh way faster and have near real time analytics access to that data in a much more timely manner. And so it really is coming true. And the, the compute power that's there, as you said, we've now got this compute power in the Cloud that we never dreamed of. I mean, you would think of only certain, very large, massive global companies or governments could afford super computers. And that's what it would have taken. And now we've got nearly the power of a super computer in our mobile device that we all carry around with us. So being able to harness all that now in the Cloud is really opening up opportunities to do things with data and access data in a way that, again really, we just kind of dreamed of before as like we can democratize data when we get to this point. And I think that's where we are. We're at that inflection point where now it's possible to do it. So the challenge on organizations is going to be how do we do it effectively? How do we do it with agility? And how do we do it in a governed manner? You mentioned Sarbanes Oxley, GDPR, CCPA, all of those are out there. And so we have all of that as well. And so that's where we're going to get into it, right into the governance and being able to do that in a very quick, flexible, extensible manner and Snowflakes really letting people do it now. >> Well, yeah. And you know, again, we've been talking about Hadoop and I, again, for all my fond thoughts of that era, and it's not like Hadoop is gone but it was a lot of excitement around it, but governance was a huge problem. And it was kind of a bolt on. Now, Felipe I going to ask you, like, when you think about a company like Google, your former employer, you know, data is at the core of their business. And so many companies the data is not at the core of their business. Something else is, it's a process or a manufacturing facility or whatever it is. And the data is sort of on the outskirts. You know, we often talk about in, in stove pipes. And so we're now seeing organizations really put data at the core of their, it becomes central to their DNA. I'm curious as to your thoughts on that. And also, if you've got a lot of experience with developers, is there a developer angle here in this new data world? >> For sure, I mean, I love seeing everything like throughout my career at Google and my two months here and talking to so many companies, you never thought before like these are database companies but they are the ones that keep rowing. The ones that keep moving to the next stage of their development is because they are focusing on data. They are adapting the processes, they are learning from it. Me, I focus a lot on developers. So, I met when I started this career as an advocate of first, I was a software engineer and my work so far, has we worked, I really loved talking to the engineers on the other companies. Like, maybe I'm not the one solving the business problem, but at the end of the day, when these companies have a business problem that they want to grow, they want to have data. There are other engineers that are scientists like me that want to work for the company and bring the best technology to solve the problems. And Yeah, there's so much where data can help, yes, as we evolved the system for the company, and also for us, for understanding the systems things like of survivability, and recently there was a big company a big launch on survivability (indistinct) whether they are running all of their data warehousing needs. And all of that needs on snowflake, just because running these massive systems and being able to see how they're working generates a lot of data. And then how do you manage it? How do you analyze it? Or Snowflake is really there to help cover the two areas. >> It's interesting my business partner, John farrier cohost of the CUBE, he said, gosh I would say middle of the last decade, maybe even around the time 2013, when Snowflake was just coming out, he said, he predicted the data would be the new development kit. And it's really at the center of a lot of the data life cycle the what I call the data pipelines. I know people use that term differently but I'm very excited about the Data cloud summit and what we're going to learn there. And I get to interview a lot of really cool people. So, I appreciate you guys coming up, but, Kent who should attend the Data cloud summit, I mean, what should they expect to learn? >> Well, as you said earlier, Dave, there's so many tracks and there's really kind of something for everyone. So, we've got a track on unlocking the value of the Data cloud, which is really going to speak to the business leaders, you know, as to what that vision is, what can we do from an organizational perspective with the Data cloud to get that value from the data to move our businesses forward. But we've also done for the technicians migrating to snowflake. Sessions on how to do the migration, modernizing your data Lake, data science, how to do analytics with the, and data science in Snowflake and in the Data cloud, and even down to building apps. So the developers and building data products. So, you know, we've got stuff for developers, we've got stuff for data scientists. We've got stuff for the data architects like myself and the data engineers on how to build all of this out. And then there's going to be some industry solution spotlights as well. So we can talk about different verticals folks in FinTech and healthcare, there's going to be stuff for them. And then for our data superheroes we have a hallway track where we're going to get talks from the folks that are in our data superheroes which is really our community advocacy program. So these are folks who are out there in the trenches using Snowflake delivering value at their organizations. And they're going to talk down and dirty. How did they make this stuff happen? So it's going to be to some hope, really something for everyone, fireside chats with our executives. Of course something I'm really looking forward to myself. So was fun to hear from Frank and Christian and Benoit about what's the next big thing, what are we doing now? Where are we going with all of this? And then there is going to be a some awards we'll be giving out our data driver awards for our most innovative customers. So this is going to be a lot, a lot for everybody to consume and enjoy and learn about this, this new space of, of the Data cloud. >> Well, thank you for that Kent. And I'll second that, at least there's going to be a lot for everybody. If you're an existing Snowflake customer there's going to be plenty of two or one content, we can get in to the how to use and the best practice, if you're really not that familiar with Snowflake, or you're not a customer, there's a lot of one-on-one content going on. So, Felipe, I'd love to hear from you what people can expect at the Data cloud summit. >> Totally, so I would like to plus one to everyone that can say we have a phenomenal schedule that they, the executive will be there. I really wanted to especially highlight the session I'm preparing with Trevor Noah. I'm sure you might have heard of him. And we are having him at the Data cloud summit and we are going to have a session. We are going to talk about data. We are preparing a session. That's all about how people that love data that people that want to make that actionable. How can they bring storytelling and make it more, have more impact as he has well learn to do through his life? >> That's awesome, So, we have Trevor Noah, we're not just going to totally geek out here. we're going to have some great entertainment as well. So, I want you to go to snowflake.com and click on Data cloud summit 2020 there's four geos. It starts on November 17th and then runs through the week and in the following week in Japan. So, so check that out. We'll see you there. This is Dave Vellante for the CUBE. Thanks for watching. (upbeat music)

>> (Instructor)From the cube studios in Palo Alto, in Boston, connecting with thought leaders all around the world. This is a cube conversation. >> Hi everyone. This is Dave Volante, the cube, and we're getting ready for the snowflake data cloud summit four geographies eight tracks, more than 40 sessions for this global event starts on November 17th, where we're tracking the rise of the data cloud. You're going to hear a lot about that now by now, you know the story of Snowflake or you know, what maybe you don't, but a new type of cloud native database was introduced in the middle part of last decade. And a new set of analytics workloads has emerged that is powering a transformation within organizations. And it's doing this by putting data at the core of businesses and organizations. You know for years, we marched to the cadence of Moore's law. That was the innovation engine of our industry, but now that's changed it's data plus machine intelligence plus cloud. That's the new innovation cocktail for the technology industry and industries overall. And at the data cloud summit, we'll hear from snowflake executives, founders, technologists, customers, and ecosystems partners. And of course, you're going to hear from interviews on the cube. So let's dig in a little bit more and to help me, are two snowflake experts, Filipe Hoffa is a data cloud advocate and Kent Graziano is a chief technical evangelists post at Snowflake. Gents great to see you. Thanks for coming on. >> Yeah thanks for having us on this is great. >> Thank you. >> So guys, first, I got to congratulate you on getting to this point. You've achieved beyond escape velocity, and obviously one of the most important IPOs of the year, but you got a lot of work to do I know that Filipe, let me start with you data cloud. What's a data cloud and what are we going to learn about it at the data cloud summit? >> Oh, that's an excellent question. And let me tell you a little bit about our story here. And I really, really, really admire what Kent has done. I joined the snowflake like less than two months ago, and for me it's been a huge learning experience. And I look up to Kent a lot on how we deliver the message and how do we deliver all of that. So I would love to hear his answer first. >> Okay, that's cool. Okay Kent later on. So talk of data cloud, that's a catchy phrase, right? But it vectors into at least two of the components of my innovation, innovation cocktail. What, what are the substantive substantive aspects behind the data cloud? >> I mean, it's a, it's a new concept, right? We've been talking about infrastructure clouds and SAS applications living in an application clouds so data cloud is the ability to really share all that data that we've been collecting. You know, we've, we've spent what, how many days a decade or more with big data now, but have we been able to use it effectively? And that's, that's really where the data cloud is coming in and snowflake in making that a more seamless, friendly, easy experience to get access to the data. I've been in data warehousing for nearly 30 years now. And our dream has always been to be able to augment an organization's analytics with data from outside their organization. And that's just been a massive pain in the neck with having to move files around and replicate the data and maybe losing track of where it came from or where it went. And the data cloud is really giving our customers the ability to do that in a much more governed way, a much more seamless way, and really make it push button to give anyone access to the data they need and have the performance to do the analytics in near real time. It's it's total game changer as, as you already know, and just it's crazy what we're able to do today, compared to what we could do when I started out in my career. >> Well, I'm going to come back to that cause I want to tap your historical perspective, but Filipe, let me ask you. So why did you join snowflake? You're you're the newbie here. What attracted you? >> Exactly, I'm the newbie. I used to work at Google until August. I was there for 10 years. I was a developer advocate there also for data, you might have heard about a big query. I was doing a lot of that and then as time went by, Snowflake started showing up more and more in my feeds, within my customers, in my community. And it came the time. When, I felt that like, you know, when wherever you're working, once in a while you think I should leave this place, I should try something new. I should move my career forward. While at Google, I thought that so many times as anyone would do, and it was only when snowflake showed up, like where snowflake is going now, how snowflake is, is being received by all the customers that I saw this opportunity. And I decided that moving to Snowflake would be a step forward for me. And so far I'm pretty happy. Like the timing has been incredible, but more than the timing and everything, it's really, really a great place for data. What I love first is data sharing data, analyzing data and how Snowflake is doing it it promotes me in phenomena. >> So Ken, I want to come back to you and I say, tap, maybe your historical perspective here. And you said, you know, it's always been a dream that you could do these other things bring in external data. I would say this, that I don't want to push a little bit on this because I have often said that the EDW marketplace really never lived up to its promises of 360 degree views of the customer in real time or near real time analytics. And, and it really has been, as you kind of described are a real challenge for a lot of organizations when Hadoop came in you know, we had, we we we got excited that it was kind of going to actually finally live up to that vision and and and we duped it a lot. And it don't get me wrong. I mean, the whole concept of, you know, bring the compute to data and the lowering the cost and so forth, but it certainly didn't minimize complexity. And, and it seems like, feels like Snowflake is on the cusp of actually delivering that promise that we've been talking about for 30 years. I wonder if you could share your perspective, is it, are we going to get there this time? >> Yeah. And as far as I can tell working with all of our customers, some of them are there. I mean, they're, they Fought through those struggles that you were talking about that I saw throughout my career and now with getting on Snowflake they're, they're delivering customer 360, they're integrating weblogs and IOT data with structured data from their ERP systems or CRM systems, their supply chain systems. And it really is coming to fruition. I mean, the, you know, the industry leaders, you know, Bill Inman and Claudia M Hoff, they've had this vision the whole time, but the technology just wasn't able to support it. And the cloud, as we said about the internet, changed everything and then Ben Y and Terry, in their vision and building the system, taking the best concepts from the Hadoop world and the data Lake world and the enterprise data warehouse world, and putting it all together into this, this architecture, that's now, you know Snowflake and the data cloud solved it. I mean, it's the, you know, the, the classic benefit of her insight is 2020 after years in the industry, they had seen these problems and said like, how can we solve them? Does the cloud let us solve these problems? And the answer was yes, but it did require writing everything from scratch and starting over with because the architecture the cloud just allows you to do things that you just couldn't do before. Yeah I'm glad you brought up, you know, some of the originators of the data warehouse, because it really wasn't their fault. They were trying to solve a problem. That was the marketers that took it and really kind of made promises that they couldn't keep. But the reality is when you talk to customers in the, in the, so the old EDW days, and this is the other thing I want to, I want to tap your guys' brains on. It was very challenging. I mean, one, one customer, one time referred to it as a snake, swallowing a basketball. And what he meant by that is you know, every time there's a change, you know, Sarbanes Oxley comes and we have to ingest all this new data. It's like, Oh, it's just everything slows down to a grinding halt. Every time Intel came out with a new microprocessor, they would go out and grab a new server as fast as they possibly could. He called it chasing the chips, and it was this endless cycle of pain. And so, you know, the originators of the data whereas they didn't, they didn't have you know the compute power, they didn't have the cloud. >> Yeah. >> And so, and of course they didn't have the 30- 40 years of pain to draw upon. But, but I wonder if you could, could maybe talk a little bit about the kinds of things that can be done now that we haven't been able to do here before. >> Well, yeah I remember early on having a conversation with, with Bill about this idea of near real time data warehousing and saying, is this real? Is this something really need people need? And at the time it was, was a couple of decades ago, he said no to them they just want to load their data sooner than once a month. >> Yeah. >> That was the goal. And that was going to be near real time for them. And, but now I'm seeing it with our customers. It's like, now we can do it, you know, with things like the Kafka technology and snow pipe in, in Snowflake, that people are able to get that refresh way faster and have near real time analytics access to that data in a much more timely manner. And so it really is coming true. And the, the compute power that's there, as you said, you know we, we've now got this compute power in the cloud that we never dreamed of. I mean, you would think of only certain very large, massive global companies or governments could afford supercomputers. And that's what it would have taken. And now we've got nearly the power of a supercomputer in our mobile device that we all carry around with us. So being able to harness all that now in the cloud is really opening up opportunities to do things with data and access data in a way that again really we just kind of dreamed of before. It's like, we can, we can democratize data when we get to this point. And I think that's the, that's where we are, we're at that inflection point where now it's, it's possible to do it. So the challenge on organizations is going to be, how do we do it effectively? How do we do it with agility? And how do we do it in a governed manner? You mentioned Sarbanes Oxley, GDPR, CCPA, all of those are out there. And so we have all of that as well. And so that's where, that's where we're going to get into it, right. Is into the governance and being able to do that in a very quick, flexible, extensible manner and you know, Snowflakes really letting people do it now. >> Well, yeah and you know, again, we've been talking about Hadoop and again, for all my, my fond thoughts of that era, and it's not like hadoop is gone, but, but it was a lot of excitement around it but but governance was a huge problem and it was kind of a ball tough enough. Felipe I got to ask you, like when you think about a company like Google your former employer, you know, data is at the core of their business. And so many companies, the data is not at the core of their business. Something else is it's a process or a manufacturing facility or you know whatever it is. And the data is sort of on the outskirts. You know, we often talk about in, in stove pipes. And so we're now seeing organizations really put data at the core of their it becomes, you know, central to their, to their DNA. I'm curious as to your thoughts on that. And also if you've got a lot of experience with developers, is there, is there a developer angle here in this new data world? >> Oh, for sure. I mean, I love seeing every, like throughout my career at Google and my two months here and talking to so many companies, you never thought before, like these are database companies, but the the ones that keep rowing. The ones that keep moving to the next stage of their development is because they are focusing on data. They are adapting the processes they learning from it. And me, I focus a lot on developers. So I mean when I started This career as an advocate. First I was a software engineer and my work so far, has been work, I really loved talking to the engineers on the other companies. Like maybe I'm not the one solving the business problem, but at the end of the day, when these companies have a business problem that they want to row, they want to have data. There are other engineers that are scientists likes me that are, that, that want to work for work for the company and bring the best technology to solve the problems. Yeah, there's so much where data can help as we evolve the system for the company. And also for us for understanding the systems, things like observability and recently, there was a big company, a big launch on observability the company name is observable, where they are running all of their data warehousing needs. And all of their data needs on Snowflake, just because running these massive systems and being able to see how they're working generates a lot of data. And then how do you manage it? How do you analyze it? Or snowflake is already there to help. >> Well you know >> I covered the two areas. >> It's interesting my, my business partner, John farrier, cohost of the cube, he said, gosh, I would say middle of the last decade, maybe even around the time, you know, 2013, when Snowflake was just coming out, he said, he predicted the data would be the new development kit. And you know, it's really at the center of a lot of, you know, the data life cycle, the, the, what I call the data pipelines. I know people use that term differently, but, but I'm, I'm very excited about the data cloud summit and what we're going to learn there. And I get to interview a lot of really cool people. And so I appreciate you guys coming on, but Kent, who, who should attend the data cloud summit, I mean, what, what are the, what should they expect to learn? >> Well, as you said earlier, Dave, there's, there's so many tracks and there's really kind of something for everyone. So we've got a track on unlocking the value of the data cloud, which is really going to speak to, you know, the business leaders, you know, as to what that vision is, what can we do from an organizational perspective, with the data cloud to get that value from the data to, to move our businesses forward. But we've also got, you know, for the technicians migrating to Snowflake training sessions on how to do the migration, modernizing your data like data science, you know how to do analytics with the, and data science in Snowflake and in the data cloud and even down to building apps. So the developers and building data products. So, you know, we've got stuff for developers, we've got stuff for data scientists. We've got stuff for the, the data architects like myself and the data engineers on how to, how to build all of this out. And then there's going to be some industry solutions spotlights as well. So we can talk about different verticals of folks in FinTech and, and in healthcare. There's going to be stuff for them. And then for our, our data superheroes, we have a hallway track where we're going to get talks from the folks that are in our data superheroes, which is really our community advocacy program. So these are folks who are out there in the trenches using Snowflake, delivering value at, at their organizations. And they're going to talk you know down and dirty. How did they make this stuff happen? So there's going to be just really something for everyone, fireside chats with our executives, of course, something I'm really looking forward to in myself. It's always fun to, to hear from Frank and Christian. And Benwah about, you know, what's the next big thing, you know, what are we doing now? Where are we going with all of this? And then there is going to be some awards. We'll be giving out our data driver awards for our most innovative customers. So this is going to be a lot, a lot for everybody to consume and enjoy and learn about this, this new space of, of the data cloud. >> Well, thank you for that Kent. And I'll second that, I mean, there's going to be a lot for everybody. If you're an existing Snowflake customer, there's going to be plenty of two on one content we can get in to the how to's and the best practice. If you're really not that familiar with Snowflake, or you're not a customer, there's a lot of one-on-one content going on. If you're an investor and you want to figure out, okay, what is this vision? And can, you know, will this company grow into its massive valuation and how are they going to do that? I think you're going to, you're going to hear about the data cloud and really try get a perspective. And you can make your own judgment as to, to, you know, whether or not you think that it's going to be as large a market as many people think. So Felipe, I'd love to hear from you what people can expect at the data cloud summit. >> Totally, so I would love to plus one to everyone that Kent said. We have a phenomenal schedule that the the executive will be there. And I really wanted to specially highlight the session I'm preparing with Trevor Noah. I'm sure you might have heard of him. And we are having him at the data cloud summit, and we are going to have a session. We're going to talk about data. We are preparing a session, That's all about how people that love data, that people that want to make data actionable. How can they bring storytelling and make it more, have more impact as he has well learned to do through his life. >> That's awesome, So yeah, Trevor Noah, we're not just going to totally geek out here. We're going to, we're going to have some great entertainment as well. So I want you to go to snowflake.com and click on data cloud summit, 2020 there's four geos. It starts on November 17th and then runs through the week and then the following week in Japan. So, so check that out. We'll see you there. This is Dave Volante for the cube. Thanks for watching. (soft music)

>> Narrator: From theCUBE Studios in Palo Alto in Boston, connecting with thought leaders all around the world, this is theCUBE Conversation. >> Hi everyone, this is Dave Vellante at theCUBE, and we're getting ready for the Snowflake Data Cloud Summit. four geographies, eight tracks, more than 40 sessions for this global event. starts on November 17th, where we're tracking the rise of the data cloud. You're going to hear a lot about that. Now, by now, you know the story of Snowflake or, you know what? Maybe you don't. But a new type of cloud-native database was introduced in the middle part of the last decade. And a new set of analytics workloads has emerged, that is powering a transformation within the organizations. And it's doing this by putting data at the core of businesses and organizations. For years, we marched to the cadence of Moore's law. That was the innovation engine of our industry, but now that's changed. It's data, plus machine intelligence, plus cloud. That's the new innovation cocktail for the technology industry and industries overall. And in the Data Cloud Summit, we'll hear from Snowflake executives, founders, technologists, customers, and ecosystems partners. And of course, you're going to hear from interviews on theCUBE. So let's dig in a little bit more. And to help me are two Snowflake experts. Felipe Hoffa is a data cloud advocate and Kent Graziano is a chief technical evangelist, both at Snowflake. Gents, great to see you, thanks for coming on. >> Thanks for having us on, this is great. >> Thank you. >> So guys, first, I got to congratulate you on getting to this point. You've achieved beyond escape velocity and obviously one of the most important IPOs of the year, but you got a lot of work to do and I know that. Felipe, let me start with you. Data cloud, what's a data cloud and what are we going to learn about it at the Data Cloud Summit? >> Oh, that's an excellent question. And, let me tell you a little bit about our story here. And I really, really, really admire what Kent has done. I joined Snowflake like less than two months ago and for me, it's been a huge learning experience. And I look up to Kent a lot on how we deliver the method here, how do we deliver all of that? So, I would love to hear his answer first. >> Dave: Okay, that's cool. Okay Kent, leader on. (Kent laughing) So we took it. Data cloud, that's a catchy phrase, right? But it vectors into at least two of the components of my innovation cocktail. What are the substantive aspects behind the data cloud? >> I mean, it's a new concept, right? We've been talking about infrastructure clouds and SaaS applications living in the application cloud, so data cloud is the ability to really share all that data that we've been collecting. We've spent what? How many da-- A decade or more with big data now, but have we been able to use it effectively? And that's really where the data cloud is coming in and Snowflake, in making that a more seamless, friendly, easy experience to get access to the data. I've been in data warehousing for nearly 30 years now. And our dream has always been to be able to augment an organization's analytics with data from outside their organization. And that's just been a massive pain in the neck with having to move files around and replicate the data and maybe losing track of where it came from or where it went. And the data cloud is really giving our customers the ability to do that in a much more governed way, a much more seamless way, and really make it push button to give anyone access to the data they need and have the performance to do the analytics in near real-time. It's a total game changer as you already know. And just, it's crazy what we're able to do today compared to what we could do when I started out in my career. >> Well, I'm going to come back to that 'cause I want to tap your historical perspective. But Felipe, let me ask you, so why did you join Snowflake? You're the newbie here, what attracted you? >> And finally, I'm the newbie. I used to work at Google until August. I was there for 10 years, I was a developer advocate there also for data, you might have heard about the BigQuery, I was doing a lot of that. And though as time went by, Snowflake started showing up more and more in my feeds, within my customers, in my community. And it came the time when I felt like-- Wherever you're working, once in a while you think, "I should leave this place, "I should try something new, "I should move my career forward." While at Google, I thought that so many times as anyone will do. And it was only when Snowflake showed up, like where Snowflake is going now, how Snowflake is being received by all the customers, that I saw this opportunity. And I decided that moving to Snowflake would be a step forward for me. And so far I'm pretty happy, like the timing has been incredible, but more than the timing and everything, it's really, really a great place for data. What I love first is data, sharing data, analyzing data and how Snowflake is doing it, its promising phenomena. >> So, Kent, I want to come back to you and I said, tap maybe your historical perspective here. And you said, it's always been a dream that you could do these other things, bring in external data. I would say this, that I would want to push a little bit on this because I have often said that the EDW marketplace really never lived up to its promises of 360 degree views of the customer, in real-time or near real-time analytics. And it really has been, as you kind of described it, a real challenge for a lot of organizations. When Hadoop came in, we had-- We got excited that it was going to actually finally live up to that vision and Hadoop did a lot. And don't get me wrong, I mean, the whole concept of, bring the computer data and lowering the cost and so forth. But it certainly didn't minimize complexity. And it seems like, feels like Snowflake is on the cusp of actually delivering on that promise that we've been talking about for 30 years. I wonder if you could share your perspective as an o-- Are we going to get there this time? >> Yeah. And as far as I can tell working with all of our customers, some of them are there. I mean, they thought through those struggles that you were talking about, that I saw throughout my career. And now with getting on Snowflake they're delivering customer 360, they're integrating weblogs and IOT data with structured data from their ERP systems or CRM systems, their supply chain systems and it really is coming to fruition. I mean, the industry leaders, Bill Inmon and Claudia Imhoff, they've had this vision the whole time, but the technology just wasn't able to support it and the cloud, as we said about the internet, changed everything. And then Benoit and Thierry in their vision in building the system, taking the best concepts from the Hadoop world and the data lake world and the enterprise data warehouse world, and putting it all together into this architecture, that's now Snowflake and the data cloud, solved it. I mean, it's-- The classic benefit of hindsight is 20/20, after years in the industry, they had seen these problems and said like, "How can we solve them? "Does the cloud let us solve these problems?" And the answer was, yes, but it did require writing everything from scratch and starting over with, because the architecture of the cloud just allows you to do things that you just couldn't do before. >> Yeah, I'm glad you brought up some of the originators of the data warehouse, because it really wasn't their fault, they were trying to solve a problem. It was the marketers that took it and really kind of made promises that they couldn't keep. But, the reality is when you talk to customers in the sort of the old EDW days, and this is the other thing I want to tap you guys' brains on, it was very challenging. I mean, and one customer one time referred to it as a snake swallowing a basketball. And what he meant by that is, every time there's a change, or Sarbanes-Oxley comes and we have to ingest all this new data. It's like aargh! It's just everything slows down to a grinding halt. Every time Intel came out with a new microprocessor they would go out and grab a new server as fast as they possibly could, he called it chasing the chips. And it was this endless cycle of pain. And so, the originators of the data warehouse, they didn't have the compute power, they didn't have the cloud. And so-- And of course they didn't have like 30, 40 years of pain to draw upon. But I wonder if you could maybe talk a little bit about the kinds of things that can be done now that we haven't been able to do here tofore. >> Well, yeah. I remember early on having a conversation with Bill about this idea of near real-time data warehousing and saying, "Is this real? "Is this something really people need?" And at the time, it was a couple of decades ago, he said, "No, to them, they just want to load their data "sooner than once a month." That was the goal. And they-- That was going to be near real-time for them. And, but now I'm seeing it with our customers. It's like, now we can do it. With things like the Kafka technology and Snowpipe in Snowflake, that people are able to get that refresh way faster and have near real-time analytics access to that data in a much more timely manner. And so it really is coming true. And the compute power that's there, as you said, we've now got this compute power in the cloud that we never dreamed of. I mean, you would think of only certain, very large, massive global companies or governments could afford supercomputers. And that's what it would have taken. And now we've got nearly the power of a super computer in our mobile device that we all carry around with us. So being able to harness all of that now in the cloud, is really opening up opportunities to do things with data and access data in a way that, again, really, we just kind of dreamed of before. Its like, we can democratize data when we get to this point. And I think that's where we are, we're at that inflection point, where now it's possible to do it. So the challenge on organizations is going to be how do we do it effectively? How do we do it with agility? And how do we do it in a governed manner? You mentioned Sarbanes-Oxley, GDPR, CCPA, all of those are out there. And so we have all of that as well. And so that's where we're going to get into it, ride us into the governance and being able to do that in a very quick, flexible, extensible manner. And Snowflakes really letting people do it now. >> Well, yeah. And again, we've been talking about Hadoop, and again, for all my fond thoughts of that era, and it's not like Hadoop is gone, but there was a lot of excitement around it, but governance was a huge problem. And it was kind of a bolt on. And now, Felipe I got to ask you, when you think about a company like Google, your former employer, data is at the core of their business. And so many companies, the data is not at the core of their business, something else is, it's a process or a manufacturing facility or whatever it is. And the data is sort of on the outskirts. We often talk about in stovepipes. And so we're now seeing organizations really, put data at the core of their... And it becomes central to their DNA. I'm curious as to your thoughts on that. And also, if you've got a lot of experience with developers, is there a developer angle here in this new data world? >> Oh, for sure. I mean, I love seeing every-- Like throughout my career at Google and my two months here, I'm talking to so many companies, that you never thought before, like these are database companies. But the ones that keep growing, the ones that keep moving to the next stage of their development is because they are focusing on data, they are adopting the processes, They are learning from it. And, me per-- I focus a lot on developers, so I mean, when I started this career as an advocate, first, I was a software engineer. And my work so far, has been... (mumbles) I really love talking to the engineers on the other companies, like... Maybe I'm not the one solving the business problem, but at the end of the day, when these companies have a business problem through out the world, they want to have data. There are other engineers that are scientists like me that are... That want to work for the company and bring the best technology to solve the problems. Yeah, for example, there's so much where data can help. If, as we evolve the systems for the company and also for us for understanding these systems, things like observability. And recently, there was a big company, a big launch on observability, on the company names of Cyberroam, where they are running all of their data warehousing needs and all of their data needs on Snowflake. Just because running these massive systems and being able to see how they're working, generates a lot of data. And then how do you manage it? How do you analyze it? Snowflake is ready there to help and support the two areas. >> It's interesting, my business partner, John Furrier, co-host of theCUBE, he said, gosh, I would say the middle of the last decade, maybe even around the time, 2013, when Snowflake was just coming out. He said... He predicted that data would be the new development kit. And, it's really at the center of a lot of the data life cycle, the-- What I call the data pipelines, I know people use that term differently. But, I'm very excited about the Data Cloud Summit and what we're going to learn there. And I get to interview a lot of really cool people. And so I appreciate you guys coming on. But Kent, who should attend the Data Cloud Summit? I mean, what are the-- What should they expect to learn? >> Well, as you said earlier Dave, there's so many tracks and there's really kind of something for everyone. So we've got a track on unlocking the value of the data cloud, which is really going to speak to the business leaders, as to what that vision is, what can we do from an organizational perspective with the data cloud to get them value from the data to move our businesses forward? But we've also got for the technicians, migrating to Snowflake. Training sessions on how to do the migration and modernizing your data lake, data science. How to do analytics with, and data science in Snowflake and in the data cloud. And even down to building apps, for the developers and building data products. So, we've got stuff for developers, we've got stuff for data scientists, we've got stuff for the data architects like myself and the data engineers, on how to build all of this out. And then there's going to be some industry solutions spotlights as well. So we can talk about different verticals, folks in FinTech and in healthcare, there's going to be stuff for them. And then for our data superheroes, we have a hallway track where we're going to get talks from the folks that are in our data superheroes, which is really our community advocacy program. So these are folks that are out there in the trenches using Snowflake, delivering value at their organizations. And they're going to talk down and dirty of how did they make this stuff happen? So there's going to be just really, something for everyone. Fireside chats with our executives, of course, something I'm really looking forward to myself. It's always fun to hear from Frank and Christian and Benoit, about what's the next big thing, what are we doing now? Where are we going with all of this? And then there is going to be some awards. We'll be giving out our Data Driver Awards for our most innovative customers. So there's going to be a lot for everybody to consume and enjoy and learn about this new space of the data cloud. >> Well, thank you for that Kent and I'll second that, and there's going to be a lot for everybody. If you're an existing Snowflake customer, there's going to be plenty of two of one content, where we can get in to the how tos and the best practice. If you're really not that familiar with Snowflake or you're not a customer, there's a lot of one-on-one content going on. If you're an investor and you want to figure out, "Okay, what is this vision? "And can, will this company grow into its massive valuation? "And how are they going to do that?" I think you're going to hear about the data cloud and really try to get a perspective and you can make your own judgment as to whether or not you think that it's going to be as large a market as many people think. So Felipe, I'd love to hear from you what people can expect at the Data Cloud Summit. >> Totally. So I would love to plus one to every one that Kent said, we have a phenomenal schedule that day, the executives will be there. But I really wanted to especially highlight the session I'm preparing with Trevor Noah. I'm sure you must have heard of him. And we are having him at the Data Cloud Summit, and we are going to have a session. We are going to talk about data. We are preparing a session that's all about how people that love data, that people that want to make that actionable, how can they bring storytelling and make it have more impact as he has well learned to do through his life. >> That's awesome. So, yeah, Trevor Noah, we're not just going to totally geek out here. We're going to have some great entertainment as well. So I want you to go to snowflake.com and click on Data Cloud Summit 2020. There's four geos. It starts on November 17th and then runs through the week and then the following week in Japan. So, check that out, we'll see you there. This is Dave Vellante for theCUBE. Thanks for watching. (upbeat music)

>> Hello everyone, and welcome back to theCUBEs coverage of the Snowflake Data Cloud Summit 2020. We're tracking the rise of the data cloud Sunny Bedi is here with me. He's the CIO and Chief Data Officer for Snowflake. Sunny, thanks for making the time today. Good to see you. >> Same here, Dave. Thanks for having me over. >> Yeah, so you're welcome. So before we get into it, I got to ask you, I mean, you recently left Nvidia to join Snowflake. I mean(chuckles) one of the few companies that are almost as hot as Snowflake, how come? >> Well, you know Dave I joined Nvidia 12 years ago. I was there for 12 years, when Nvidia was less than 2000 people company. And Nvidia have an unbelievable growth trajectory, and then from 2000 employees to 16,000, when I left in December of 2019. And Snowflake kind of provided the same opportunity to come in, and help scale the company. I thrive in an environment where I can be creative, I thrive in an environment where I can build things, I can scale things, I can grow things. And its been just a perfect opportunity to come and repeat that success over here. >> Awesome, Well we wish you the best. Talk about your role a little bit. I mean, it's like totally unique. I mean, especially in certain smaller organizations that have the same person, in the role of Chief Information Officer and Chief Data Officer, but, which are you? Are you more CIO, CDO, how do you balance that out? >> I would say that I'm both, to be an effective CIO, you need immersion with automation, you need immersion with data, you need immersion with security, and you also need immersion with compliance. So if all of these things are together, things are integrated. You have a cohesive way of handling all the pieces that come together. We believe if you keep them separated, you create silos and we definitely don't want silos. We want integration. We want seamless integration to drive and scale the company for future. >> I always felt-- >> So my time is balanced between both areas. >> I mean, I always felt like a lot of the CIOs I talked to, they'd love to get more involved in the data, but they're just too busy trying to keep the lights on. So, maybe what are your thoughts on the priorities of each hats CIO and CDO? >> Yeah, so look, I mean, I think because we're a full cloud company, we don't have anything on-prem. I don't have any workloads on-prem. we don't have a data center. I really don't have to worry about all the operational challenges that you have to deal with being an on-prem company. So the cycles that I can be involved from a transformation prospect, driving transformation for the company, both on the data side, as well as on the IT side. I have that cycles to invest that time and energy into both areas. Typically in a traditional company, which has not yet migrated towards the cloud, a major portion of their bandwidth gets wasted. CIOs bandwidth and IT professionals bandwidth gets wasted, in dealing with the operational challenges that you have in an on-prem environment. So having not to worry about that over here, it gives me all the cycles to be investing my time on both areas. >> Yeah, a lot of wasted IT labor over the decades. Let me ask you, how is running a data company? We were inside of a fast moving Silicon Valley Tech Company. What are the similarities and the differences from some of the customers? I mean, on the one hand, you're moving faster than your customers at least most of them, and you don't have the technical that you just described, CX on Nirvana. On the other hand, you're an example of what's possible. You can sort of set the best practice mark. How do you see that dynamic? >> So, in our firm world-class IT organization, it needs to be data-driven, it needs to be highly automated, it needs to enable world-class user experience, and then to secure and make the environment compliant resilient. The cloud platform that we have, inside Snowflake, allows us to achieve all of that. Now that is, an ideal situation to be in. But you don't have to deal with, all the on-prem type of workloads. So finding that balance is what we're going after. And, however this is a journey, right. For other companies who are not on the cloud, its a journey. They have to prioritize that. They have to start moving things to the cloud, and that's where we are different and similar, right. We're different that we don't have to worry about that. Everything is in the cloud for us. And then, that's kind of how we see it. >> So, you know, used to call it the dogfooding segment, but Oliver Bussmann was the CIO of SAP. So no, no, Dave, we call it drinking your own champagne. (laughs) which is how you guys are referring to it. But, sometimes still in such situations you're (laughs) inside the sausage factory, which is good in a way because you see it before it goes into production. But, so what's your journey with, with Snowflake been like? >> Yeah, so that's a really good question. That's a major portion of what I do at work. And, let's start with the first principles of we believe, that we want to measure everything in the company, that's important for companies performance. If we measure the right things, we believe we can drive the best outcomes. We are driven through those first principles and we leveraged our business applications, our data, our security, our automation, and our compliance to integrate with our product to power, all these use cases and workloads. In our own environment, we call that snow house. Which is nothing but a Snowflake instance. So, for all the new products that we are coming into market with, we work very closely with the engineering team, with the product management team, to make sure that we actually become customer zero, and try to use as much functionality of that, inside our own enterprise and give as much feedback to our engineering and our product management teams, so that they can make the customer one experience to be world-class. So that's kind of in a nutshell how we go to market with those products. >> So you're customer zero. So all the product guys that they suck up to you, or are they afraid of you? (laughs) >> Well, I think it's a very neutral, beneficial relationship. So, they know that my team's feedback, is important to how they are kind of shaping up the product, and it's just not necessarily IT, right. We have folks in finance, folks in sales, marketing, everybody is drinking the champagne, right. And IT and the data team actually enabled that deployment, but the use cases are pretty much in the entire enterprise of the company in every aspect of it. Well you know-- >> Including security. >> Well, that's what we say. We always talk about alignment, but it's like, it's almost alignment by design, as opposed to being this forced thing. I'm interested in this, sort of Snowflake on Snowflake concept that you guys talk about. What were your objectives going in and maybe thinking about the outcomes, what did you expect? Did you work backwards from that? What were you trying to achieve? >> Yeah, I mean, look again back to the first principles. We believe we want to measure everything that's important to our business. That will drive the right outcomes. We then layer the application layer. We then overlay the business process layer. We then overlay the compliance and security layer. And the end result really is operationalizing Snowflake internally to drive our business, making the right choices, right decisions for the company. So we have a ton of use cases that are just ideal, using Snowflake on Snowflake. You know I can give you some examples of that if you like, >> Yes. >> But, >> Go on please. >> Security being one of the biggest use cases. We use the entire monitoring and remediation work that goes in the security compliance world, all through Snowflake. And we are finding real time events through data sharing, with our key suppliers. And we're ensuring that we're protecting our environment as much as possible with that whole infrastructure. >> You talked about layering, governance, security, et cetera. Yeah (laughs) I'm imagining a coat of primer paint in a nice and smooth over, it's not a bolt-on. I want to press you on that, because it can't be an afterthought. And what you're describing is much more of a modern approach. And I want you to totally differentiate between the layers that you talked about and what you've surely seen in your experience over the years as a bolt-on, what's the difference? >> Well, I mean the security wall, there's a lot of data, and a lot of the data that is critical to your environment. You want to make sure it is fully complete, you're getting it in the right hands, in the right platform to understand that, and doing the correlation work that needs to happen real time. Our platform allows all that data to be ingested and real time and anything that is suspicious, that's being out there. We're finding that stuff in real time. The monitoring has to be real time. And if there is an event, somebody needs to take an action real time. So the platform allows it to integrate altogether. And basically, the suppliers that we're using are also doing data sharing with us on this platform. So it makes the whole security remediation to be really really fantastic experience. >> Well I think too, I'd to share often with my audience when I talk to practitioners that are using Snowflake they, surprising to me when I first heard this, they said, "Well we choose Snowflake as the security," and I went, what! But the simplicity and the workflow is simpler, and it just means less human labor involved in setting these things up. So I wonder if you could talk about the team that you put together, the culture that you're building, and what's the makeup look like? >> Sure, so are you specifically asking about the characteristics of how we're building up the culture? >> Yeah, absolutely. >> Okay, so I think we're looking for, obviously very much high energy folks, people who have, high accountability, they're data-driven. We want to measure everything that's important to us. We're looking for folks who have situational awareness, and then finally high sense of urgency. I think all of these elements, allows IT organization to be integrated with the business. In large traditional companies, IT organizations kind of disintegrate with the business. We want to integrate with the business, to drive the best outcomes that are needed for the company. >> I Want to ask you about some of your favorite use cases, but you mentioned measurement. How do you measure? What are you measuring? >> Sure, so I would say that, let's just take security. Cause we talked about security. Let's just use security as a use case. So in security, there are many different frameworks, as you may know, right. There is the NIST framework, there is the CIS framework, there is an ISO framework. We have adopted towards a CIS framework inside Snowflake. That framework has 20 controls and that 20 controls has another 20 sub-controls. So we're talking about 400 controls potentially. Not every control is applicable to us, but majority of them are. And so for every control, there is a source of data, that's being ingested in Snowflake. I'll give you an example of that is asset management. So, asset management for end points, asset management for our servers, or asset management for our network gear. All of that data gets ingested inside Snowflake. We measure that. We can tell you exactly how many end points I have. I can tell you exactly when an employee gets onboarded, what laptop we have given them, when the employee leaves the company, I'll be collecting that laptop back on time, I'll be revoking all that access. That's part of CIS Control 1 as an example, and we're measuring all of that. And I can tell you exactly at my real time inside Snowflake. How effective I am for that specific control. That's just an example of that Dave. Now imagine 400 of these items that make up the whole security CIS framework. You want to measure everything on that 400 controls or 400 sub-controls. And you want to make sure that if any of that control is not being managed properly, you're alerted about it and you're remediating it to prevent a security issue that may pop up. >> Awesome, visibility and automation component. Are you a CSO too Sunny? We don't really have that title. We don't really have a CSO title, but I do wear a security hat as well. It's actually a joint responsibility between... I manage the corporate security. The product security is inside the product team, but we use the same common framework. We use the same common telemetry. We use the same common methodology. Incident management response teams are very similar, and it's all powered through a Snowflake. >> Awesome. Sunny Bedi you're great guests, I would imagine the sales guys love dragging you on zooms these days to sales calls, just to (laughs) share best practice, but love to have you back and continue the conversation. Sunny Bedi, really appreciate your time. Thank you. >> Thank you Dave. Thank you very much. >> All right, keep it right there everybody. We'll be right back with our next guest, right after this short break.

>> 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)