 with me are three amazing guest panelists. What are the things that we can do today with data that we say weren't able to do maybe five years ago? Yes, certainly. I think there's lots of things that we can integrate specific actions, but if you were to zoom out and look at the big picture, our ability to reason through data, to inform our choices with data is bigger than ever before. There are still many companies that have to decide to sample data or to throw away all their data, or they don't have the right data from external companies to put their decisions and actions in context. Now we have the technology and the platforms to bring all that data together, tear down silos and look at 360 of a customer or entire action. So I think it's reasoning through data that has increased the capability of organizations dramatically in the last few years. So my line, when I was a young pup at IDC, I started the storage program there many, many moons ago. And so I always pay attention to what's going on in storage, back in my mind. And S3 people forget sometimes, that was actually the very first cloud product announced by AWS, which really ushered in the cloud era. And that was 2006, and fundamentally changed the way we think about storing data. I wonder if you can explain how S3 specifically in an object storage generally, would get put really transformed storage from a blocker to an enabler of some of these new workloads that we're seeing. Absolutely. I think it has been transformational for many companies in every industry. And the reason for that is because in S3, you can consolidate all the different datasets that today are scattered around so many companies, different data centers. And so if you think about it, S3 gives the ability to put unstructured data, which are video recordings and images. It puts semi-structured data, which is your CSV file, which every company has lots of. And it has also support for structured data types like Parquet files, which drive a lot of the business decisions that every company has to make today. And so if you think about S3, which launched on Pi Day in March of 2006, S3 started off as an object store, but it has evolved into so much more than that where companies all over the world in every industry are taking those different datasets. They're putting it in S3. They're growing their data and then they're growing the value that they capture on top of that data. And that is the separation we see that Snowflake talks about and many of the pioneers across different industries talk about, which is a separation of the growth of storage and the growth of your compute applications. And what's happening is that when you have a place to put your data like S3, which is secure by default and has the availability and the durability and the operational profile you know and can trust, then the innovation of the application developers really take over. And one example of that is where we have a customer and the financial sector and they started to use S3 to put their customer care recordings and they were just using it for storage because that obviously dataset grows very quickly. And then somebody in their fraud department got the idea of doing machine learning on top of those customer care recordings. And when they did that, they found really interesting data that they could then feed into their fraud detection models. And so you get this kind of alchemy of innovation that happens when you take the datasets of today and yesterday and tomorrow, you put them all in one place, which is S3. And the innovation of your application developers just takes over and builds not just what you need today but what you need in the future as well. Thank you for that. Mark, I want to bring you into this panel. It's great to have you here. So thank you. I mean, Tableau has been a game changer for organizations. I remember my first Tableau conference, passionate customers and really bringing the cloud-like agility and simplicity to visualization just totally changed the way people thought about data and met with massive data volumes and simplified access. And now we're seeing new workloads that are developing on top of data and snowflake data and the cloud. Can you talk about how your customers are really telling stories and bringing to life those stories with data on top of things like S3, which Mylon was just talking about. Yeah, for sure. Building on what Christian and Mylon have already said, our mission at Tableau has always been to help people see and understand data. And you look at the amazing advances that are happening in storage and data processing. And now the data that you can see and play with is so amazing, right? Like at this point in time, it's really nothing short of a new microscope or a new telescope that really lets you understand patterns that were always there in the world that you literally couldn't see them because of the limitations of the amount of data that you could bring into the picture because of the amount of processing power and the amount of sharing of data that you could bring into the picture. And now, like you said, these three things are coming together, this amazing ability to see and tell stories with your data combined with the fact that you've got so much more data at your fingertips, the fact that you can now process that data, look at that data, share that data in ways that was never possible. Again, I'll go back to that analogy. It feels like the invention of a new microscope, a new telescope, a new way to look at the world and tell stories and get to insights that were just, were never possible before. So thank you for that. And Christian, I want to come back to this notion of the data cloud. And, you know, it's a very powerful concept. And of course it's good marketing, but I wonder if you could add some additional color for the audience. I mean, what more can you tell us about the data cloud, how you're seeing it evolving and maybe building on some of the things that Mark was just talking about, just in terms of, you know, bringing this vision into reality? Certainly. Yeah, and the data cloud for sure is bigger and more concrete than just the marketing value of it. The big insight behind our vision for the data cloud is that just the technology capability, just a cloud data platform is not what gets organizations to be able to be data driven, to be able to make great use of data or be highly capable in terms of data ability. The other element beyond technology is the access and availability of data to put their own data in context or enrich based on the knowledge or data from other third parties. So the data cloud, the way to think about it is the combination of both technology, which for Snowflake is our cloud data platform and all the workloads, the ability to do data warehousing and queries and speeds and feeds fit in there and data engineering, et cetera. But it's also how do we make it easier for our customers to have access to the data they need or they could benefit to improve the decisions for their own organizations. I think of the analogy of a set-top box. I can give you a great, technically set-top box, but if there's no content on the other side, it makes it difficult for you to get value out of it. That's how we should all be thinking about the data cloud. It's technology, but it's also seamless access to data. And my luck, can you give us a sense of the scope and what kind of scale are you seeing with Snowflake on AWS? Well, Snowflake has always driven, as Christian knows, a very high transaction rate to S3. And in fact, when Christian and I were talking just yesterday, we were talking about some of the things that have really been remarkable about the long partnership that we've had over the years. And so I'll give you an example of how that evolution has really worked. So as you know, S3 has the first AWS service that's launched and we have customers who have petabytes, hundreds of petabytes and exabytes of storage on S3. And so from the ground up, S3 has been built for scale. And so when we have customers like Snowflake that have very high transaction rates for requests for S3 storage, we put our customer hat on and we ask customers like Snowflake, how do you think about performance? Not just what performance do you need, but how do you think about performance? And when Christian and his team were walking through the demands of making requests to their S3 data, they were talking about some pretty high spikes over time and just a lot of volume. And so when we built improvements into our performance over time, we put that hat on for where Snowflake was telling us what they needed. And then we built our performance model not around a bucket or an account. We built it around a request rate per prefix because that's what Snowflake and other customers told us they needed. And so when you think about how we scale our performance, we scale it based on a prefix and not a bucket or an account which other cloud providers do. We do it in this unique way because 90% of our customer roadmap across AWS comes from customer requests and that's what Snowflake and other customers were saying is that, hey, I think about my performance based on a prefix of an object and not some arbitrary semantic of how I happen to organize my buckets. I think the other thing I would also throw out there for scale is as you might imagine, S3 is a very large distributed system. And again, if I go back to how we architected for our performance improvements, we architected in such a way that a customer like Snowflake can come in and they could take advantage of horizontally scaling. They can do parallel data retrievals and puts and gets for your data. And when they do that, they can get tens of thousands of requests per second because they're taking advantage of the scale of S3. And so, when we think about scale, it's not just scale, which is the growth of your storage which every customer needs. IDC says that digital data is growing at 40% year over year. So every customer needs a place to put all of those storage sets that are growing. But the way we also have worked together for many years is this, how can we think about how Snowflake and other customers are driving these patterns of access on top of the data? Not just the elasticity of the storage, but the access. And then how can we architect often very uniquely as I talked about with our request rate in such a way that they can achieve what they need to do not just today but in the future? I don't know, you three companies here that don't often take their customer hats off. Mark, I wonder if we could come to you. During the data cloud summit, we've been exploring this notion that innovation in technology is really evolved from point products, the next generation of server or software tool to platforms that made infrastructure simpler or called functions. And now it's evolving into leveraging ecosystems, the power of many versus the resources of one. So my question is, how are you all collaborating and creating innovations that your customers can leverage? Yeah, for sure. So certainly, Tableau and Snowflake kind of were dropped at natural partners from the beginning, right? Like putting that visualization engine on top of Snowflake to combine that processing power on data and the ability to visualize it was obvious. As you talk about the larger ecosystem, now of course Tableau is part of Salesforce. And so there's a much more interesting story now to be told across the three companies, one and two and a half maybe, as we talk about Tableau and Salesforce combined together of really having this full circle of Salesforce, with this amazing set of business apps that so much value for customers and getting the data that comes out of those Salesforce applications, putting it into Snowflake so that you can combine that, share that, process it, combine it with data, not just for across Salesforce, but from your other apps in the way that you want and then put Tableau on top of it. Now you're talking about this amazing platform ecosystem of data coming from your most valuable business applications in the world with the most sales opportunity objects, marketing, service, all of that information flowing into this flexible data platform and then this amazing visualization platform on top of it. And there's really no end of the things that our customers can do with that combination. Christian, we're out of time, but I wonder if you could bring us home and I want to end with, let's say some people here, maybe they're still struggling with the cumbersome nature, let's say they're on prem data, warehouses, the kids just unplug them because they rely on them for certain things like reporting, but let's say they want to raise the bar in their data and analytics. What would you advise for the next steps for them? Yeah, I think the first part or first step to take is around embrace the cloud and the promise and the abilities of cloud technology. There's many studies where relative to peers, companies that are embracing data are coming out ahead and outperforming their peers. And with traditional technology, on prem technology, you ended up with proliferation of silos and copies of data. And a lot of energy went into managing those on prem systems and making copies and data governance and security. And cloud technology and the type of platform that Snowflake has brought to market enables organizations to focus on the data, the data model, the data insights, and not necessarily on managing the infrastructure. So I think that would be the first recommendation from our end, embrace cloud, get into a modern cloud data platform, make sure that you're spending your time on data, not managing infrastructure and seeing what the infrastructure lets you do. Okay, this is Dave Vellante for theCUBE. Thank you for watching. Keep it right there with more great content coming your way.