 And welcome back to theCUBE, everyone. I'm John Walls, continuing our coverage here of AWS ReInvent 22, where part of the AWS startup showcases the global startup program that AWS so proudly sponsors and with us to talk about what they're doing now in the AWS space. Your Sean Knapp, who's the CEO of AscendIO. And Sean, good to have you here with us. We appreciate it. Thanks for having me, John. Yeah, thanks for the time. First off, I've got to show the t-shirt. You caught my attention. Big data is a cluster. I don't think you get a lot of argument from some folks, right? But it's your job to make some sense of it, is it not? Tell us about AscendIO. Sure, AscendIO is a data automation platform. What we do is connect a lot of the disparate parts of what data teams do when they create ETL and EOT data pipelines. And we use advanced levels of automation to make it easier and faster for them to build these complex systems. And have there will be a little bit less of a cluster. All right, so let's get in automation a little bit then. Again, I mean, your definition of automation and how you're applying it to your business case. Absolutely, you know, what we see oftentimes is as spaces mature and evolve, the number of repetitive and repeatable tasks that actually become far less differentiating, but far more taxable, if you will, to the business, start to accumulate as those common patterns emerge. And as we see standardization around tech stacks, like on Amazon and on Snowflake and on Databricks. And as you see those patterns really start to formalize and standardize, it opens up the door to basically not have your team have to do all those things anymore and write code or perform the same actions that they used to always have to. And you can lean more on technology to properly automate and remove the monotony of those tasks and give your teams greater leverage. All right, so let's talk about at least, maybe you're the journey, say, in the past 18 months, in terms of automation and what have you seen from a trend perspective and how are you trying to address that in order to meet that need? Yeah, I think the last 18 months have become really exciting as we've seen both a very exciting boom and bust cycle that are driving a lot of other macro behaviors. What we've seen over the last 18 months is far greater adoption of the standard, what we call the data planes, the architectures around Snowflake and Databricks and Amazon, and what that's created as a result is the emergence of what I would call as the next problem. As you start to solve that category, I've had to get- It always works too, isn't it? Yeah, exactly. It always works. This is the wonderful thing about technology is the job security of there's always the next problem to go solve. That's what we see is, as we go into cloud, we get that infinite scale, infinite capacity, infinite flexibility, and without these modern now data platforms, we get that infinite ability to store and process data incredibly quickly with incredible ease. And so what do most organizations do? You take a ton of new bodies, all the people who wanted to do those really cool things with data, and you're like, okay, now you can. So you start throwing a lot more use cases, you start creating a lot more data products, you start doing a lot more things with data, and this is really where that third category starts to emerge, which is, you get this data mess. Not mesh, but a data mess. You get a cluster, exactly, where the complexity skyrockets, and as a result, that rapid innovation that you are all looking for and promised, just comes to a screeching halt, as you're just trying to swim through molasses. And as a result, this is where that new awareness around automation starts to really heighten. You know, we did a really interesting survey at the start of this year. Did it as a blind survey, independent third party, surveyed 500 chief data officers, data scientists, data architects, and asked them a plethora of questions. But one of the questions we asked them was do you currently, or do you intend on investing in data automation to increase your team's productivity? And what was shocking, and I was very surprised by this, what was shocking was only three and a half percent said they do today, which is really interesting because it really hones in on this notion of automation is beyond what a lot of us think of, you know, tooling and enhancements today. Only three and a half percent today had it. But 88.5% said they intend on making data automation investments in the next 12 months. And that stark contrast of how many people have a thing and how many people want that benefit of automation. I think it is incredibly critical as we look to 2023 and beyond. I mean, it just seems like a no brainer. Does it not? I mean, no, it's your business. So of course you agree with me. But of course, what a brilliant statement. But it is, it seems like, you know, the more you're able to automate certain processes and then free up your resources and your dollars to be spent elsewhere and your human capital, you know, to be invested elsewhere, that just seems to be a layup. I'm really, I'm very surprised by that three and a half percent figure. I was too. I actually was expecting it to be higher. I was expecting five to 10% as there's other tools in the marketplace around ETL tools or orchestration tools that some would argue fit in the automation category. And I think what the market is telling us based on that research is that those in themselves don't qualify as automation, that the market has a larger vision for automation, something that is more metadata driven, more AI back that takes us a greater leap and of leverage for the teams than what the existing capabilities in the industry today can afford. So if you got this big leap that you can make, but maybe, you know, should sites be set a little lower? Are you in danger of creating too much of an expectation or too much of a false hope? Because, you know, I mean, sometimes incremental increases are okay. I agree. I think the, you know, I think you want to do a little bit of both. I think you want to have a plan for reaching for the stars and you got to be really pragmatic as well. Even inside of a Sundio, we actually have a core value, which is build for 10X, plan for 100X. And so know where you're going, but solve the problems that are right in front of you today as you get to that next scale. And I think the really important part for a lot of companies is how do you think about what that trajectory is and be really smart around where you choose to invest? As you wanted the things that we have is last year's innovation is next year's anchor around your neck. And that's because we're in this very fortunately, so this really exciting, rapidly moving, innovative space. But the thing that was your advantage, not too long ago is everybody can move so quickly, now it becomes commonplace, and a year or two later, if you don't jump on whatever that next innovation is that the industry starts to standardize on, you're now on hook paying massive debt and paying, you know, you thought you had home mortgage debt and now you're paying the worst of credit card debt, trying to pay that down and maintain your velocity. It's a whole different kind of FOMO, right? I'm fairly missing out on that. What am I missing out on with the next big thing? Exactly. We've been missing out on that. So we encourage a lot of folks, as you think about this, and as it pertains to automation too, is you solve for some of the problems right in front of you, but really make sure that you're designing the right approach that as you stack on, you know, five times, 10 times as many people building data products and your volume and library of data weaving throughout your business. Make sure you're making those right investments. And that's one of the reasons why we do think automation is so important and really this next generation of automation, which is a metadata and AI backed level of automation that can just achieve and accomplish so much more than sort of traditional norms. Yeah, on that, like as far as Dexterine goes, what do you think is going to be possible that cloud sets the stage for that maybe not too long ago seemed really out of reach? Like what's going to give somebody to work on that 88% in there that's going to make their spin come your way? Good question. So I think there's a couple of fold. You know, I think the, right now we see two things happening. You know, we see large movements going to the dominant data platforms today. And you know, frankly, one of the biggest challenges we see people having today is just how do you get data in? Which is insanity to me because that's not even the value extraction. That is the cost center piece of it. Just get data in so you can start to do something with it. And so I think that becomes a huge hurdle. But the access to new technologies, the ability to start to unify more of your data and in rapid fashion, I think is really important. I think as we start to invest more in this metadata backed layer that can connect those notions of how do you ingest your data? How do you transform it? How do you orchestrate it? How do you observe it? One of the really compelling parts of this is metadata does become the new big data itself. And so to do these really advanced things, to give these data teams greater levels of automation and leverage, you actually need cloud capabilities to process large volumes of not the data but the metadata around the data itself to deliver on these really powerful capabilities. And so I think that's why this new world that we see of the developer platforms for modern data cloud applications actually benefit from being a cloud native application themselves. So before you take off, talk about the AWS relationship. Part of the startup showcase, start part of the growth program. And we've talked a lot about the cloud, what it's doing for your business. But let's just talk about, again, how integral they have been to your success. And likewise, what you think, maybe you bring to their table too. Yeah, well we bring a lot to the table. Absolutely, I had no doubt about that. I mean, honestly, working with AWS has been truly fantastic. You know, I think as a startup that's really growing and expanding your footprint, having access to the resources in AWS to drive adoption, drive best practices, drive awareness is incredibly impactful. I think, you know, conversely too, the value that Ascend provides to the AWS ecosystem is tremendous leverage on onboarding and driving faster use cases, faster adoption of all the really great, cool, exciting technologies that we get to hear about. By bringing more advanced layers of automation to the existing product stack, we can make it easier for more people to build more powerful things faster and safely, which I think is what most businesses at ReInvent really are looking for. It's win-win. Win-win. Yeah, that's for sure. Sean, thanks for the time. Thank you, John. Good job on the t-shirt and keep up the good work. Thank you very much. I appreciate that. Sean Knapp joining us here on the AWS startup program, part of there of the startup showcase. We are, of course, on theCUBE. I'm John Walls, we're at the Venetian in Las Vegas and theCUBE, as you well know, is the leader in high tech coverage.