 Welcome back to SuperCloud 2. You know, this event and the SuperCloud initiative in general, it's an open industry wide collaboration. Last August at SuperCloud 22, we really honed in on the definition, which of course we've published. And there's this shared doc, which folks are still adding to and refining effect just recently, Dr. Nehlu Mihai added some critical points that really advance some of the community's initial principles. And today at SuperCloud 2, we're digging further into the topic with input from real world practitioners. And we're exploring that intersection of data, data mesh and cloud and importantly, the realities and challenges of deploying technology to drive new business capability. And I'm pleased to welcome Ash Naseer to the program. He's a senior director of data engineering at Warner Brothers. Discovery, Ash, great to see you again. Thanks so much for taking time with us. It's great to be back. These conversations are always very fun. I was so excited when we met last spring, I guess. And so before we get started, I wanted to play a clip from that conversation. It was June, it was at the Snowflake Summit in Las Vegas. And it's a comment that you made about your company, but also data mesh, data mesh. Guys, roll the clip. Yeah, so when people think of Warner Brothers, you always think of like the movie studio, but we're more than that, right? I mean, you think of HBO, you think of TNT, you think of CNN. We have 30 plus brands in our portfolio and each have their own needs. So the idea of a data mesh really helps us because what we can do is we can federate access across the company so that CNN can work at their own pace. When there's election season, they can ingest their own data and they don't have to bump up against, as an example, HBO, if Game of Thrones is going on. So, okay, so that's pretty interesting. So you've got these sort of different groups that have different data requirements inside of your organization. The data mesh, it's a relatively new concept. So you're kind of ahead of the curve. So Ash, my question is, when you think about getting value from data and how that's changed over the past decade, you had pre-Hadoop, Hadoop, what do you see that's changed? Now you've got the cloud coming in. What's changed, what's had to be sort of fixed? What's working now and where do you see it going? Yeah, so I feel like in the last decade, we've come through quite a maturity curve. I actually like to say that we're in the golden age of data because the tools and technology in the data space, particularly and then broadly in the cloud, they allow us to do things that we couldn't do way back when like you suggested back in the Hadoop era or even before that. So there's certainly a lot of maturity and a lot of technology that has come about. So in terms of the good, bad and ugly, so let me kind of start with the good, right? In terms of bringing value from the data, I really feel like we're in this place where the folks that are charged with unlocking that value from the data, they're actually spending the majority of their time actually doing that. And what do I mean by that? If you think about it 10 years ago, the data scientist was the person that was gonna sort of solve all of the data problems in a company, but what happened was companies asked these data scientists to come in and do a multitude of things. And what these data scientists found out was they were spending most of their time on really data wrangling and less on actually getting the value out of the data. And in the last decade or so, I feel like we've made the shift and we realized that data engineering, data management, data governance, those are as important practices as data science which is sort of getting the value out of the data. And so what that has done is it has freed up the data scientist and the business analyst and the data analyst and the BI expert. So to really focus on how to get value out of the data and spend less time wrangling data. So I really think that that's the good. In terms of the bad, I feel like there's a lot of legacy data platforms out there. And I feel like there's gonna be a time where we'll be in that hybrid mode. And then the ugly, I feel like with all the data and all the technology creates another problem of itself because most companies don't have arms around their data and making sure that they know who's using the data, what they're using for and how can sort of the company leverage the collective intelligence. That is a bigger problem to solve today than 10 years ago. And that's where technologies like the data mesh come in. Yeah, so when I think of data mesh and I say you're an early practitioner of data mesh, you mentioned legacy technologies. The concept of data mesh is inclusive. You know, in theory anyway, you're supposed to be including the legacy technologies, whether it's a data lake or data warehouse or Oracle or Snowflake or whatever it is. And when you think about Jamak Degani's principles, domain-centric ownership, data as product, and that creates challenges around self-serve infrastructure and automated governance. And then when you start to combine these different technologies, you got legacy, you got cloud, everything's different. And so you have to figure out how to deal with that. So my question is, how have you dealt with that and what role has the cloud played in solving those problems, in particular that self-serve infrastructure and that automated governance? Where are we in terms of solving that problem from a practitioner standpoint? Yeah, I always like to say that data is a team sport and we should sort of think of it as such. And that's, I feel like the key of the data mesh concept is treating it as a team sport. A lot of people ask me, they're like, oh, hey, Ash, I've heard about this thing called data mesh. Where can I buy one? Or what's the technology that I use to get a data mesh? And the reality is that there isn't one technology, you can't really buy a data mesh. It's really a way of life. It's how organizations decide to approach data. Like I said, back to the team sport analogy, making sure that everyone has the seat on the table, making sure that we embrace the fact that we have a lot of data, we have a lot of data problems to solve. And the way we'll be successful is to make everyone inclusive. You think about the old days, I mean, data silos or shadow IT, some might call it. That's been around for decades. And what hasn't changed was this notion that, hey, everything needs to be sort of managed centrally. But with the cloud and with the technologies that we have today, we have the right technology and the tooling to democratize that data and democratize not only just the access, but also sort of building blocks and sort of taking building blocks which are relevant to your product or your business and adding to the overall data mesh. We've got all that technology. The challenge is for us to really embrace it and make sure that we implement it from an organizational standpoint. So thinking about super cloud, there's a layer that lives above the clouds and adds value. And you think about your brands, you got 30 brands, you mentioned shadow IT. If, let's say one of those brands, HBO or TNT, whatever, they want to go, they, hey, we really like Google's analytics tools and they maybe go off and build something. I don't know if that's even allowed. Maybe it's not. But then you build this data mesh. My question is around multi-cloud, cross-cloud, super cloud, if you will. Is that an advantage for you as a practitioner or is that just make things more complicated? I really love the idea of multi-cloud. I think it's great. I think that it should have been the norm, not the exception. I feel like, you know, people talk about it as if it's the exception. That should have been the case. I will say though, I feel like multi-cloud should evolve organically. So back to your point about some of these different brands and different brands or different business units or even in a merger and acquisition situation where two different companies or multiple different companies come together with different technology stacks. I feel like that's an organic evolution and making sure that we use the concepts and the technologies around the multi-cloud to bring everyone together. That's where we need to be. And again, it talks to the fact that each of those business units and each of those groups have their own unique needs. And we need to make sure that we embrace that and we enable that rather than stifling everything. Now where I have a little bit of a challenge with the multi-cloud is when technology leaders try to build it by design. So there's a notion there that, hey, you need to sort of diversify and don't put all your eggs in one basket. And so we need to have this multi-cloud thing. I feel like that is just sort of creating more complexity where it doesn't need to be. We can also simplify our lives but where it evolves organically, absolutely. I think that's the right way to go. So Ash, if it involves organically, don't you need some kind of cloud interpreter to create a common experience across clouds? Does that exist today? What are your thoughts on that? There is a lot of technology that exists today and that helps go between these different clouds. A lot of these sort of cloud agnostic technologies that you talked about, the snowflakes and the day breaks and so forth of the world, they operate in multiple clouds. They operate in multiple regions within a given cloud and multiple clouds. So they span all of that and they have the tools and technology. So I feel like the tooling is there. There does need to be more of an evolution around the tooling and I think the market's need are going to dictate that. I feel like the market is there, they're asking for it. So there's definitely going to be that evolution but the technology is there. I think just making sure that we embrace that and we sort of embrace that as a challenge and not try to sort of shut all of that down and box everything into one. What's the biggest challenge? Is it governance or security or is it more, like you're saying, adoption, cultural? I think it's a combination of cultural as well as governance. And so the cultural side I talked about, right? Just making sure that we give these different teams a seat at the table and they actually bring that technology into the mix and we use the modern tools and technologies to make sure that everybody sort of plays nice together. That is definitely, we have ways to go there. But then in terms of governance, that is another big problem that most companies are just starting to wrestle with because like I said, I mean, the data silos and shadow IT that's been around there, right? The only difference is we're now sort of bringing everything together in a cloud environment. The collective organization has access to that and now we just realized, oh, we have quite a data problem at our hands. So how do we sort of organize this data? Make sure that the quality is there, the trust is there. When people look at that data, a lot of those questions are now coming to the forefront because everything is sort of so transparent with the cloud, right? And so I feel like, again, putting in the right processes and the right tooling to address that is gonna be critical in the next years to come. Is sharing data across clouds something that adds, is valuable to you or even within a single cloud, being able to share data? And my question is not just within your organization, but even outside your organization. Is that something that has sort of hit your radar? Is it mature or is that something that really would add value to your business? Data sharing is huge and again, this is another one of those things which isn't new. I remember back in the 90s when we had to share data externally with our partners or vendors, they used to physically send us stacks of these tapes or sort of physical media on some truck. And we've evolved since then, right? I mean, it went from that to sharing files online and so forth, but data sharing as a concept and as a concept which is now very frictionless through these different technologies that we have today, that is very new. And that is something, like I said, it's always been going on, but that needs to be really embraced more as well. We as a company heavily leverage data sharing between our own different brands and business units, that helps us make that data mesh so that, when a CNN as an example builds their own data model based on election data and the kinds of data that they need, compare that with other data in the rest of the company, sports, entertainment and so forth and so on. Everyone has their unique data, but that data sharing capability brings it together wherever there is a need. So you think about having a Tiger Woods documentary as an example on HBO Max and making sure that you reach the audiences that are interested in golf and interested in sports and so forth, right? That all comes through the magic of data sharing. So it's really critical internally for us and then externally as well, because just understanding how our products are doing on our partner's networks and different distribution channels, that's important. And then just understanding how our consumers are consuming it off properties, right? I mean, we have brands that transcend just the screen, right? We have a lot of physical merchandise that you can buy in the store. So again, understanding who's buying the Batman action figures after the Batman movie was released, that's another critical insight. So it all gets enabled through data sharing and something we rely heavily on. So I wonder if I get your perspective on this. So I feel like the nirvana of data mesh is if I want to use Google BigQuery, Oracle Database, or Microsoft Database, or Snowflake Databricks, Amazon, whatever, that that's a node on the mesh. And the perfect world, you can share that data can be governed and I don't think we're quite there today. So, but within a platform, maybe it's within Google or within Amazon or within Snowflake or Databricks, if you're in that world, maybe even Oracle, you actually can do some levels of data sharing, maybe greater with some than others. Do you mandate as an organization that you have to use this particular data platform or are you saying, hey, we are architecting a data mesh for the future where we believe the technology will support that or maybe you've invented some technology that supports that today. Can you help us understand that? Yeah, I always feel like mandate is a strong area and that breeds the shadow IT and the data silos. So we don't mandate, we do make sure that there's a consistent set of governance rules, policies and tooling that's there so that everyone is on the same page. However, at the same time, our focus is really operating in a federated way. That's been our solution, right? Is to make sure that we work within a common set of tooling, which may be different technologies, which in some cases may be different clouds, although we're not that multi-cloud. So what we're trying to do is making sure that everyone who has that technology already built as long as it sort of follows certain standards, it's modern, it has the capabilities that will eventually allow us to be successful and eventually allow for that data sharing amongst those different nodes as you put it, as long as that's the case and as long as there's a master governance layer where we know where all that data is and who has access to what and we can sort of be really confident about the quality of the data as long as that case, our approach to that is really that federated approach. So did I hear you correctly? You're not multi-cloud today? Yeah, that's correct. There are certain spots where we use that but by and large, we rely on a particular cloud and that's just been, like I said, it's been the evolution, it was our evolution. We decided early on to focus on a single cloud and that's the direction we've been going in. So do you want to go to a multi-cloud or do you feel like you mentioned organic before? If a business unit wants to go there, as long as they're adhering to those standards that you put out, maybe recommendations, that that's okay, I guess my question is, does that bring benefit to your business that you'd like to tap or do you feel like it's not necessary? I'll go back to the point of, if it happens organically, we're going to be open about it. Obviously we'll have to look at every situations, not all clouds are created equal as well. So there's a number of different considerations but by and large, when it happens organically, the key is time to value, right? How do you quickly bring those technologies in as long as you could share the data, they're interconnected, they're secured, they're governed, we are confident on the quality, as long as those principles are met, we could definitely go in that direction but by and large, I mean, we're sort of evolving in a singular direction, but even within a singular cloud, we're a global company and we have audiences around the world, so making sure that even within a single cloud, those different regions interoperate as one, that's a bigger challenge that we're having to solve as well. Last question, kind of to the future of data and cloud, how it's going to evolve, do you see a day when companies like yours are increasingly going to be offering your data, their software services and becoming more of a technology company, sort of pointing your tooling and your proprietary knowledge at the external world, as an opportunity, as a business opportunity? That's a very interesting concept and I know companies have done that and some of them have been extremely successful, I mean, Amazon is the biggest example that comes to mind, right? When they launched AWS, something that they had that expertise they had internally and they offered it to the world as a product, but by and large, I think it's gonna be far and few between, especially it's gonna be focused on companies that have technology as their DNA or almost like in the technology sector, building technology, most other companies have different markets that they are addressing and in my opinion, a lot of these companies, what they're trying to do is really focus on the problems that we can solve for ourselves. I think there's enough, there are more problems than we have people and expertise. So my guess is that most large companies, they're gonna focus on solving their own problems. A few, like I said, more tech-focused companies that would want to be in that business would probably branch out, but by and large, I think companies will continue to focus on serving their customers and serving their own business. All right, Ash, we're gonna leave it there. Ash, nice to see you here. Thank you so much for your perspectives. It's great to see you. I'm sure we'll see you face-to-face later on this year. This is great. Thank you for having me. You're welcome. All right, keep it right there for more great content from SuperCloud 2. We'll be right back.