 Good afternoon everyone. It's theCUBE, the leader in live tech coverage covering day two of Snowflake Summit 23. These people are excited if you can hear behind us. They're excited for day two. They're excited for theCUBE to be here. Lisa Martin with Dave Vellante. Dave, I was watching some of our coverage from last year. This is the fifth annual Snowflake Summit. Including the virtual ones during COVID? I believe so. I think they were two during COVID. Yeah, yeah. We talk a lot with Snowflake executives, customers, partners. We're going to be talking about data trends in manufacturing, oil and gas. An update on Snowflake's manufacturing data cloud that was recently launched. And ExxonMobil's data journey. You're going to hear all of it next. Please welcome our two guests. Tim Longus here, Global Industry GTM Lead Manufacturing at Snowflake. And Andrew Curry, Head of the Central Data at ExxonMobil. Welcome. Thank you. Great to be here. Everyone's excited. You heard the applause. We couldn't have time that better. I want to get both of your perspectives on the industry. Tim, we'll start with you. Then Andrew will go to you. When you look at the manufacturing industry as a whole, what are some of the trends that you're observing? Challenges customers are facing and how you guys are positioned to help? Well, it is truly amazing. In my position, I have the opportunity to meet with hundreds of manufacturers and industrial companies around the world. And there really are a few key themes that emerge from each of those conversations. Even though the pandemic is behind us, we can say still a big focus on supply chain and resiliency and not taking anything for granted and really making sure that supply chains are optimized. The second thing is everybody wants to do better in terms of being more sustainable and being more socially responsible. So a lot of programs and of course, a lot of data to support those programs coming online across the industry. And then the third thing that we see, of course, is all manufacturing organizations are trying to wrestle with the increased costs, inflation and labor and shipping and raw materials, energy, all the concern, and everybody's looking for efficiencies that they can leverage to offset those costs. Andrea, let's get your perspective. And I apologize, I got your title wrong. You were the head of the central data office at ExxonMobil. That's correct. You were close. I was close. I just forgot one central word. What are some of the things that you're saying? I think Tim's spot on. Supply chain is definitely an area where everyone is focusing on these days. I think there's opportunities to optimize. There's risk in the supply chain that's obviously emerged during COVID and hasn't gone away, quite frankly. So that's an area where if you want to thrive and succeed, you have to manage your supply chain in a different way that we have in the past. So that's certainly an area that we're going to be focusing on. I think for ExxonMobil and the manufacturing space, really leveraging our corporate scale is a key thing. We talked about inflation. We talked about some of the pressures that are going on there. Making sure you're fully leveraging the scale of your organization, breaking down those historical silos and getting that full power and putting that to use is a key objective for us right now. And how about cyber risk? I mean, is that something that's always been top of mind or is it just the last couple of years has been escalated? It is continually escalated. It is probably a way to, but it's been top of mind for a long time. Yes, I guess. Particularly, someone of ExxonMobil's size, complexity in a number of countries we deal in, that is something that is at the forefront of our leader's mind. So, there's this saying that data is the new oil. I'm not crazy about it. I get it, but data is different, right? But from your standpoint, how do you think about data as it relates to specifically driving your business? Yeah, I think the first thing we always focus on is the business itself. We don't provide data for data's sake. We actually say, what are the business objectives? What are their priorities? What are they trying to achieve? And then understanding what data they actually need to achieve those objectives. And so, we actually do create data products. We manage and create data from all these different sources and we create them products and make those available to the business. We have a lot of objectives to start small, start with a key business initiative, but build our data to scale for future initiatives and future opportunities. So, a lot of focus on understanding the business, providing the data they need, but provide that data the way they can reuse it in multiple use cases and multiple opportunities. That's the difference from oil. Yes, I liked your tweet, by the way. I think I retweeted it, because it made sense. So, Andrew, just kind of following on, creating data products, what's the data journey been like at ExxonMobil and how and why did you seek out help from Snuff Lake? So, ExxonMobil's been around for 130 years. As a result, we have a lot of data and we have a lot of legacy tools and different things in our arsenal. And so, we've really recognized that we want to do a digital transformation. We really want to leverage that data as an asset. And so, that journey really began with, say, how do you start breaking down the silos that you have in your data? And those silos are often built through the organizational structure that we've historically had. And so, we said, all right, that data is valued beyond any one division within ExxonMobil. How do we share that data? How do we break it down? So, we realized we needed a central place. We need to start kind of moving off of our historical systems. The cloud was a logical place to go. We wanted someone who was cloud agnostic. We wanted an area where we could manage our consumption effectively as well. So, Snowflake became a natural partner for us in that sense. Why cloud agnostic out of curiosity? Well, it's a great question. Exxon operates in many, many countries across the world and we sometimes don't have the option and luxury to say, hey, we're going to go with one cloud. And so, we have to recognize that there are different areas and the performance we need in certain areas, you go with the closest mile, perhaps, or that cloud provider that's in that area. So, you have to have that flexibility. There are governmental regulations and regimes and things that impact those decisions as well. I presume you want, like most customers, a consistent experience across those clouds, call it a super cloud sometimes. Is that been your experience? Are you able to get a consistent experience from Snowflake across clouds? Yeah, it's certainly something we have a vision of what we call a data-centric architecture, right? How to keep your data unique from any one application, any one infrastructure and make that kind of reusable. And that's a core component. So, having that data fabric mindset and saying, hey, how do I have that single plane of glass? Doesn't matter with the infrastructure underneath. Having that consistently presented to your customer is important. And Tim, you gave, I thought, a great outline of the key issues in manufacturing. Supply chain, sustainability, the inflation factors, you know, et cetera. How is data helping with those? Well, through so many ways, and specifically in supply chain, it's about increasing visibility, being able to see what's coming upstream, getting more predictable about what to expect upstream, and then the same goes for downstream, making sure you're optimizing the transportation routes, using the best insights available, so you're sending product out the door the most efficient way to get it to the customer on time. So in supply chain, it's about visibility. When we talk about inflation, a lot of manufacturers are doing what they call smart manufacturing. They're bringing AI and machine learning to their big data, and they're finding value in data that they've never used before. So we talk about data, you know, it's the new oil. They were throwing this stuff away before because they didn't know how to work with it. And now there are tools and native tools to Snowflake now where they can work directly with that data and improve their yield and their output from their manufacturing operations. And how has Snowflake's manufacturing data cloud recently announced a facilitator of that? Yeah, so Snowflake's manufacturing data cloud is really the combination of Snowflake's platform, our one product that we offer, along with industry-relevant content. And what I mean by that is we've been working really hard to develop partnerships where we have rich data sets in Snowflake's marketplace that have wisdom and insights around what's happening in the supply chains around the world. We also bring technology partners that have deep integrations to Snowflake, that really leverage our strengths, and they make it that much easier and faster for manufacturing customers to get data from enterprise systems, as well as the shop floor systems. Bring it all together in Snowflake. And then lastly, we have a rich portfolio of system integrators, each who have experience in manufacturing environments, and they're bringing their experience to Snowflake, leveraging our strengths to deliver the manufacturing data cloud. So Andrew, many decades ago, drill for oil, oh, no oil here, look somewhere else, no oil there, go out today, hey, oil, okay, great. And that obviously data, even I would imagine decades ago, changed how you approach finding oil and et cetera, and refining oil. What's the focus today? Is it just better processes? Is it more efficiency? Does it help you find new sources, or has that sort of already been taken care of? That journey never ends. It's probably the efficiencies, the optimization. Where do you differentiate? It's still driven by the business and the people that are knowledge, but you'll give them the information that their fingertips in a timely manner can put you ahead. And I think one of the advantages of this manufacturing environment we're talking about is we share a lot of data, we have a lot of joint ventures, a lot of partnerships out there, and information needs to be shared in a timely manner. And so the ability to partner, and especially if I have a partner I'm working with who uses Snowflake, and we use Snowflake, the ability to integrate and share data is so much faster. And so the speed of doing business is really key and important for us. I mean, that sounds incredible business, but I see on TV, I see the ads about alternative sources, and you mentioned ESG and energy efficiency. Elon Musk says, look, we have a lot of oil. We're not going to run out of oil anytime soon. We need to find sustainable alternatives, but there's a lot of oil. But as Tower Power would say, there's only so much oil in the ground. So what about data and alternative sources? How do you use data? How does the business think about data in the context of alternative sources? Is the data inform you that one is more attractive than the other or has more potential? I'd love to understand that a little bit. I'll say our emissions data source is a critical, valuable data source for us to say, hey, what is carbon? Where is it being produced? Any project we invest in today, we look at the carbon footprint in that area. Exxomobile has a low carbon solutions division now, so it's an area we're heavily investing in. We think there is a bright future for us in there. So it is very data driven though. If you need to understand and optimize, maybe through your supply chain, what is the best route to minimize the carbon footprint to deliver your product? Those are important decisions and those are very detailed, timely decisions. Do you go rail? Do you go vessel? Those kinds of things have an impact today and more and more that's going to be important to our consumers. I know I've talked to, this is kind of off topic, but VCs who have gone over to the kingdom and there's an interest in getting into AI, the new oil kind of thing. How does Exxon think about its business long term? Are you solid in that? What business are you in when you think about the future? So AI and ML, particularly with the emergence of generative AI and large language models, is truly going to be transformative. I think Exxomobile understands that we're preparing it. We're also studying it very closely. I think you have to be careful sometimes about what information you make public inadvertently through using some of these public models and different things out there. So I'll say we're taking a cautious approach for what we've implemented to date, but we're also being very aggressive and looking at the future and what those opportunities are. And I will say the quality of your data becomes more and more important as you start leveraging these types of technologies. So that foundation of data that we've been building that we're leveraging at Snowflake is actually positioning us very well in the future to take advantage of some of this new AI and ML capabilities that are emerging. And you talk a little bit about the data culture that you've helped build. You mentioned Exxonobile, 130 plus year old company, legacy systems, maybe legacy thinking as well. How have you helped really mold an evolving data culture and how has Snowflake been kind of an accelerant in that? So we actually do a lot of work. In fact, I have a team dedicated to data culture in our organization, so it's an area we focus on a lot. We have a kind of grassroots everybody in the door kind of culture program that we address. We have thousands of people that are kind of members of our data community across the globe. We run hackathon events. We've actually partnered just recently with Snowflake to kind of run and host a hackathon. We had 447 employees on their spare time participate across 15 different countries. So we have a real grassroots community activity going on. That's one key persona when you're trying to change the culture. Your leadership is another key persona as well. They may not need to know how to do AI and ML, but they need to understand that data is an asset, that data is something you invest in and it's not just a byproduct of your business process. You say, hey, when I'm going to generate this data, how else can that data be used? Let's make sure we're maximizing it. Those kind of thought processes when you're making key investment decisions is really critical for us. So that's been part of our cultural journey as well. Tim, I'm not sure this is an example for Exxon, but are you seeing also a trend in manufacturing toward on-shoring or is that just more sort of talking the press? No, absolutely. In fact, the data confirms that. I think it's record level investment in construction of manufacturing domestically this year. It's one of the many things that manufacturers are doing to restore resiliency in their supply chain is making sure that what they depend on the most is closer to home. So absolutely there's an investment and a boom I think happening right now in manufacturing in the U.S. So there's some interesting countervailing trends in the data, I wonder if it shows this, but the CHIPS Act is an example of some on-shor and European investments, but then you mentioned inflation before, so there's that countervailing factor. You bring it back on-shore, it might be more expensive, but it might have other benefits. What are you seeing in the data or even anecdotally? Well, I mean, it's always a cost analysis, a return on benefit analysis, but I think that there's so many new efficiencies with the modern factory, new construction of new factories that it's competitive to produce in the U.S. again. So a lot of the advancements with AI and machine learning and the data, they're helping to make it much more efficient and lowering the overall cost profile. What's been some of the feedback from customers on the manufacturing data cloud and how does the Exxon use case kind of help evolve it and mature it? Well, the feedback has been really great. We have so many customers and prospects reaching out that want to learn more about it, and specifically, you know, everybody's at a different point in their journey. Many of the people we talk with are still just looking to connect data from one system to another and Snowflake's just the best place to do that. Bring the data out of the silos, combine it in Snowflake. And so when Andrew tells the story of Exxon Mobile, they see how they can do it too, and the benefits that Andrew and his team have created for the Exxon Mobile business are right there. And then the second thing that I'd say is they're really excited about some of the new capabilities we have to take data off the shop floor and bring it to Snowflake, that's a game changer. So where are you in your journey? Is Snowflake your data strategy? Is it one part of your data strategy? Is it a broader mesh? Yeah, so we do have a data strategy and we are actively implementing it. It's probably a way to describe it. In fact, that journey will never end in some sense, but yeah, we have a centralization strategy. We have a lot of data, bringing that data together, being able to link it more and more. And so we've been on that journey for about two years with Snowflake and then building that out and we're going to continue on that journey into the future. And centralization means logically centralized or physically or both? Yeah, so I mentioned before we used to have legacy data platforms that you may have had the chemical customers used to sit on one system and the fuels and loops customers used to sit on another system. All of our customer data is in one place now and that's on Snowflake. But physically as well or is it sort of distributed across multiple clouds? It is physically as well, I would describe that. I'll let Snowflake, if they're putting it in one cloud or the other. But yes, it's physically together in one platform on Snowflake. Well, certainly in one platform. But I'm curious as to if you try to actually get it to the same region or the same, is that the typical best practice or is it more, hey, it's inside of Snowflake, it's a global instance? Yeah, there are reasons, there are trade-offs and different reasons to do either strategy. So we have a variety of all sorts of configurations. Many of our multinational companies will have Snowflake instances around the world and operating on different clouds. So as Andrew had mentioned, maybe some on Microsoft, some on Amazon and so on. And what's unique about Snowflake in that environment is our customers can build one data product and then simply share that, make that available across the enterprise, across clouds, everywhere. And that's also what enables our marketplace. All the data that Andrew's talking about, they use to improve their supply chain. That's coming from any number of different clouds and regions around the world and we facilitate that network. That's what I'm trying to get to. So notwithstanding DR, I know there's some disaster recovery reasons where you do that, but if I'm inferring that you're not necessarily physically putting it into the same, let's say, AWS region, it actually can be distributed and live there, but it's the same global instance of Snowflake because we know from talking to Benoit that it's a single global instance, even across clouds. Exactly. Yeah, okay. And I think the simplicity of that from our standpoint, now that's a configuration option rather than a large design activity by us now. So that's something we're just taking advantage of functionality that Snowflake provides. So latency-wise, you might choose to leave data in a certain region or sovereignty, as you mentioned before. Exactly. But if you have to query, you might have to, I don't know, create a materialized view or whatever magic you guys make or maybe even copy the data if necessary, right? So, okay, so you basically, you've built this massive distributed network and you're taking advantage of it. Absolutely. Exactly right. Very cool. Guys, thanks so much for joining Dave and me on theCUBE talking about ExxonMobil. It's data strategy, it's data journey, why Snowflake and the manufacturing data cloud, the customer feedback and where you guys are going. We really appreciate your time and your insights. Oh, thank you very much. My pleasure. Our pleasure as well. For our guests and Dave Vellante, I'm Lisa Martin. Up next, we're going to be talking with Snowflake and Tenable. They're going to be talking about Tenable One and Snowflake together, how customers can easily centralize all vulnerability and threat data in one place to unlock that holistic view of their entire attack surface and glean insights. That's what customers want. You can catch all of theCUBE content from Snowflake on thecube.net and of course our analysis and editorial on siliconangle.com. Stick around next, Dave and I will see you in a minute. You're watching theCUBE, the leader in live tech coverage.