 Good morning, everyone. Did you catch that awesome interview with Dave Vellante and Frank Slutman just now? It's on theCUBE.net, if case you missed it, you're definitely going to want to see it. Lisa Martin with Dave Vellante, day two of our coverage of Snowflake Summit from Caesar's Forum in Las Vegas. We've had great conversations yesterday, today. There was a special Easter egg in Dave's interview with Frank, you're going to want to watch it. Up next, we're going to be talking about Snowflake, its partner ecosystem, how they're helping customers with their cloud data transformation, helping customers achieve really big business outcomes. Dave, I always love talking to the Snowflake ecosystem. It's never a dull moment. Well, and you know when the ecosystem brings in the leading system integrators, that it's beginning to get real, because that's where it actually all happens. Yeah, the rubber's going to meet the road and you're going to hear about it next. Narayan Kamat is here, Global Head of Strategic Initiatives and Partnerships at Wipro. Welcome to theCUBE. Thank you for having me here. And it's always an honor to follow somebody like Frank Slutman. I've dropped in some of the interview notes and unbelievable where we are today. Isn't it fantastic, lots of news, starting Monday night with NVIDIA yesterday was like one of those t-shirt cannons at like a basketball game of news, I say. But talk to us about what's new at Wipro, what's the partnership. I know that partnerships are really core to Wipro's DNA, give us the backstory. We've gone absolutely serious about the kind of partnerships we choose and we've been very, very strategic about it. We've selected only a handful of partners, including the hyperscalers and snowflakes sits right at the top. We want to go, as they call it, inch wide and a mile deep with what we do and we have committed full end. Wipro's committed a billion dollars into Wipro Full Stride Cloud, which is around complete cloud modernization, digital transformation and a lot of that is investments into our partnerships, partner programs, joint solution and go to markets. And we're doing it pretty big with Snowflake now and that's why Snowflake, especially in today's world for the last three years, we've only seen growths about 200% in terms of how it's impacting our revenue and the business outcomes that are reflective of to our customers. An inch wide and a mile deep generative AI, it's the hottest topic one of, it's like the new it girl for tech. Give us your point of view on the impact that it's having on Snowflake, cloud data storage and some of the outcomes that you're excited for it to generate. Awesome question. I mean, if I had a cent for every time I had gen AI, the last two days I've been a millionaire, the fastest one. But yes, I mean, absolutely disruptive and we know that, especially Wipro was marked by IDC as worldwide AI services leaders for 23. So we know a thing or two about gen AI and the disruptive nature of it is so much so that I cannot go to a meeting with customer or talk about a solution, even some of the solutions we launched without having gen AI component follow up on Snowpark. Just take the fact, March, chat GPT, 100 billion users hit it per month. The kind of growth, the kind of acclimatization towards chat GPT across all ages is huge. But that's showing up on the demand for data. I mean, we talk about spearheading with AI, there's also regenerative AI, it is more feedback based, you fail fast, you know what is right, what is not, you do your data sets which are replicative, you have your LLMs that would give you the reasons why things fail and you have regenerative AI. So it's spearheading by AI, but that can only take you to as good as what is driving gen AI and that is the data. That's the fuel, that's what is propelling every industry use case, every customer success today. So tell us more what those conversations are like with customers. Is it trying to figure out, like you know how everybody was trying to get digital right until COVID forced us to get digital right? I feel like everybody's trying to figure out LLMs and gen AI and it's magic, but it seems like Frank said it's got to have a return. So what is that conversation like and where is the ROI? Absolutely, I mean most of the conversation, believe it or not, are non-technology. Most of the conversations start with business and what they want to and almost always end up with significant business outcomes, right? And I can give an example for a customer that we created a solution. It was around using gen AI. It's one of the largest cigarette manufacturers. It's about the time spent on selecting the quality of tobacco leaves, right? I mean it is manual process, you describe the quality by taking a look at different quality grades and based on that those kinds of cigarettes are made. That was all automated through gen AI, right? And that bought in a savings of about 25 to 30 million dollars per year. I mean it was a business conversation. How can I automate? Today business are initiating the conversation. What can I do with AI? Where do I want to save money or time to market? And that is going in. For example, we're talking about 30 to 40% of all new innovations today touched by gen AI and regenerative AI. In fact, we are predicting about 60% of some form of AI or region AI will touch into all product development and innovation by 2025, next two years. So that example you just gave, was that analytics? Was that a snowflake example? A snowflake example. We have a solution built on snow park, on snowflake. So and also the market is such that Dave and Lisa is today even considering the macroeconomic environment, the companies that are going to make investment into AI, gen AI and solutions around it are going to be coming extremely strong. That's why I love what Frank said. I mean the investments with their new acquisitions and with NVIDIA, it's just tremendous. But once the economy comes back in the next two quarters companies like us who are investing big time in snowflake are going to really rock the boat. So Narayan, you've developed a solution in snow park. Yes. Help us understand what that was like. What is that solution like? What was the experience like from a developer perspective? Share that with us. This was one of the first times we actually took our solutions as part of snowflake cloud data network launch. We opened up two solutions, one on telco, one on manufacturing. The telco one we inaugurated in mobile congress in Barcelona. The manufacturing one we did in Hanover, messy Germany and Gartner back in Florida. The mobile solution, the telco solution was more around two use cases that we predominantly ran. One was the telco churn, which was predominantly running on the snow park AI logic and also in proactive maintenance and early warning system, if you will. For example, the kind of interfaces their towers would have with different electrical lines or if some towers need proactive management before failure, if you can predict the damage that is coming in. We had models running through all of that. We also, you might hear, I'll give you an example. I mean that could be the AI component. I'll tell you the data component. To have that kind of tremendous insight to it, you need a solid twinning mechanism. I need to stand up a data or a digital twin of that organization for AI to hit. Totally, love this conversation. And understand your failure points and that builds up. That creates what I call it the regenerative AI and that builds a solution. So that digital twin is like, we always say people, places and things and turning that into something that a database understands. But those solutions that you built, are they different data types? Are they all the sort of, Snowflake talks about unstructured data, structured data, semi-structured. It's all, it grows, there's columns, there's graphs, there's streaming. There are UAV pictures, there are drone pictures, there's everything. It's completely digital, 100% digital. And then we've said, this is our premise, that the magic of Snowflake is you're able to return a consistent, coherent answer, if you will, data point that then you can act on, right? Has that been your experience? Absolutely, the game here is the speed with which you can have that data, the speed with which you can have fail. You can fail on your analytics and Snowflake enables that, right? Having to date the data exchange or standing up or creating a digital twin, it's immense. That's what powers quicker analytics today. So, I got to ask you this, I wish I'd asked Frank on camera, but I wasn't really sure of the questions, but in George and I, we're talking about this, we've talked to some customers who say they would rather do the data engineering and data pipelining outside of Snowflake, because it's too expensive because of the cloud cogs, because Snowflake bundles that in, they have to pay for the cloud in, they get to pay for Snowflake. I asked Frank off camera, he's like, they're wrong. Because our initial experience with Snowpark has been just the opposite, that you can do things so much quicker and so much cheaper if you do that data engineering inside the platform. So, what was your experience? It can go anyways, I mean, it depends on the customer, but I can understand where it comes from, especially with the comment he made. I mean, we are seeing now apps coming closer to the data than data going in. So, your data should be wholesome, intrinsic, and the least dependency on anything outside, the better it is. But I also understand that in a federated architecture, sometimes it's difficult. You need to have certain engines outside. Again, it's a business dependency, it could be two different organizations working, but I feel, I mean, this is my personal opinion, the engine to data and your apps, the closer they are, the faster and better it is to turn our business. And yours is a Greenfield app, is that right? It's a Greenfield app. Yeah, so that makes sense actually for a Greenfield app. I mean, if you're using a bunch of Informatica or other sort of ETL, and you've got your data, or maybe even a Spark execution engine, and you've got infrastructure built up around that over 10 years, maybe it makes sense to do it there, but- I'll tell you, we see equal amount of this ecosystem place, right? Where it's on AWS, no flake, and we are working in Informatica engines, because there is so much stickiness with business. Business are risk, they don't want their risk averse, right? They don't want failure. They want much of the same. They want the same systems, what they understand, and especially large banking financials. We see a lot of transformation. We take them through the journey of cloud modernization. That aspect, the change is what worries them, and I'll tell you why that is coming in, right? Because a lot of the cloud failures are happening, they move the data onto the cloud, but the afterthought is security, my governance, my data catalog, when these are the things that they're familiar with things like Informatica. So they exist, coexist very well in Informatica, and I heard Informatica today released one more integration, pipe into Snowflake. So it coexists, but the follow-up is that now, we are talking about the importance of data governance. You heard Franck yesterday talk, Debupur yesterday talk about data governance, the quality and security. It's going to be so intrinsic and tightly coupled. It's the hail storm, that's the hail Mary of success on cloud, in my opinion. I think if, sorry, at least I know you want to jump in, but I think if you're building a digital twin of your business, people, places, and things like, we use the Uber example. Uber for the enterprise, Uber had to do a lot of work to actually create the coherence across its people, places, and things, and riders, and drivers, and ETAs, et cetera. Establishing that horizontally in any industry, inch deep, mile wide, and then you come in and make it mile deep is a real challenge, and that is, I feel like Snowflake's in a good position to do that, but. What's the Wipro's secret sauce? When you're working with Snowflake, helping customers to really transform so that they can achieve business outcomes, and use, you know, generative AI and LLMs to create new apps, new products, new revenue streams. What makes Wipro really unique in that sense? So, Wipro started pretty early with Snowflake. We invested into them pretty early. We were also partner of the year too, when we began. But now the secret sauce is we try to stay ahead of the curve with respect to our competition to predict where Snowflake's future is and try to build around that. For example, I mean, and our entire organization, it's just not, just Snowflake, right? It's, as I said, it's around the whole cloud. I mean, we created the entire organization of Wipro full-site cloud services around cloud modernization. We put a billion dollars into it. We created an organization which is very simple, four by four metrics, which helps, you know, take, go to our customers in a very simplified way along with our partners, right? We also built an end-to-end ecosystem called WDIS, Wipro Data Intelligent Suite, which Snowflake forms, Snowflake and Snowpark forms the backbone, which helps customer traverse to the cloud journey in a risk-averse way. We take them to the whole blueprint of what is your short-term goals, where are the aspects that you fail, which is the quickest path for quickest returns to your certain business goals or business outcomes. And we take them to the journey and we help them implement all the way towards their AI models to their business outcomes and business goals. That suite, we built about three years ago, we started investing in, and seamlessly we are trying to modify and engineer it to fit in with whatever Snowflake brings in, right, today. So you guys launched recently, and you've already talked about this with Dave, two Snowflake data cloud industry solutions, five business cases so far, using Snowpark, what's next? More of the same, I guess. I mean, we want to go industry-wide. We want to focus, as I said. I mean, if you want to build the example of digital twinning again, you need to know the markets. Where Wipro comes in is we need, we know our customers deep. And we have been with those customers for years. Our deals are deals where we sit across the ecosystem of a customer, guiding them to the journey of modernization across to the business. So we are in a unique place where we can take the technology and we can bring our business understanding and take it deep across the organization, deep into the organization, right? Today, you heard, I don't know if you're in the partner meet, Colleen said there are about $150 billion worth of unused, you know, Snowflake work out there. And that's where partners like us come and help our customers to use those GPUs and use those, you know, investments across their business to drive success. And that's where we're going to be invested more towards, towards industry solution, towards tying more back, tying into some of the investments into, Snowflake has made it, especially with Neva and what's working with NVIDIA. We're going to make sure that is directly reflecting to our customer to get that business outcomes faster, better, deeper solutions. Yeah, that inch wide, inch wide, mile deep might go two miles deep. Absolutely. We cannot go, as I said, right? We cannot do the spray and pray concept. Well, you know, it's funny, you do see a lot of, I think less today than you used to, what we call Barney press releases, you know? I love you, you love me, and then it doesn't drive productivity. And I think companies are being smarter about that. We're going to make the investment, let's go deep. Well, you know, apparently Barney's making a comeback. Is he? Oh yeah. He's back. Loving everybody. Norayana, it's great to have you on theCUBE with Dave and me. Thank you for sharing what's new. Thank you for having me here. Wipro, Snowflake, how you're helping customers with that transformation so that they can get to market faster, and we'll keep our eye on some of those new upcoming industry solutions. Thanks for your time. Absolutely. Thank you for having me here. It's a pleasure. We want to thank you for watching this segment. For our guests and for Dave Vellante, I'm Lisa Martin. Up next, Exxon Mobile and Snowflake are going to be here talking about trends in manufacturing oil and gas. They're going to be talking about an update on Snowflake's manufacturing data cloud announced recently. An Exxon Mobile's data journey. Keep it right here on theCUBE. Your leader in live tech coverage, everything available on thecube.net and siliconangle.com. See you in a minute.