 Good morning everyone and welcome to theCUBE's day one coverage of Google Cloud Next Live at Moscone South in San Francisco. I'm Lisa Martin. Dustin Kirkland is my CUBE analyst co-host. We're here with about 20,000 people. You can hear the din of the buzz behind us. There was a tremendous amount of announcements this morning. Lot of great Google Cloud execs customers, partners were here. We have Stream joining us next. John Coutte, the head of product, joins us. John, great to have you. Thank you so much for joining us on theCUBE. Thanks so much for having me. Super excited for this discussion. Yeah, would love to share with the audience more about Stream. What do you guys do? Mission, vision, help us understand that. Absolutely. Stream is unified data streaming for generative AI analytics and operations. We love helping our customers infuse real-time data into their decisions, into their operations and now generative AI which is becoming a top priority for many of the enterprise data teams that we're working with. It is. Gen AI is probably the hottest topic on the planet or one of. You talked about real-time and I think one of the things we've learned in the last few years is that access to real-time data is no longer nice to have for companies. It's an imperative. It's absolutely. For every industry, it's really hard to do that but I'm curious what some of the gaps in the market were when Stream was launched that you guys saw that you thought, we can solve this. Absolutely, so the company's CEO and CTO came from Golden Gate software which at the time of its acquisition by Oracle was the number one database replication product in the market but it was very pigeonholed into just copying data between databases and there was this obvious demand in the market to not only move data in real-time but to analyze it. And now with this big wave of generative AI and it's not about data going into some warehouse and you wait for someone to pull up a report, now you want data automatically making decisions for you. You want your customers to talk to a smart AI-driven bot that knows everything about them and can answer questions for them and this all requires real-time data. Absolutely and every company, whether it's the grocery store or the gas station or Starbucks has my data and they expect that they not only use it responsibly and securely but also use it to give me that real-time relevant personalized experience that I want. Every company has to be really, I've heard people say data-driven and I heard someone last week say no, not data-driven, insight-driven. There's a difference, there's a difference there. Talk to us about how Stream is working with enterprise data teams to really help them extract the value of data and especially working with Gen AI. Absolutely. Macy's.com who we presented with previously at Google Cloud next session. They power, and remember, they're not in the business of doing data, right? They're trying to sell clothes and they had a digital-first initiative. Stream helped them go from their existing investments in their on-premise, you can call legacy infrastructure and help make sure that that data's in Google Cloud within seconds because if they're building new digital applications, that data has to be there. So we're really proud to have customers like that and then we have other examples of airlines, for example. They want to run their operations on time. They need good customer experiences. They need to make sure that the aircrafts are safe. We help American Airlines do exactly that. We were presenting with them at a data and AI summit and with Stream, Databricks, MongoDB, they were able to, again, take their aircraft telemetry, action it for their operational teams that are there to maintain the aircraft, make sure that everything's safe, everything's ready to go and best of all, everything's on time. Yeah, that's what it's all about, right? Being on time these days. Yeah, along those lines, talk to me a little bit about the velocity in terms of how teams integrate this, how fast, how long does it take, how long till we see results from integrating Stream? Absolutely, we're really proud of being able to get our customers into production in a matter of weeks. Even when it's complex, it's breaking down, long standing data silos within the enterprise, a lot of technical complexity. For instance, at our presentation with American Airlines at data and AI summit, they were really proud of the fact that they went to production at global scale within 12 weeks of Stream. And it's because Stream is a unified data streaming platform, meaning connectors, the data movement, the modeling, the processing, streaming it into your target systems, meaning whether it's Google Cloud infrastructure, Databricks, Snowflake, all that data has to be there with quality and uptime SLAs that the business can trust. Where are your customer conversations these days? Are you talking with chief data officers, CIOs, is it all of the above? I imagine it can vary depending on the organization. But every company is so data rich, but they have to be able to figure out, how do we get access to this now? It's really important to be a catalyst for internal collaboration, meaning, yeah, you have to work with the CIOs, the chief data officers, all the way down to the people who are in the trenches building the pipelines and build alignment there. And that's something that we're also really proud of. And because at the end of the day, yeah, you're solving technical problems, but you're delivering on business use cases and initiatives, and that's the most critical thing. What are some of the key use cases that you see that maybe have more horizontal play across industries that stream is involved in? Yeah, that's an amazing question. So right now, data teams, you know, they already had years worth of initiatives on their plate, and now a generative AI, all the innovation that's happening here at Google Cloud Next and across various platforms, there's a very high priority mandate for data teams to adopt generative AI and really bring their data into generative AI and then do the reverse, which is bring generative AI to where their data is today. So those are some of the use cases that they're looking at in terms of making sure that data is making decision on its own. Yeah. Can you share a little bit about the partnership with Google, what you guys are doing together, how you're helping customers really unlock the value of AI and gen AI? Absolutely. We're really proud of our partnership with Google. If you're a BigQuery user, you go into the add data button, Streams right there. You can launch it from your console. Stream is a Google Cloud native product. Our CTO, Alok Parikh, presented up here at Google Cloud Next since the beginning when they were doing these shows, and we're really proud of helping enterprises quickly realize the value of Google Cloud by complimenting their existing enterprise investments, getting that data into Google Cloud and making sure that it's reliable and the business can build on top of that using the modern infrastructure that Google is providing. Yeah, that modern infrastructure, we talked a lot about that this morning and for the builders, it was probably like music to their ears. Yes, Stream's clearly an important piece of that, for sure. How do your customers think about the return on investment, you know, the Stream, Google Cloud, all that making their investment in you and seeing a return? Look, when I work with the data team and I try to work with them on their goals and OKRs and things along those lines, if their goal is to move data from A to B, that's not good enough. We have to talk about what your actual business initiatives are and how this data project or tactic is going to help you there. So in the example like I brought up with Macy's, they can tie that to customer experiences. Having more fresh, reliable data is critical. American Airlines, their aircrafts moving, making sure that those are operating with as fast as possible. Aircrafts are taking off on time, well-maintained. And that's really where you see the ROI's. Like, how is data helping your business meet their mission statements? When you're in customer or prospect conversations, John, and they say, why Stream, what do you say? What are those key differentiators that really shine a light on the value problem? Yeah, absolutely. The fact that it's simply a unified platform with just a couple clicks, we're spinning up a lot of complex infrastructure that you don't have to know about as an end user, making sure that it's very reliable, it's very fast. Instead of Stream vendors were, I mean, sorry, companies were pulling in six, seven vendors to do the same thing. Now you get the whole thing in one single pane of glass. You get your connectors, you get your data processing, your data delivery, monitoring data quality and freshness so that the data stakeholders know that there's ultimately trust in that data. And that trust is currency these days, right? It absolutely has to be there. But sounds like what Stream is doing to me is you're really, are you helping companies to kick out six to seven other vendors so that from, I'm hearing workforce productivity, cost efficiencies, ROI, as Dustin was talking about, it seems like those are some of the big outcomes in general that organizations can achieve with Stream. I always think about it as very purpose-driven. You have a specific business problem you're trying to solve rather than it taking years of development and expensive investments. You can get your initiatives off the ground and into production very quickly. And that's just with the power of the platform and the way that we partner with data teams as well to make sure that they're tying it to their business initiatives and getting that value out of it. Yep, it's all about getting trust. Making sure the data is trustworthy, responsible, secure, and extracting that value. Last question, John, for you, as before we wrap here. Anything new, exciting, coming up for Stream that we should be looking for? Any events, any webinars, things that you want to plug? Yeah, in fact, tonight, we're doing a What's New in Data Live. This is a thought leadership session that I run. We're really excited to have Bruno Aziza, who's formerly a Google's, yeah, head of data analytics. Now he's at Capital G, Alphabet's Capital G. And we have Sanji Mohan, who was previously at Gartner. And we have Radima Khan, VP of Dapper Labs, who's going to talk about modern digital consumer experiences. So that's tonight at Salesforce Hour. We're going to record it so it'll be made available to everyone. And we're going on tour with What's New in Data and bringing all the data practitioners, data leaders to really talk about how they're innovating with data and meeting on these business goals that they're trying to deliver on. Awesome, lots of stuff going on. Best of luck tonight, Sanji is a CUBE analyst from time to time. We know Bruno, he's been on the show. So lots of great folks, that's stuff we were talking about before we went live. Like tech is just like two degrees of separation. John, it's great to have you. You're now officially a CUBE alumni. I probably can get you a sticker. We appreciate you sharing with us what's going on at Stream with Google and how you're really enabling those data teams to maximize value and use Gen AI. Thank you so much. Thank you for having me. Our pleasure for John Coutet and Dustin Kirkland. I'm Lisa Martin and you're watching the CUBE Live, day one of our three days of coverage of Google Cloud Next. Dustin and I are going to be right back with our next guest, so don't go anywhere.