 Welcome back, everyone, to theCUBE's live stage performance here in Las Vegas for SAS Innovate 2024. I'm John Furrier, host of theCUBE with my co-host and co-founder Dave Vellante, restructing the seeds of noise. We're back here with another SAS partner conversation, Gavin Day, EVP, executive president with SAS, and Tiffany Borghardt, CUBE alumni, vice president, general manager, fabric, strategic ISVs, Azure, Databricks, and AppDev, Microsoft. That's the longest idol I've ever heard. You got a lot going on. We do. And you have really interesting background from a startup that came into Azure. We're going to, that's really relevant. Gavin, great to see you again. As well, thank you. All right, so let's talk about the SAS, Microsoft relationship. Let's set the table. Give us a brief overview, and then we'll dig in. We'll dive in. Yes, so been strategic partners for four years. That was after kind of exhaustive research that we did with all of the cloud providers. And first decision was Azure is our strategic cloud provider. We run SAS internally on Azure. And second of all, we moved SAS cloud for our customers into Azure and then brought our products into the Azure marketplace. So really it's been a four-year partnership of build it and then go to market together. And one of the things we've said a lot about this partnership is that we're better together and we're meeting our customers where they are. It's been really, really exciting for us the last couple years. Dip, do you mention that they were a design partner? I'm not sure if that's public information or is that confidential? No, I guess it's out there now, but can you describe what that means and specifically why and when and the timing of the importance of that and what are you designing in? Yeah, absolutely. Well, first thing, thank you so much for running on Azure. We appreciate it. It's a very deep collaboration that we have. And as part of our Microsoft Fabric platform, which is a truly open platform, we have had SAS participate with us as a design partner from the early days. In fact, last year at Ignite, we introduced this and announced this and we'll be sharing more over the next several months. So explain Fabric a little bit more because you're unifying all your tools under a single environment. And I have some follow-up questions on how you're handling multiple models versus single models and what the future of apps looks like. Absolutely. So Fabric is an end-to-end unified analytics platform. It brings together the power of Power BI. Azure Data Factory, our Synapse Warehouse, Lake Houses, and so much more. Real-time analytics in a single unified platform where the foundation is One Lake. One Lake is what brings together the data and it's open formats. And so no longer do you have walled gardens of data, it truly is open. Your data could be in Azure, of course, but it might be in other clouds and it comes together in One Lake and all of these workloads run natively on top. So that's what Microsoft Fabric enables, a seamless software as a service experience for data analysts, data scientists, all the way to business users. So very wide range of personas, all being able to get a lot more with their data. And Fabric unifies the metadata models as well, correct? Metadata goes with the data. It's a big part of it, whether it is, you know, it's files in One Lake, whether they're tables, all of this is in, we use our Delta Parquet, Delta Lake format, which is completely open. And so you can run other workloads on top of One Lake as well. What's the strategy as, first of all, I love the open, want to get into that, dive into the lake if you will. Databricks last event they had really changed the game in our opinion. We've reported on that when they started to open up the formats. They're like, well, wait, we just want to move faster. We don't want all this thing. Snowflake made the market. But you have us now, NextGen, Data Lake, new way to get insights out of data. What's the differentiation for Microsoft? What's the core strategy? Should it be open to integrate in, seamless integration? What's the core differentiated that you guys are putting forward? Absolutely, right? Open is really important for us. And there's many forms of open, right? There's open formats, which is, we've started off with one, right? We'll do more in the future. There's open source projects we're already involved with, like X-Table. And then there's open APIs, T-SQL, KQL, all of these well-understood APIs that anyone can integrate into. And then the open platform. And that's where SAS comes in as a partner to really bring in a native experience along with our other Microsoft workloads. So we have Power BI and our warehouse and Lakehouse, and we'll have the SAS decision builder as a native experience, which we'll be talking about right now. So this is what I want to ask you about, because as an analyst, you try to squint through this stuff and say, okay, looks like Microsoft is going to one model, maybe two models, whether it's open AI or mistrial. And then you mentioned Databricks. They seem to be trying to build applications with multiple models. Now you got SAS decision builder, and this is multiple models now. And so I'm trying to connect the dots. What the future of applications look like, because I want to access multiple models. Maybe you could help us understand that. Yeah, for us, it's the freedom of choice for our customers, right? And we get to questions a lot about SAS and Microsoft and the other partners and competitive, like listen, we're all competitors and friends at the same time. Yeah, that's all cool. And for us, it's giving the optionality to our customers and bringing the power of SAS technology into Microsoft fabric. So our customers have the ability to choose and intelligent, you know, SAS decision builders built on top of SAS decisioning, which we're plowering, you know, banks around the world, where all of their credit lending decisions are going through intelligent decisioning. So for us, it brings together business users, application users and programmers to bring business rules and logic and AI models and deploying them into composite AI. So we're really excited about this. I mean, no one gets, no one wants to get locked in the optionality. Reminds me of the old interoperability days, Dave. Remember that back in the day? Oh, we got to be interoperable. Heterogeneous, it truly is that now because there's so much at stake. Absolutely. Okay, then you compete on the clouds. And for us, it's the optionality of customers using the technology that's fit for purpose for them. Sometimes it's standalone SAS. Sometimes it's SAS within Azure and we love that. All right, integration is a huge topic. You guys talk about a lot. I know in the cloud when you get the cloud, now you have cloud on premise and edge. It's cloud architecture, it's cloud operations. AI is going to certainly do a lot there. Again, we've talked about this a lot in the past theCUBE. Open data lakes, DevSecOps, it's all driven by data. If data doesn't have the SLA, it doesn't, it's not relevant. So you need access to all the data. So I like this idea of open lake because it facilitates the idea that let's not create a bottleneck or constraint on getting data to a place where you can architect it for the workload that you need. Okay, and then get all the right data and rethink that. So we think this flips the script. Gen AI flips the script on how you think about data architecture. Absolutely, like in this Gen AI era, you have to have open data, right? Because data becomes the foundation of these models. And once you have that open foundation, you can then run a variety of engines, models on top of it. It could be one of our Microsoft core workloads with Power BI or our lake houses or Spark or, and so on. It could be our partners who are bringing in to have build native experiences on a single platform so that our joint customers, our users can get more from their data in a very easy way. You don't need a PhD in this. You drag and drop. You use a native language to write SQL, build dashboards, make the best decisions from your data. Okay, so you're obviously open. You've got to have optionality for customers. As we said, Microsoft's ubiquitous. So you're a platform for everything. Okay, but things are changing so fast. This is why you have to be open. So two years ago, nobody was even, half the people didn't even know what iceberg was. Now all of a sudden that's the only thing that Snowflake and Databricks can agree on and it's forced them both to sort of change the strategies. So you kind of indicated, you talked about Delta. You said other tables are coming up. Presume iceberg is part of that. So there'll be others in the future. So you've got to have this. Remember, Unix used to be open systems. The definition evolves. But now it's really, I think achieved what I think we have an understanding of what open is and that's around optionality. You guys agree with that scenario? I mean, absolutely. I think the way we think about it, we want it to be completely open from a format's perspective. Interop is what it is, right? X-Table is for interop. And then even for compute, there are different engines that may run different types of workloads on the same data, right? On the same data, you can have different insights, better insights that you can drive. And we pull in our partners and SAS being one of them because we want to have a very rich set of capabilities for our customers, right? We won't be able to build it all. And that's where we have to have this ISV ecosystem, wide ecosystem, where we can all innovate together for the better of our customers. And integration is key there. That brings integration. I won't even say challenges. It's really opportunities. As long as you put the resource in, the engineering resource, and it's not just a... Yeah, and we are. Collaborating together, very closely. The next, we have our Microsoft build coming up in a couple of months, and stay tuned. There's going to be, we might have some good things to show there. There's always a lot of announcements at Build and Ignite, and I mean, this is just viral. Is it better to attend the Build show or Ignite? It's hard to choose between two good shows. Builds, but it's kind of cloud developers. Yes, so Build is a developer conference, right? It's builders, right? And honestly, this is an era where developers are building the very new kind of applications. Increasingly, these applications are smart applications. Obviously, with GenAI plugged in, with more analytics that is plugged in, and we have all the platforms together with our partners to give them that foundation to innovate on top of. There's a lot of developer content at Ignite too. Absolutely. I mean, there is. Absolutely. There's a lot of new innovations coming and announcements. What I love about the cloud game right now with GenAI is very entrepreneurial, even in the big companies. And we've had a riff on theCUBE many times, certainly on theCUBE, I know we've debated it multiple times, Dave, about how this generation of entrepreneurship is changing because this is the first big wave of entrepreneurship, in my opinion. People could debate, go on Twitter, I'm happy to debate this, but I feel it's true. Where the cloud players are at full-scale capacity in terms of utility, not full-scale, and they can't do it anymore, right? They are a major presence in the factors of how startups will go now. Now, Amazon was there day one, just kind of by accident on purpose, because they had a big retail, and so you'll turn it around, build a data center or go to this cloud with some console. Now it's actually a major part of the startup ecosystem. So low-code, no-code, workbench, data, workflows, and now the intellectual property, that's clearly coming out of this CUBE event here, and others, that the workflow and the data is the IP, and the scale is going to be a resource. So how do you guys see this creating value on behalf of the customers? Because at the end of the day, entrepreneurs are, they see opportunity, you've been a co-founder of companies, and so when you see opportunity recognition, you can seize it faster. And that's the end game, that's what we're talking about here. It's keeping up with the pace of change, right? And it's cliche, but the time to value is shrinking daily for our customers. And one of the things you heard this week that's so important to us is you mentioned open, right? There was, for a long time, there was a perception of SaaS being a very closed language. And what you continue to hear this week is us embracing and using SaaS. We believe it's very powerful, the language, but R and Python, bringing the optionality to our customers so they can get time to value faster based on the languages or the tools that they're used to using. And this partnership is one example of that. And Dipty, you've been an entrepreneur, you've seen it. So you can see opportunities, not just out on the streets and the wild as a startup entrepreneur, but inside a big company. You could make, you could fix one feature of an app and change the nature of that app, whether it's lowering costs or even driving, or both. And you don't need to be like a coder. So opportunity capture, what's your vision on how you see this? I mean, the game has changed, right? And you could say that three more times. The number of capabilities you can build today in days, not years, in days with Gen AI and with the tools we have today is just phenomenal. And so, on the one hand, you would think it's harder to build and grow, but on the other hand, there's a lot to innovate on. The good news is with partnerships like this, we're making it super easy for customers, for startups all the way to large enterprises, to build new experiences for their customers and do it much more smoothly, less effort, hopefully lower costs and with less resources, right? So productivity is a big part of it. Huge productivity gains, you can innovate faster and the scale of it, right? You can, with cloud scale, you can start off small, but you have the ability to grow as large as you would and be ambitious to be. Easy to experiment. I'm glad you brought a low code and then something that you talk about all the time, boring but important, governance. So you got the power platform, right? So you're knocking down the low code story. And then, governance, is it purview that you guys have that's your governance capability? How does that fit into all this? Yeah, so purview and governance is a big part of data, right? So Microsoft Fabric has built in governance, but we integrate very deeply with Microsoft Purview as well to give customers that entire platform, right? A complete unified platform with advanced capabilities. So whether it's metadata or all the way to lineage, advanced lineage across all these workloads that we're talking about, any change to your data can be tracked. And that's really important, especially, from a security cyber perspective, the world is changing on that front too and providing a nice secure governance tier on top of Fabric so that even as partners come in into that ecosystem and operate, we are actually creating a much more secure and governed platform for everyone. So it becomes really important. Fabric has what we call one security which applies across the platform and it will apply to our partners. So as the SaaS experiences come in, they will use and leverage the one security that we have built in. And so this is what really truly makes it an end-to-end unified platform where you have GenAI built in, you have semantic models, you have pipelines, right? You have real-time analytics and we have the power of our ecosystem coming in. We're opening up this platform through SDKs and that's where you can envision a single experience for our partners and us together. And just fast-forwarding maybe, maybe it's a couple of years transactions as well. I think for now, let's leave it as unified analytics platform. I don't want to get into any trouble here. You know. Dave's spoken the bear, come on. But I mean, you can envision people, places and things and new systems coming together. I mean, we saw a lot of things. We saw on Twitter a lot of controversy of people saying the modern data stack is dead. I mean, okay, it was not modern yet. It was modern for two seconds and it became dead. Long live the modern data stack. But people talk a lot about digital twins. You hear that term now much more than you used to or digital representation of your business, different data types, different data formats. SaaS obviously plays a part of that. There's the analytic systems of record and someday transactions are going to be there. Again, this is a big debate area. Again, you will get Joe, you work at Microsoft. Stick to your messaging, but it's okay to riffle a bit. And I'd love to get your thoughts on this because what's coming out of the market that we're seeing is that, and I said this a while ago, Dave, that no one can construct, it's hard to own the data player as a vendor or a supplier if you own other things. Or a new player might emerge and own that data layer or control plane and the semantic layer or no one owns it. Okay, and so what's happening is that data is only as good as the person valuing it. Beauty's in the eye, the behold of the workload. So we're seeing this layer that has to be kind of open that supports the open. So what do you guys see that? It has to be intelligent. How does this roll forward? What are the prerequisites for a CISO, a CIO, an app developer, the people that are really going to have to get in and relook at these things, these workloads to make it so that it's highly available. It hits latency SLAs, and it's the right data. Formatic, Gnostic, and multiple query types. I mean, you guys to take care of all that with technologists. They're exactly, give it, aren't we? And we touched on interoperability and that's the most important part. There was so much vendor lock in with databases and appliances and all of those things that we saw. So interoperability is key. For us, we have to consume and be able to store data where our customers want, right? We're not dictating that. But for me at a higher level, I'm glad we're talking about data again because it became unfashionable for a number of years and there was a whole bunch of bad practices around data. Not talking about necessarily security and things like that, but data quality, data integration, data governance, a little bit of what you mentioned. I mean, go ahead and go train your general AI models on bad data and let's see the results, right? So I'm glad that we're back to having this conversation again because it's a critical point for enterprises. Yeah, and you guys pointed out last year just to give you guys props on this kudos because Brian said you guys, your top four verticals are pretty much regulated industries pretty much and they have to have data quality and data hygiene. And so people who have done the work are actually in pole position with the Gen AI wave, they have this short-term lead out of the gate. Do you guys agree with that? Yeah, I mean, look, the foundation of it is this desegregation that's happened, right? Of storage and compute, with this, with the storage tier, your data can sit anywhere with one lake. We hope your data's on Azure, but we know that you probably might have some on S3 and you might have some on GCS. Well, guess what, you could shortcut this data into one lake, let it sit where it is and just link it into one lake and have a unified platform, right? Now you got me started. Because you're right, the modern data stack has separated compute from storage but now we're basically separating data from compute where any compute can go to the data. And that's a big win for customers. Because today I can only operate on the compute of whether it's an AWS or a Menager and in the future, with things like Iceberg, I'm going to be able to bring any compute to any data and that's what the customers want. Yeah, on one lake, you could run multiple different engines. You could bring in your own libraries, right? You could bring in your own code. We're welcoming all our partners into fabric so that their workloads can run on one lake. You can interrupt with one lake, even just links using these shortcuts without using fabric, right? The data is where it starts. You can build on that, pick the right engine. We have our native workloads and we hope to have hundreds more on top of fabric natively. I know, you got me going. No, no, she's got to get on SuperCloud 7, and I want to reach her. But a unified metadata model and a semantic layer that makes all these different data types coherent and that enables co-pilots to take action, transactions. And become agents. We're not talking about any specific roadmap or anything, just envisioning the future. Yes, absolutely. We're not under NDA, so we can speculate all we want. The good news is the future is bright. The best is yet to come. And moving quickly towards us. That's right. Have we had more time? I get a couple more questions in, but last question to end the segment. Gavin and Dipty, what's next in the partnership? You kind of hinted to lighting something up with these guys at SAS, relative to being a design partner. Gavin, we heard builders around the corner. I also see you guys had a multi-year relationship. Sure that's going to go forward. What's next in the partnership? Give us, tease us with a little bit of specifics. Yeah, I mean, we're going to show some pretty cool demos tomorrow on stage of, you know, decision builder. And then, as we said, there's a number of events coming where, I think Dipty said it right, stay tuned. But yeah, there is, this is the first of many from a co-engineering perspective that we have across all the different aspects of the Microsoft ecosystem and with us at SAS. So as Dipty said, the future is bright. We have a co-engineering that meets and works together daily on this partnership, side by side. We're sticking with our cues here, right, Gavin? But actually, we're really excited about getting this into the hands of our joint customers. Because at the end of the day, we want to make sure that these experiences really benefit from a time perspective that it takes them minutes, if it stays, if it's hours, if it's weeks, and really get feedback and iterate on it, right? We see this as the beginning. It's just the beginning. There is so much more that we can build on top. I mean, just like we've talked about with co-pilots and all of these other things, very exciting times. And yeah, looking forward to build and stay tuned. Great to see you, Dipty, and I want to say congratulations on your exit of your startup to Microsoft. They got a big win, congratulations. And Gavin, that's always great to have you on, to love the operational focus of data and the roadmap you guys have and the partnership. Looks like it's going to be a big ecosystem opportunity for you guys. Congratulations. Thank you guys again for being here, great. Okay, I'm John Furrier with Dave Vellante, watching theCUBE. We're going to be right back with more after this short break.