 Hey, everyone, welcome back to theCUBE's continuing coverage day two, Snowflake Summit 22 live from Caesars Forum in Las Vegas. Lisa Martin here with Dave Vellante bringing you wall-to-wall coverage yesterday, today, and tomorrow. We're excited to welcome Matthew Carroll to the program, the CEO of Emuta. We're going to be talking about removing barriers to secure data access, security. Matthew, welcome. Thank you, have me, appreciate it. Talk to the audience a little bit about Emuta. You're a Snowflake Premier technology partner, but give them an overview of Emuta, what you guys do, your vision, all that good stuff. Yeah, absolutely, thanks. Yeah, if you think about what Emuta is at its core is we're a data security platform for the modern data stack, right? So what does that mean? It means that we embed natively into a Snowflake and we enforce policies on data, right? So the rules to be able to use it to accelerate data access, right? So that means connecting to the data very easily, controlling it with any regulatory or security policy on it, as well as contractual policies, and then being able to audit it. So that way, any corporation of any size can leverage their data and share that data without risking leaking it or potentially violating a regulation. What is the key as we look at industry by industry challenges that Emuta is helping those customers address and obviously quickly since everything is accelerating? Yeah, and you're seeing it because the big guys like Snowflake are verticalizing, right? You're seeing a lot of industry-specific concepts. With us, if you think of where we live, obviously policies on data, regulated, right? So healthcare, how do we automate HIPAA compliance? How do we redesign clinical trial management post-COVID, right? If you're gonna have billions of users and you're collecting the data, pharmaceutical companies can't wait to collect that data. They need to remove those barriers so they need to be able to collect it, secure it, and be able to share it, right? So double and triple blinded studies being redesigned in the cloud. Government organizations, how do we share security information globally with different countries instantaneously, right? So these are some of the examples where we're helping organizations transform and be able to kind of accelerate their adoption of data. Matt, I don't know if you remember, I know you remember coming to our office, but we had an interesting conversation and I was telling Lisa, years ago I wrote a piece of, how to build on top of AWS. There's so much opportunity. And we had a conversation at our office at the Cube Studios in Marlboro, Massachusetts, and we both sort of agreed that there was this new workload emerging. We said, okay, there's AWS, there's Snowflake. At the time we were thinking, and you bring machine learning, at the time we were using Databricks as the example. Of course, now it's been a little bit more of a battle with those guys. But, and so you see them going in their different directions. But the premise stands is that there's an ecosystem developing new workloads, developing on top of the hyperscale infrastructure, and you guys play a part in that. So describe what you're seeing there because you were right on in that situation. Yeah, yeah, it's nice to be right. Yeah, so when you think of this design pattern, right, is you have a data lake, you have a warehouse, and you have an exchange, right? And this architecture is what you're seeing around you now is this is every single organization in the world is adopting this design pattern. The challenge that where we fit into kind of a sliver of this is, the way we used to do it before is application design, right? And we would build lots of applications and we would build all of our business logic to enforce security controls and policies inside each app and you go through security and get it approved. In this paradigm, any user could potentially access any data. There's just too many data sources, too many users, and too many things that can go wrong. And to scale that is really hard. So like where the Muda, what we've done versus what everyone else has done is, we natively embedded into every single one of those compute partners. So Snowflake, Databricks, BigQuery, Redshift, Synapse, on and on, natively underneath the covers. So that was BI tools. Those data science tools hit Snowflake. They don't have to rewrite any of their code, but we automatically enforce policy without them having to do anything. And then we consistently audit that. I call that the separation of policy from platform. So just like in the world in big data when we had to separate compute from storage in this world because we're global, right? So we have a distributed workforce and our data needs to abide by all these new security rules and regulations. We provide a flexible framework for them to be able to operate at that scale. And we're the only ones in the world doing it. So the key there is, I mean, Snowflake is obviously building out its data cloud and the functions that it's building in are quite impressive. But at some point, a customer is going to say, look, I have other stuff, whether it's in an Oracle database or a data lake or wherever. And that should just be a node on this global, whatever you want to call it, master fabric. And if I'm hearing you right, you participate in all of that. Correct. Yeah, we're able to just natively inject into each and then be able to enforce that policy consistently. So, hey, can you access HIPAA data? Who are you? Are you authorized to use this? What's the purpose you want to query this data? Is it for fraud? Is it for marketing? So what we're trying to do as part of this new design paradigm is ensure that we can automate nearly the entire data access process, but with the confidence and de-risk it. That's kind of the key thing. But the one thing I will mention is I think we talk a lot about the core compute. But I think, especially at this summit, data sharing is everything. And this concept of no copy data sharing, because the data is too big and there's too many sets to share. That's the keys to the kingdom. You've got to get your lake and your warehouse set with good policy so you can effectively share it. Yeah, so I wanted to just to follow up if I may. So you've mentioned separating compute from storage and a lot of VC money poured into that, a lot of VC money poured into cloud database. How do you see snowflake differentiating substantially from all the other cloud databases and how so? I think it's the ease of use, right? Apple produces a phone that isn't much different than other competitors, right? But what they do is end to end, they provide an experience that's very simple, right? And so yes, are there other warehouses? Are there other ways to, you know, you heard about their analytic workloads now, you know, through Unistore where they're gonna be able to process analytical workloads as well as their ad hoc queries. I think other vendors are obviously gonna have the same capabilities, but I think the user experience of snowflake right now is top tier, right? Is I can, whether I'm a small business, I can load my data in there and build an app really quickly, or if I'm a JP Morgan or, you know, a West Farmers, I can move legacy, you know, monolithic architectures in there in months. I mean, these are six month transitions. Think about 20 years of work is now being transitioned to cloud in six months. That's the difference. So measuring ease of use and time to value, time to market. Yeah, it's everything is time to value. No one wants to manage the infrastructure. In the Hadoop world, no one wants to have expensive customized engineers that are, you know, keeping up your Hadoop infrastructure any longer. Those days are completely over. Can you share an example of a joint customer where really the joint value proposition that immediate in snowflake bring are delivering some pretty substantial outcomes? Yeah, what we're seeing is, and we're obviously highly incentivized to get them in there because it's easier on us, right? Because we can leverage their row and cum level security. We can leverage their features that they built in to provide a better experience to our customers. And so when we talk about large banks, they're trying to move terror data workloads into snowflake. When we talk about clinical trial management, they're trying to get away from physical copies of data and leverage the exchange as a mechanism so you can manage data contracts, right? So like, you know, when we think of even like a company like Latch, right? Like Latch uses us to be able to oversee all of the consumer data they have. Without like a snowflake, what ends up happening is they end up having to double down and invest on their own people, building out all their own infrastructure. And they don't have the capital to invest in third-party tools like us that keep them safe, prevent data leaks, allow them to do more and get more value out of their data, which is what they're good at. So TCO reduction I'm hearing. Yes, exactly. Matt, where are you, as a company, you've obviously made a lot of progress since we last talked. Maybe give us the update on, you know, headcount and fundraising. Yeah, we're just at about 250 people, which scares me every day, but it's awesome. But yeah, we just raised $100 million. I saw that, congratulations. On the series E, thank you with Night Dragon leading it. And Night Dragon was very tactical as well. We're moving, we found that data governance, I think what you're seeing in the market now is, is the catalog players are really maturing and they're starting to add a suite of features around governance, right? So quality, control, observability, and just traditional asset management around their data. What we are finding is, is that there's a new gap in the space, right? So if you think about legacy, it's we had infrastructure security. We had the four walls and we protect our four walls. Then we moved to network security. We said, oh, the adversary's inside, zero trust. So let's protect all of our endpoints, right? But now we're seeing is data is the security flaw. Data could be, anyone could potentially access it in this organization. So how do we protect data? And so what we have matured into is a data security company. What we have found is, there's this next generation of data security products that are missing. And it's this blend between authentication, like an octa or an ortho, and authorization, like a muta where we're authorizing certain access and we have to pair together with the modern observability like a data dog to provide a layer above this modern data stack to protect the data, to analyze the users, to look for threats. And so a muta has transformed with this capital and we brought Dave DeWalt onto our board because he's a cybersecurity expert. He gives us that understanding of what is it like to sell into this modern cyber environment? So now we have this platform where we can discover data, analyze it, tag it, understand its risk, secure it to author and enforce policies, and then monitor, the key thing is monitoring. Who is using the data? Why are they using the data? What are the risks to that in order to enforce the security? So we are a data security platform now with this raise. Okay, well that's a new vector for you guys. I always saw you as an adjacency, but you're saying smack dab in the heart. Yes, yeah, we're jumping right in. What we've seen is there is a massive global gap. Data is no longer just in one country. So it is how do we automate policy enforcement of regulatory oversight like GDPRCCPA, which I think got this whole category going, but then we quickly realized is, well, we have data jurisdiction. So where does that data have to live? Where can I send it to? Because from Europe to US, what's the export treaty? We don't have defined laws anymore. So we needed a flexible framework to handle that. And now what we're seeing is data leaks upon data leaks and the snowflakes and the other cloud compute vendors, the last thing they ever want is a data leak out of their ecosystem. So the security aspects are now becoming more and more important. It's going to be an insider threat. It's someone that already has access to it and has the rights to it. That's going to be the risk. And there is no pattern for a data scientist. There's no zero trust model for data. So we have to create that. How are you, last question, how are you going to be using 100 million raised in series E funding, which you mentioned? How are you going to be leveraging that investment to turn the volume up on data security? Well, and we still have also another 80 million still in the bank from our last race. So 180 million now and potentially more soon. We'll kind of throw that out there. But the first thing is M&A. I believe in a recessing market, we're going to see these platforms consolidate. Larger customer vars are driving us to say, hey, we need less tools. We need to make this easier so we can go faster. They're even in a recessing market, these customers are not going to go slower. They're moving to the cloud as fast as possible, but it needs to be easier, right? It's going back to the mid 90s kind of Lego blocks, right? Like the IBM, the SAP, the Informatica, right? So that's number one. Number two is investing globally. Customer success, engineering, support, 24 by seven support globally. Global infrastructure on cloud, moving to true SaaS everywhere in the world. That's where we're going. So sales, engineering and customer success globally. And the third is doubling down on R&D. That monitor capability, we're going to be building software around, how do we monitor and understand risk of users? Third parties, so how do you handle data contracts? How do you handle data use agreements? So those are three areas we're focused on. How are you scaling go to market at this point? I mean, I presume you are. Yeah, well, I think as we're leveraging these types of engagements, so like our partners are the big cloud compute vendors, right, those data clouds. We're injecting as much as we can into them and helping them get more workloads onto their infrastructure because it benefits us. And then obviously we're working with GSIs and then RSI's to kind of help with this transformation, but we're all in. We're actually deprecating support of legacy connectors and we're all in on cloud compute. How did the pivot to all in on security, how did it affect your product portfolio? I mean, is that more positioning or was there other product extensions that where you had a test product market fit? Yeah, this comes out of customer drive. So we've been holding customer advisory boards across Europe, Asia, and US. And what we just saw was a pattern of some of these largest banks and pharmaceutical companies and insurance companies in the world was, hey, we need to understand who is actually on our data. We have a better understanding of our data now, but we don't actually understand why they're using our data. Why are they running these types of queries? Is this machine logic that we're running on this now? We invested all this money in AI. What's the risk? They just don't know. And so yeah, it's going to change our product portfolio. We modularized our platform to the street components over the past year, specifically now, so we can start building custom applications on top of it for specific users like the CISO, like the legal department, and like third-party regulators to come in as well as going back to data sharing to build data use agreements between one or many entities, right? So when SMP Global can expose their data to third parties and have one consistent digital contract, no more long memo that you have to read the contract, like a muta can automate those data contracts between one or many entities. And make it a checkbox item. It's just a checkbox, but then you can audit it all, right? Yeah, yeah. The key thing is this, I always tell people there's negligence and gross negligence. Negligence, you can go back and fix something, gross negligence, you don't have anything to put into controls. Regulators want you to be at least negligent. Gross negligent, they get upset, you know? Matthew, it sounds like great stuff that's going on at a mutated. Lots of money in the bank, and it sounds like a very clear and strategic vision and direction. We thank you so much for joining us on theCUBE this morning. Thank you so much. For our guests on Dave Vellante, I'm Lisa Martin. You're watching theCUBE's coverage of day two, Snowflake Summit 22, coming out alive from the show floor in Las Vegas. You right back with our next guest.