(tranquil music) >> Alation was an early pioneer in solving some of the most challenging problems in so-called big data. Founded early last decade, the company's metadata management and data catalog have always been considered leading examples of modern tooling by customers and analysts alike. Governance is one area that customers identified as a requirement to extend their use of Alation's platform. And it became an opportunity for the company to expand its scope and total available market. Alation is doing just that today, announcing new data governance capabilities, and partner integrations that align with the market's direction of supporting federated governance. In other words, a centralized view of policy to accommodate distributed data in this world of an ever expanding data cloud, which we talk about all the time in theCUBE. And with me to discuss these trends and this announcement is Satyen Sangani, who's the CEO and co-founder of Alation. Satyen, welcome back to the CUBE. Good to see you. >> Thank you Dave, It's great to be back. >> Okay, so you heard my open, please tell us about the patterns that you were seeing in the market and what you were hearing from customers that led you in this direction and then we'll get into the announcement. >> Yeah, so I think there are really two patterns, right? I mean, when we started building this notion of a data catalog, as you said a decade ago, there was this idea that metadata management broadly classified was something that belonged in IT, lived in IT and was essentially managed by IT, right? I always liken it to kind of an inventory management system within a warehouse relative to Amazon.com, which has obviously broadly published for the business. And so, with the idea of bringing all of this data directly to the business and allowing people arbitrarily, depending on their role to use the data. You know, you saw one trend, which was just this massive, shift in how much data was available at any given time. I think the other thing that happened was that at the same time, data governance went through a real transitionary phase where there was a lot of demand often spurred by regulations. Whether that's GDPR, CCPA or more recently than that, certainly the Basel accord. And if you think about all of those regulations, people had to get something in a place. Now what we ended up finding out was when we were selling in to add accounts, people would say, well guess what? I've got this data governance thing going on, but nobody's really using it. I built this business glossary, it's been three years. Nothing's been really very effective. And we were never able to get the value and we need to get value because there are so many more people now accessing and using and leveraging the data. And so with that, we started really considering whether or not we needed to build a formal capability in the market. And that's what we're today that we're doing. >> I liked the way you framed that. And if you think back, we were there as you were in the early big day-to-days. And all the talk was about volume, variety and velocity. And those are sort of IT concepts. How do you deal with all these technical challenges? And then the fourth V which you just mentioned was value. And that's where the line of business really comes in. So let's get into the news. What are you announcing today? >> So we're announcing a new application on top of Alation's Catalog platform, which is an Alations data governance application. That application will be released with our 2021.3 release on September 14th. And what's exciting about that is that we are going to now allow customers to discreetly and elegantly and quickly consume a new application to get data governance regimes off the ground and initiatives off the ground, much more quickly than they've ever been able to do. This app is really all about time to value. It's about allowing customers to be able to consume what they need when they need it in order to be able to get successful governance initiatives going. And so that's what we're trying to deliver. >> So maybe you could talk a little bit about how you think about data governance and specifically your data governance approach. And maybe what's different about Alation's solution. >> Yeah, I think there's a couple of things that are different. I think the first thing that's most critically different is that we move beyond this notion of sort of policy declaration into the world of policy application and policy enforcement, right? I think a lot of data governance regimes basically stand up and say, look you know, it's all about people and then process and then technology. And what we need to do is declare who all the governors are and who all the stewards are. And then we're going to get all our policies in the same place and then the business will follow them. And the reality is people don't change their workflows to go off and arbitrarily follow some data governance policy that they don't know exists, or they don't want to actually have to follow up. And so really what you've got to do is make sure that the policy and the knowledge exists as in where the data exists. And that's why it's so critical to build governance into the catalog. And so what we're doing here is we're basically saying, look, you could declare policies with a new policy center inside of Alation. Those policies will get automatically created in some cases by integrating with technologies like Snowflake. But beyond that, what we're also doing is we're saying, look, we're going to move into the world of taking those policies and applying them to the data on an automated basis using ML and AI and basically saying that now it doesn't have to be some massive boil the ocean three-year regime to get very little value in a very limited business loss rate. Rather all of your data sets, all of your terms can be put into a single place on an automated basis. That's constantly being used by people and constantly being updated by the new systems that are coming online. And that's what's exciting about it. >> So I just want to follow up on that. So if I'm hearing you correctly, it's the humans are in the loop, but it's not the only source of policy, right? The machines are assisting. And in some cases managing end-to-end that policy. Is that right? >> You've got it. I think the the biggest challenge with data governance today is that it basically relies a little bit like the Golden Gate Bridge. You know, you start painting it and by the time you're done painting it, you've got to go back and start painting it again, because it relies upon people. And there's just too much change in the weather and there's too much traffic and there's just too much going on in the world of data. And frankly in today's world, that's not even an apt analogy because often what happens is midway through. You've got to restart painting from the very beginning because everything's changed. And so there's so much change in the IT landscape that the traditional way of doing data governance just doesn't work. >> Got it, so in winning through the press release, three things kind of stood out. I wonder if we could unpack them, there were multi-cloud, governance and security. And then of course the AI or what I like to call machine intelligence in there. And what you call the people centric approach. So I wonder if we could dig in into these and help us understand how they fit together. So thinking about multi-cloud governance, how do you think about that? Why is that so challenging and how are you solving that problem? >> Yeah, well every cloud technology provider has its own set of capabilities and platforms. And often those slight differences are causing differences in how those technologies are adopted. And so some teams optimize for certain capabilities and certain infrastructure over others. And that's true even within businesses. And of course, IT teams are also trying to diversify their IT portfolios. And that's another reason to go multi-cloud. So being able to have a governance capability that spans, certainly all of the good grade called megascalers, but also these new, huge emerging platforms like Snowflake of course and others. Those are really critical capabilities that are important for our customers to be able to get a handle on top of. And so this idea of being cloud agnostic and being able to sort of have a single control plane for all of your policies, for all of your data sets, that's a critical must have in a governance regime today. So that's point number one. >> Okay and then the machine learning piece, the AI, you're obviously injecting that into the application, but maybe tell us what that means both maybe technically and from a business stand point. >> Yeah, so this idea of a data policy, right? Can be sometimes by operational teams, but basically it's a set of rules around how one should and should not be able to use data, right? And so those are great rules. It could be that people who are in one country shouldn't be able to access the data of another country, very simple role, right? But how do you actually enforce that? Like you can declare it, but if there is a end point on a server that allows you to access the data, the policy is effectively moot. And so what you got to go do is make sure that at the point of leverage or at the point of usage, people know what the policy happens to be. And that's where AI come in. You can say let's document all the data sets that happened to be domiciled in Korea or in China. And therefore make sure that those are arbitrarily segregated so that when people want to use that as datasets, they know that the policy exists and they know that it's been applied to that particular dataset. That's somewhere where AI and ML can be super valuable rather than a human being trying to document thousands of databases or tens of thousands of data sets, which is really kind of a (mumbles) exercise. And so, that application of automation is really critical and being able to do governance at the scale that most enterprises have to do it. >> You got it 'cause humans just can't do that at scale. Now what do you mean by people-centric approach? Can you explain that? >> Yeah, often what I find with governance is that there's this notion of kind of there's this heavy notion of how one should deal with the data, right? So often what I find is that there are certain folks who think, oh well, we're going to declare the rules and people are just going to follow them. And if you've ever been well, a parent or in some cases seeing government operate, you realize that that actually isn't how things work. And involve them in how things are run. And if you do that, right? You're going to get a lot more success in how you apply rules and procedures because people will understand that and people know why they exist. And so what we do within this governance regime is we basically say, look, we want to make sure that the people who are using the data, leveraging the data are also the people who are stewarding the data. There shouldn't be a separate role of data steward that is arbitrarily defined off, just because you've been assigned to a job that you never wanted to do. Rather it should be a part of your day job. And it should be something that you do because you really want to do it. And it's a part of your workflow. And so this idea of being people centric is all about how do you engage the analyst, the product managers, the sales operation managers, to document those sales data sets and those product data sets. So that in fact, those people can be the ones who are answering the questions, not somebody off to the side who knows nothing about the data. >> Yeah, I think you've talked in previous CUBE interviews about context and that really fits to this discussion. So these capabilities are part of an application, which is what? it's a module onto your existing platform. And it's sort of it's a single platform, right? I mean, we're not bespoke products. Maybe you can talk about that. >> Yeah, that's exactly right. I mean, it's funny because we've evolved and built a relation with a lot of capability. I mean, interestingly we're launching this data governance application but I would say 60% of our almost 300 customers would say they do a form or a significant part of data governance, leveraging relations. So it's not like we're new to this market. We've been selling in this market for years. What's different though, is that we've talked a lot about the catalog as a platform over the last year. And we think that that's a really important concept because what is a platform? It's a capability that has multiple applications built on top of it, definitionally. And it's also a capability where third party developers can leverage APIs and SDKs to build applications. And thirdly, it has all of the requisite capabilities and content. So that those application developers, whether it's first party from Alation or third party can really build those applications efficiently, elegantly and economically well. And the catalog is a natural platform because it contains all of the knowledge of the datasets. And it has all of the people who might be leveraging data in some fundamental way. And so this idea of building this data governance module allows a very specialized audience of people in governance to be able to leverage the full capabilities of the platform, to be able to do their work faster, easier, much more simply and easily than they ever could have. And that's why we're so excited about this launch, because we think it's one example of many applications, whether it's ourselves building it or third parties that could be done so much more elegantly than it previously could have been. Because we have so much knowledge of the data and so much knowledge of how the company operates. >> Irrespective of the underlying cloud platform is what I heard before. >> irrespective of the underlying cloud platform, because the data as you know, lives everywhere. It's going to live in AWS, it's going to live in Snowflake. It's going to live on-premise inside of an Oracle database. That's not going to be changed. It's going to live in Teradata. It's going to live all over the place. And as a consequence of that, we've got to be able to connect to everything and we've got to be able to know everything. >> Okay, so that leads me to another big part of the announcement, which is the partnership and integration with Snowflake. Talk about how that came about. I mean, why snowflake? How should customers think about the future of data management. In the context of this relationship, obviously Snowflake talks about the data cloud. I want to understand that better and where you fit. >> Yeah, so interestingly, this partnership like most great partnerships was born in the field. We at the late part of last year had observed with Snowflake that we were in scores of their biggest accounts. And we found that when you found a really, really large Snowflake engagement, often you were going to be complementing that with a reasonable engagement with Alation. And so seeing that pattern as we were going out and raising our funding route at the beginning of this year, we basically found that Snowflake obviously with their Snowflake Ventures Investment arm realized how strategic having a great answer in the governance market happened to be. Now there are other use cases that we do with Snowflake. We can certainly get into those. But what we realized was that if you had a huge scale, Snowflake engagement, governance was a rate limiter to customers' ability to grow faster. And therefore also Snowflake's ability to grow faster within that account. And so we worked with them to not only develop a partnership but much more critically a roadmap that was really robust. And so we're now starting to deliver on that roadmap and are super excited to share a lot of those capabilities in this release. And so that means that we're automatically ingesting policies and controls from Snowflake into Alation, giving full transparency into both setting and also modifying and understanding those policies for anybody. And so that gives you another control plane through which to be able to manage all of the data inside of your enterprise, irrespective of how many instances of Snowflake you have and irrespective of how many controls you have available to you. >> And again, on which cloud runs on. So I want to follow up with that really interesting because Snowflake's promise of the data cloud, is it essentially abstracts the underlying complexity of the cloud. And I'm trying to understand, okay, how much of this is vision, how much is is real? And it's fine to have a Northstar, but sometimes you get lost in the marketing. And then the other part of the promise, and of course, big value proposition is data sharing. I mean, I think they've nailed that use case, but the challenge when you start sharing data is federated governance. And as well, I think you mentioned Oracle, Teradata that stuff's not all in the cloud, a lot of that stuff on-prem and you guys can deal with that as well. So help us sort of to those circles, if you can. Where do you fit into that equation? >> I think, so look, Snowflake is a magical technology and in the sense that if you look at the data, I mean, it reveals a very, very clear story of the ability to adopt Snowflake very quickly. So any data team with an organization can get up and running with the Snowflake instance with extraordinary speed and capability. Now that means that you could have scores, hundreds of instances of Snowflake within a single institution. And to the extent that you want to be able to govern that data to your point, you've got to have a single control plane through which you can manage all of those various instances. Whether they're combined or merged or completely federated and distinct from each other. Now, the other problem that comes up on governance is also discoverability. If you have all these instances, how do you know what the right hand is doing if the left hand is working independently of it? You need some way to be able to coordinate that effort. And so that idea of discoverability and governance is really the value proposition that Alation brings to the table. And the idea there is that people can then can get up and running much more quickly because, hey, what if I want to spin up a Snowflake instance, but there's somebody else, two teams over those already solved the problem or has the data that I need? Well, then maybe I don't even need to do that anymore. Or maybe I can build on top of that work to be able to get to even better outcome even faster. And so that's the sort of kind of one plus one equals three equation that we're trying to build with them. >> So that makes sense and that leads me to one of my favorite topics with the notion is this burgeoning movement around the concept of a data mesh in it. In other words, the notion that increasingly organizations are going to push to decentralize their data architectures and at the same time support a centralized policy. What do you think about this trend? How do you see Alation fitting in? >> Yeah, maybe in a different CUBE conversation. We can talk a little bit about my sort of stylized history of data, but I've got this basic theory that like everybody started out what sort of this idea of a single source of truth. That was a great term back in the 90s where people were like, look, we just need to build a single source of truth and we can take all of our data and physically land it up in a single place. And when we do that, it's going to all be clean, available and perfect. And we'll get back to the garden of Eden, right? And I think that idea has always been sort of this elusive thing that nobody's ever been able to really accomplish, right? Because in any data environment, what you're going to find is that if people use data, they create more data, right? And so in that world, you know, like that notion of centralization is always going to be fighting this idea of data sprawl. And so this concept of data mesh I think is, you know, there's formal technical definitions. But I'll stick with maybe a very informal one, which is the one that you offered. Which is just sort of this decentralized mode of architecture. You can't have decentralization if nobody knows how to access those different data points, 'cause otherwise they'll just have copies and sprawl and rework. And so you need a catalog and you need centralized policies so that people know what's available to them. And people have some way of being able to get conformed data. Like if you've got data spread out all over the place, how do you know which is the right master? How do you know what's the right customer record? How do you know what's your right chart of accounts? You've got to have services that exist in order to be able to find that stuff and to be able to leverage them consistently. And so, to me the data mesh is really a continuation of this idea, which the catalog really enabled. Which is if you can build a single source of reference, not a single source of truth, but a single place where people can find and discover the data, then you can govern a single plane and you can build consistent architectural rules so that different services can exist in a decentralized way without having to sort of bear all the costs of centralization. And I think that's a super exciting trend 'cause it gives power back to people who want to use the data more quickly and efficiently. >> And I think as we were talking about before, it's not about just the IT technical aspects, hey, it works. It's about putting power in the hands of the lines of business. And a big part of the data mesh conversation is around building data products and putting context or putting data in the hands of the people who have the context. And so it seems to me that Alation, okay, so you could have a catalog that is of the line of businesses catalog, but then there's an Uber catalog that sort of rolls up. So you've got full visibility. It seems that you've fit perfectly into that data mesh. And whether it's a data hub, a data warehouse, data lake, I mean, you don't care. I mean, that's just another node that you can help manage. >> That's exactly right. I mean, it's funny because we all look at these market scapes where people see these vendor landscapes of 500 or 800 different data and AI and ML and data architecture vendors. And often I get asked, well, why doesn't somebody come along and like consolidate all this stuff? And the reality is that tools are a reflection of how people think. And when people have different problems and different sets of experiences, they're going to want to use the best tool in order to be able to solve their problem. And so the nice thing about having a mesh architecture is you can use whatever tool you want. You just have to expose your data in a consistent way. And if you have a catalog, you can be able to have different teams using different infrastructure, different tools, different fundamental methods of building the software. But as long as they're exposing it in a consistent way, it doesn't matter. You don't necessarily need to care how it's built. You just need to know that you've got good data available to you. And that's exactly what a catalog does. >> Well, at least your catalog. I think the data mesh, it should be tools that are agnostic. And I think there are certain tools that are, I think you guys started with that principle. Not every data catalog is going to enable that, but I think that is the trend Satyen. And I think you guys have always fit into that. It's just that I think you were ahead of the time. Hey, we'll give you the last word. Give us the closing thoughts and bring us home. >> Well, I mean that's exactly right. Like, not all the catalogs are created equal and certainly not all governance is created equal. And I think most people say these words and think that are simple to get into. And then it's a death by a thousand cuts. I was literally on the phone with a chief data officer yesterday of a major distributor. And they basically said, look, like we've got sprawl everywhere. We've got data everywhere. We've got it in every type of system. And so having that sophistication turned into something that's actually easy to use is a super hard problem. And it's the one that we're focused on every single day that we wake up and every single night when we go to sleep. And so, that's kind of what we do. And we're here to make governance easy, to make data discovery easy. Those are the things that we hold our hats on. And we're super excited to put this release out 'cause we think it's going to make customers so much more capable of building on top of the problems that they've already solved. And that's what we're here to do. >> Good stuff, Satyen. Thanks so much, congratulations on the announcement and great to see you again. >> You too, Dave. Great talking. >> All right, thanks for watching this CUBE conversation. This is Dave Vellante, we'll see you next time. (tranquil music)

(upbeat music) >> Announcer: From theCUBE studios in Palo Alto, in Boston connecting with all leaders all around the world, this is theCUBE conversation. >> Lisa Martin here with theCUBE conversation. One of our alumni is joining me Satyen Sangani the CEO and Co-Founder of Alation is back. Satyen, it's great to see you this morning. >> I know it's so great to see you especially so soon after we last talked. >> Yeah, we only spoke a couple of months ago when you guys launched the Alation Cloud Service and now big news raising 110 million in Series D led by Riverwood Capital from participation with some new investors, including Snowflake Ventures. Talk to us about this new funding raise. >> Yeah, it's so funny. I mean, we've seen market demand pick up ever since the sort of tail end of last year. And it's just been incredible. And quarter after quarter we keep on hitting and exceeding our numbers and we keep on hiring faster and faster and faster and it just doesn't seem like it's ever been fast enough. And so we've been aggressive since the beginning of the year. And even actually before that in spending and, taking the company from roughly 275 people at the end of the year to now, by the end of this year, 525 people. So with that kind of growth we definitely wanted to have the capital to, carry us to this year and then certainly beyond. And, so we went out and raised around and, obviously we're able to do that on great terms and to find a phenomenal partner in Riverwood. And so super excited about the outcome. >> Exactly saw a lot of demand as you and I talked about just a couple of months ago the acceleration of the business during the pandemic. Talk to me about, as you mentioned the demand has never been higher. Let's talk about the demand for the data intelligence platform how the funding is going to help. What are some of the things that you're specifically going to do? >> Yeah, so there's you know we're going to grow the business in a pretty balanced way. And so from our perspective, that means a couple of things right? So starting with sales and marketing, we've got just a need for more feet on the street. Everybody understands generally that they've got problems in data governance, data management, data search and discovery, enablement to people around data. These are things that people are now starting to understand but they don't always necessarily know how to solve the problem in the most efficient and best way. And many of the traditional approaches that sort of command and control top down, you know, let's go hire an army of consultants to figure this stuff out, tends to be the first thing that comes to mind. And so we're building our sales organization is one thing that we're going to do. The second thing that we're going to do is invest in our customer success and customer journey because everybody's looking for best practice and last but not least workforce investing in product and R&D. And so we're going to be growing the R&D organization by almost a factor of two, and that's going to be globally. And, just being the best in the market means you've got to still solve all these unsolved problems. And we're going to do that. >> Sounds like a tremendous amount of momentum kind of igniting this next era for Alation. When we talk about customers, I love that you're doubling down on the customer success. That's absolutely critical. That's why you're in business. But one of the things that we talk about with customers in every industry is being data-driven. And as we see data intelligence emerging as a very, very critical technology investment to enable an enterprise to become more data-driven or actually data-driven, what are some of the things that you're seeing that those customers are saying Alation help us with XYZ? >> Yeah, so I think everybody feels like they need to be on this. So let's first of all, talk about data intelligence. Like, what is this category? So historically there has been these sort of data management categories where the general approach has been let's curate or manage or clean the data in this manual way in order to be able to get good data in front of people so they can start to use it, right. And that data cleaning, that data work that data stewardship has lived often in IT sometimes with very technical people in the business. And it just doesn't scale. There's just too much data out there and there's too much demand for data. So the demand for data is increasing, the supply for data is increasing. So now there's this category of data intelligence. And basically what it's doing it's saying, look all these things that we're talking about machine learning, AI, all of that can be applied to actually the management of data. People can be way more intelligent about how they do this work. They can be more intelligent how they search. They can be more intelligent about how they curate the data. And so what we're seeing is that people are saying, look, I've got so much data. My entire business relies upon data, and now I need you Alation or somebody to help me do this better to do this faster, to do this more efficiently. And all of these really traditional approaches where you use, you know, predominantly workflows and all this stuff it's just not working. And so that's why people are coming after us. >> Well, that need for data in real time is something that we saw during the pandemic. It's for many industries and many different types of situations. It's no longer a nice to have. It's really going to be the defining element between those businesses that succeed in really kind of leveraged COVID as an accelerant versus those that don't succeed. But I'm curious where your conversations are going within the customer base. As we see the need for data across an organization, but the need to access data that they can trust quickly, data that tells the truth, data that can be shared. Are you seeing this elevate up to C-suite in terms of your customer conversations? >> Yeah, and it is and it is because of one really critical reason because a lot of these data projects both fail and under exceed expectations and they do it for reasons that the C-suite doesn't understand. And so now the C-suite is getting forced to say, well, why is this happening? Why are these not going like, wow, you know the boardroom is saying like, well, we need to do more AI. Well, why aren't we doing more AI? Well, it's 'cause your data isn't really clean 'cause you don't actually have the data that you think you have. Because people don't share your data because people are, you know, your data is locked in some on-premise instance in, some access database that nobody's ever heard of. And so all of these reasons are things that now because they're impeding the business or getting to more senior levels in the organization >> That's kind of what I was thinking. I want to talk now about the investment this particular Series D that we talked about. So you've got investment, as I mentioned from a couple of new partners, but talk to me about the Snowflake and the Salesforce Ventures and how that is helping to catalyze what Alation is doing. >> Yeah, so we've, you know had a long time relationship with Salesforce but we found in the last year in particular that our relationship with Snowflake has just taken off in a way that I have seen few partnerships taking off in in certainly in my career. And, you know, it started really with just scores of customers. I mean, literally scores of customers that are all global to 1000s and fortune 500s where we would often just say, hey, what's your data source. And, you know, let's start with Alation and they'd be like, yeah we are either about to invest in Snowflake or we're invested in Snowflake or, something like that. So we'd often see customers on the journey with Snowflake and Alation at the exact same time. And then the next order conversation became well, you know if we're expanding and rolling out with Snowflake, which customers, you know, everybody looks at Snowflakes 168 net percent net expansion rate where every customer is spending a dollar 68 more than they were last year on average. And, you know, says, wow, if I'm going to scale that much we need to govern all of that data. And so Snowflake customers came to Snowflake and to Alation at the same time, and we've been the natural solution of choice. And so that kind of marriage has been quite symbiotic and we're super excited to partner with them. You know, they think exclusively about data consumption. We think about, you know, finding, discovering understanding data. So it's a really natural marriage. And so we're really excited to partner with them and you're going to see a lot from the two companies moving forward. >> So it sounds like that really was driven from joint customers in terms of facilitating maybe an expansion of the partnership that Alation and Snowflake have. Talk to me a little bit more about what some of the things are that we can expect in the next year. >> Yeah, so I won't take away from the stories that we're about to release, but you are going to see really exciting innovations and product between Snowflake and Alation over the course of the next couple of months. And in particular, you're going to see, you know some fun announcements at the snowflake summit coming up next week. So stay tuned for that. Not surprisingly data governance is going to be a big topic for us. Data search and discovery is going to be a big topic for us. Data privacy and security is going to be a big topic us. And so those are all areas where you're going to see lots of fun products innovation. And then on the other side, you're going to see a lot of go to market innovation. So customers are moving data to the cloud, obviously and that's going to be a big place of discussion just enabling all of the field sales forces getting the stories and the customer stories to market. You're going to see a lot of that from us. >> In the last year, I'm curious if you saw any verticals in particular that really have pivoted with fuel from Alation. I think healthcare, life sciences, manufacturing anything that you, that really stood out to you in the last year >> You know, it's, I mean I think there's been the pandemic certainly hurt certain industries more than others transportation, travel and hospitality. And so we definitely saw a trend where there were dips in some of those industries but those were really temporary. And what we're finding is in a lot of those industries are now coming back bigger than ever. And the other industries in manufacturing and pharma in financial services, you know those are just as strong as they've ever been. And interestingly through the pandemic, what we found is that our user account within the company doubled. So even though the customer base itself didn't double the number of users on the platform across all of our customers, literally doubled on an active basis. And so, it's just been, interestingly enough it's just that across the board the growth has been consistent. And I think, really speaks to the fact that everybody's working from home and needs more data to do their job. >> Well, hopefully that's something that's going to be temporary. This, I was telling you, this is my first day back in the studio and not sitting in the home office. So in terms of the demand we talked about the demand we're customers, you're more than 250 customers now, big names, including one of the I think last year's most used terms household terms of Pfizer. Talk to me about the customer perspective on the funding and in terms of the things that you're going to be able to do to go to market. What are you hearing from your customer? >> Yeah I mean, literally the first thing I hear from 80 to 90% of my customers is go faster. You know, like there's this fun story, right? Where there's two people, they meet in the forest, they start walking together and then all of a sudden they both see a big bear. And the bear is, right about to come right after them. One person sits down and like puts on their running shoes. And they're like, well, you know, the other guy says, oh, there's no way you're going out run the bear. And they're like, well, I (indistinct)the bear. I've got to out run you. Right, and our customers are basically saying to us, look the bear of the data problem is gigantic. And yeah, you might be better than everything else out there, but I still have to as a customer contend with this massive data problem. And you know, if I have to do that, I need you to go faster because data's coming after me faster than ever. And I've got to contend with all of that work. And so they just want us to go faster and they want us to go faster in product. And they want us to go faster in developing the customer journey. And they want us to go faster in developing the ecosystem because many of our customers are you leveraging us as a platform. They want to see data on top of Alation. They want to see data privacy on top of Alation. They want to see data migration on top of Alation. So building out all these capabilities with our partners in our ecosystem and with partners like Snowflake and Salesforce, I mean, they just want us to move faster >> Moving faster, I think we all want that in certain senses but in any industry, consumers, users are getting more and more demanding as you're helping customers achieve their desire of going faster. How do you do that and help them foster a data culture that's, that supports that speed. >> Yeah, it's so interesting because cultural transformation, as you all know, like as we all know, that's like that's certainly slow work, right? Like you're not going to show up at an enterprise and say, hey, I installed Alation. You know what? You're going to have a totally different area culture. Everybody's going to start asking questions with data and the world's going to change, right. And so that, that, you know I'd love for that to be the eventual vision that we achieve. But it's certainly not where we are at today. I think, one of the things that I believe is that you can't go fast and big things you've got to break up big problems and turn them into small problems. And so one of the habits that we've seen within the organization, and one of the things that I talked to our team about every single day is look, you know make small promises and deliver on them. If you got to connect to data source, do that faster. If you're going to train a set of employees do that more quickly because customers have intent with data, but if they don't get the data in front of themselves quickly then they're just going to go to their gut decision. And so capturing that moment of intent and building a sort of velocity is where we see our best customer engagements go. And so that sort of incremental success approach, as opposed to the boil the ocean three month engagement, you know never see the finish line approach is really what I think makes us special and different. >> Tell me a little bit about speaking of culture, about Alations culture. What are some of the things that have changed in the last year? And it sounds like with the Series D round that you've just raised a lot of growth opportunities you mentioned that. Talk to me about the culture, how it's transformed in the last year and what you are excited for going forward. >> Yeah, it's so funny 'cause I always think about culture. You know, people think about culture and they say, companies (indistinct) culture and they think of that culture as being a fixed thing. And it's totally true that, yeah, there's got to be some shared vision, shared values shared ideals within a company in order for it to grow at the pace that we're growing, right. Adding 250 people in a 12 month period is not easy. But it's also the case that, you know, what we found is that there's a lot more specialization within the company. And so people now really, you know where you found the company on generalist you scale a company on specialists. And so getting those specialists inside of the company and respecting them and letting them do their jobs and really kind of building that expertise in the company is something that's been really fabulous and just wonderful to see the team work that way. I think the other thing that's been really interesting obviously is just the remote first work. I mean, we've seen zero loss in productivity and I've talked to CEOs who were like, yeah we need to get people back in the office. I don't really care where my team works. They're getting the job done and they're doing it fabulously for customers. And so if customers want them in front of them, totally great. Obviously love to see the team all the time but it is so wonderful to see how productive people can be when they don't have to spend two hours in a car every day. And so those have been two small things. I mean, at the core, there are other aspects of our culture that have been more permanent, but those two have been slightly different. >> That's great to hear that about the productivity. I was actually very excited to commute this morning for the first time. Although there was no traffic to navigate. As we look at the current market valuation, 1.2 billion the growth rate, the demand for the technologies. What are some, you mentioned some of the events that you're going to be at you mentioned Snowflakes event. Where can folks go to hear more information about this? >> Yeah, absolutely. You can come to our website, of course, at alation.com. There's a ton of information there. Anybody who's watching this interview obviously is a experienced and thoughtful enterprise IT buyers. So certainly, you know, this is a fairly expert audience but we do have tons of field resources that are available. The Alation Cloud instance allows you to get up and running super quickly. And you're going to see that speed increase further over the coming 12 months, but, you know start with alation.com and go from there. And then there's a whole bunch of people who are sitting behind that front door waiting to help you. >> Excellent, alation.com. Well, Satyen congratulations on the funding announcement. Thank you for joining me today helping us unpack what at means the impact, the demand from the customers and how we're going see Alation go even faster. I'm excited to see what happens next in the next couple of months. I'm sure I'll see you again. >> I know. Me too. Thank you Lisa, it's always great to talk. >> Likewise, for Satyen Sangani, I'm Lisa Martin. You're watching this CUBE conversation. (upbeat music)

>> Hello everyone. Welcome to this Cube conversation here in Palo Alto. On John Furrier, co host of the Cube. I'm here. Aaron Kalb is the co founder and VP of design and Alation. Great to see them on some fresh funding news. Aaron, Thanks for coming. And spend the time. Good to see you again. >> Good to see you, John. Thanks for having me >> So big news. You guys got a very big round of financing because you go to the next level. A startup. Certainly coming out that start up phase and growth phase super exciting news. You guys doing some very innovative things around, date around community around people and really kind of cracking the code on this humanization democratization of data, but actually helping businesses. I want to talk about it with you. First. Give us the update on the financing, the amount what it means to the company. A lot of cash. >> Yeah. So we're very excited to have raised a fifty million dollar round. Sapphire led the round, and we also had, you know, re ups from all of our existing investors. And, you know, as as a co founder, he always had big dreams for growth. And it's just validating tohave. Ah, a community of investors who can see the future, too, as well as our great community of over one hundred customers now who want to build this data democratized future with us. >> We've been following you guys since the founding obviously watching you guys great use of capital. Fifty million's a lot of capital, so obviously validation check. Good, good job. But now you go to a whole other level growth. What's the capital gonna be deployed for? What's going on with company where you guys I and in terms of innovation, what's the key focus? >> It's a great question. So you know, obviously we have revenue from our customers. But getting this extra infusion from VC lets us just supercharge our development. It's growth. It's going to more customers, both domestically and abroad, goingto a broader user base. And we're Enterprise-wide Adoption within those customers, as well as innovation in the core product, new technology, great design and futures. that are really going to change the organization's access and use data to make better decisions? >> What was the key Learnings As you guys went into this round of funding outside the validation to get through due diligence, all that good stuff. But you guys have made some successful milestones. What was the key? Notable accomplishments that Alation hit to kind of hit this trigger point here for the fifty million? >> Yeah, I'm glad you asked about that. I think that the key thing that's changed it's enabled this. This next phase is that the data catalog market has really come into its own right. In the beginning, in the early days, we were knocking on doors, trying to say, You know, we don't even know it was going to be called data catalog in our first few months. And even though we had the technology, we said, Hey, we got this thing and we know it's useful. Please buy it. Please want it. And the question was, you know, what's the data catalog by what I ever even look at that? And it's just turned a corner. Now, you know, Thanks. In part of things like Gartner telling companies you know, in the next year by twenty twenty, if you have a data catalog, you're goingto see twice the ROI from your existing data investments than if you don't your stories like that are making companies say? Of course, you want to data catalog. It just turned out a dime. Now they're asking, Which data catalog should we get? Why is yours the best in this change of the market maturing? I think it's the biggest change we've seen >> with one thing that we've observed. I want to get your reaction to This is that I'll stay with cloud computing economics, a phenomenally C scale data data science working the cloud. We see great success there. Now there's multiple clouds, multi clouds, a big trend, but also the validation that it's not just all cloud anymore. The on premises activity steel is relevant, although it might have a cloud. Operations really kind of changes the role of data. You mentioned the data catalogue kind of being kind of having a common mainstream visibility from the analysts like Gardner and others on Wiki Bond as well. It makes data the center of the innovation. Now you have data challenges around. Okay, where's the data deployed? Where my using the data? Because data scientists want ease of data, they want quality data. They want to make sure their their algorithm, whether it's machine learning component or software actually running a good data. So data effectiveness is now part of the operations of most businesses. What's your reaction to that? Which your thoughts. Is that how you see it? Is there something different there? What's going on with the whole date at the center? >> Absolutely hit on two key themes for us. One of that idea of the center and the other is your point about data quality and data trust. So, so centrality, we think, is really essential. You know, we're seeing cataloging technology crop up more and more. A lot of people were coming out with catalogs or catalog kind of add ons to their products. But what our customers really tell us is they want the data catalog to be the hub, that one stop shop where they go to to access any data, wherever it lives, whether it's in the cloud or on Prem, whether it's in a relational database or a file system, so is one of Alations key. Differentiators early on was being that central index, much like Google is out of the front page to the Internet, even though it's linking to ad pages all over the place. And the other thing in terms of that data quality and data trustworthiness has been a differentiator, and this was something that was part of our technology when we launched that we didn't put the label out till later. Is this idea of Behavior IO, that's kind of looking at previous human behavior to influence future human behavior to be better. And there's another place we really took some inspiration from Google and Terry Winograd at Stanford before that, you know, he observed. You know, if you remember back before Google search sucked, frankly, right, the results on top are not the most development were not the most trustworthy. And the reason was those algorithms were based on saying, how often does your key word appear in that website? Built, in other words, and so you'd get results on top. That might just not be very good. Or even that were created by spammers who put in a lot of words to get SEO and and, you know, that isn't the best result for you on what Google did was turned that around with page rank and say, Let's use the signals that other people are getting behind about the pages they find valuable to get the best result on top. And Alation is the exact same thing our patented proprietary behavior technology lets us say Who's using this data? How were they using it? Is it reputable? And that enables us to get the right data and transfer the data in front of decision makers. >> And you call that Behavioral IO >> Behavior IO, that's right. >> I mean, certainly remember Google algorithmic search was pooh poohed. It first had to be a portal. Everyone kind of my age. You can't remember those those days and the results were key word stuff by spammer's. But algorithmic search accelerated the quality. So I got to ask you the behavioral Io to kind of impact a little bit. Go a little deeper. What does that mean for customers? Because now I'll see as people start thinking, OK, I need to catalogue my data because now I need to have replication, all kinds of least technical things that are going on around integrity of the data. But why Behavioral Aya? What's the angle on that? What's the impact of the customer? Why is this important? Absolutely so. >> Might have to work through an example, you know we joke about. You might be looking around in your SharePoint drive and find an Excel file called Q three Numbers final. Underscore final. Okay, that seems that'S inject the final numbers, and then you see next to it when it says underscore final underscore, final underscore finalist. Okay, well, is that one final? And it turns out what Data says about itself is less reliable than what other people say about the data. Same thing with Google that if everyone's linking with Wikipedia Page, that's a more reliable page than one that just has, you know, paid for a higher placement, Right? So what a means an organization is with Alation will tell you. You know, this is the data table that was refreshed yesterday and that the CFO and everybody in this department is using every day. That's a really strong signal. That's trustworthy data, as opposed to something that was only used once a year ago. >> So relevance is key there. >> Absolutely. It's relevant. And trustworthiness. We find both all right, indicated more strongly by who's using it and how than by the data itself. >> Are you seeing adoption with data scientist and people who were wrangling date or data analysts that if the date is not high quality, they abandoned. The usage is they're getting kind of stats around that are because that we're hearing a lot of Hey, you know, that I'm not going to really work on the data. But I'm not going to do all the heavy lifting on the front end the data qualities, not there. >> Absolutely. We see a really cool upward spiral. So in Alation, we have a mix of manual, human curated metadata, you know, data stewards and that a curator saying, this is endorsed data. It's a certified data. This is applicable for this context. But we also do this automatic behavior. Io. We parse the query logs. These logs were, you know, put there for audit on debugging purposes. But we were mining that for behavioral insight, and we'll show them side by side on what we see is overtime on day one. There's no manual curation. But as that curation gets added in, we see a strong correlation between the best highest quality data and the most used data. And we also see an upward spiral where, if on day one. People are using data that isn't trustworthy that stale or miscalculated as soon as Ah, an Alation steward slaps a deprecation or a warning on the data asset because of technology like trust check talking about last time I was here, that technology, that's the O part of behavior IO We then stop the future behavior from being on bad data, and we see an upward spiral where suddenly the bad sata is no longer being used and everyone's guided put the pound. >> One thing I'm really impressed with you guys on is you have a great management team and overall team with mixed disciplines. Okay, I think last night about your role, Stanford and the human side of the world. But you have to search analogy, which is interesting because you have search folks. You got hardcore data data geeks all working together. And if you think about Discovery and navigation, which is the Google parent, I need to find a Web page and go, Go, go to it. You guys were in that same business of helping people discover data and act on it or take action. Same kind of paradigm, so explain some customer impact anecdotes. People who bought Alation, what your service and offering and what happened after and what was it like before? We talk about some of that? And because I think you're onto something pretty big here with this discovery. Actionable data perspective. >> Yeah, well, one of our values, it Alation, is that we measure our success through customer impact, you know, not do financing or other other milestones that we are excited about them. So I I would love to talk about our customers. One example of a business impact is an example that our champion at Safeway Albertsons describes where, after safe, it was acquired by Albertson's. They've been sort of pioneers of sort of digital, ah, loyalty and engagement. And there was a move to kind of stop that in its tracks and switch should just mailing people big books of coupons that of customizing, you know, deals for you based on your buying behavior. And they talked about getting a thirty x  ROI on the dollars they've spent on Alation by basically proving the value of their program and kind of maximizing their relationship with their customers. But the stories they're even more exciting to me, then just business impacts in dollars and cents when we can leave a positive impact on people's lives with data. There's a few examples of that Munich reinsurance, the biggest being sure and also a primary ensure in Europe, had some coverage and Forbes about the way that they use Alation, other data tools to be able to help people get back on their feet more quickly after, ah, earthquakes and other natural disasters. And similarly, there's a piece in The Wall Street Journal about how Pfizer is able to create diagnostics and treatments for rare diseases where it wouldn't have been a good ROI even invest in those if they didn't get that increased efficient CNN analytics from Alation on the other data. >> So it's not just one little vertical. It's kind of mean data is horizontally. Scaleable is not like one. Industry is going to leverage Alation, >> Absolutely so you know, I mentioned just now. Insurance and health care and retail were also in tech were in basically every vertical you can imagine and even multiple sectors. You know, I've been focusing on industry, but there's another case that you can read about at the city of San Diego were there. They're doing an open data initiative, enabling people to figure out everything from where parking is easiest, the hardest to anything else. >> The behavioral Io. And it's all about context and behavior, role of data and all this. It's kind of fundamental to businesses. >> That's right. It's all about taking everything about how people using data today and driving people to be even more data driven, more accurate, better able to satisfy their curiosity and be more rational in >> the future. So if I'm a from a potential customer and I heard a rAlation, get the buzz out there, why would I need you? What air? Some signals that would indicate that I should call Alation. What's some of that Corvette? What's the pitch? >> Yeah, it's a great question. No, I sometimes joke with the team that you know every five minutes another enterprise reaches that point where they can't do it the old way anymore. And the needle ations. And the reason for that is that data is growing exponentially and people can only grow at most, you know, linearly. So I compare it a bit again to the days of of Yahoo When the Internet was small, you make a table of contents for it. But as there came to be trillions of red pages, you needed an automatic index with pay drink to make sense of it. So I would say, once you find that your analytics team has spread out and they're spending, you know eighty percent of their time calling up other people to find where development data is, you're asked to Your point is this data high quality show even spend my time on it? You know that's probably not money is well spent with these highly paid people spending other times scrounging If you switch from scrounging to finding understanding and trusting their data for quick and accurate analysis, give us >> a call. So basically the pitches, if you want to be like Yahoo, do it the old way. We know what happened. Yeah, you want to be like Google, two algorithmic and have data >> God rAlation, and you'll be around for a while very well. After that, maybe the one see that that's my words. >> And and that's part of turning that corner. I think in the beginning we were trying to tell people this could be a nice toe have. And now customers are coming to us realizing it's a must have to stay a relevant, you know, And if you've made all these investments in data infrastructure and data people, but you can't connect the dots is you said, between the human side and the tech side that money's all wasted and you're going to not be able to compete against your competitors and impact of customers what you want. >> Well, Eric, congratulations. Certainly is the co founder. It's great success. And how hard is that you start ups? You guys worked hard and again. Why following you guys? Been interesting to see that growth and this innovation involved in creative, A lot of energy. You guys do a good job. So final question, talk about the secret sauce of Alation. What's the key innovation formula? And now that you got the funding where you're going to double down on, where's the innovation going to come next? So the innovation formula and where the innovation, the future, >> absolutely innovation has been critical for us to get here on our customers didn't just buy the exciting features with behavioral and trust. Check that we had but also are buying into the idea that we're going to continue to be the leaders and to innovate. Andi, we're going to do that. So I think the secret sauce which we've had in the past, we're going to continue to innovate in this vein, is to be really conscious of water computers great at and what humans uniquely good at what you humans like doing and trying to have the human and computers work together to really help the human achieve their goals. Right? So, Doctor, the Google example. You know, there's a bunch of systems for collaboratively ranking things, but it takes work to, you know, write a review on the upper Amazon. Google had the insight that we could leverage people are already doing and make it about it. Out of that, we're going to continue to do that. >> The other kind of innovation you'll see is bringing Alation to a wider and wider audience, with less and less technical skill needed. So I came from Syria Apple, and the idea is you have to learn a programming language to Queria database. You could just speak in English. That helps you ask answer questions like What's the weather today? Imagine taking that same kind of experience of seamless integration to the more important questions enterprises are asking. >> We'll have to tap your expertise is we want to have an app called the Cube Syria, which is a cube. What's the innovation in Silicon Valley and have it just spit out a video on the kidding? Final question just to double down on that piece, because I think the human interactions a big part of what you're saying I've always loved that about with your vision is. But this points to a major problems. Seeing whether it's, you know, media, the news cycle These days, people are challenging the efficacy of finding the research and the real deep research on the media. So I was seeing scale on data scale is a huge challenge. You mentioned the growth of data. Computers can scale things, but the knowledge and the curation kind of dynamic of packaging it, finding it, acting on it. It's kind of where you guys are hitting. Talk about that tie name, my getting that right and set is that important? Because, you know, certainly scale is table stakes these days. >> That is super insightful John, because I think human cognition and human thought excuse me, is the bottleneck four being data driven right we have on the Internet trillions of Web pages, you know, more than the Library of Alexandria a hundred times over, and we have in databases millions of columns and trillions of rose. But for that to actually impact the business and impact the world in a positive way, it's got to go through a person who could understand it. And so, in the same way that Google became the mechanism by which the Internet becomes accessible, we think that Alation for organizations is becoming the way that data can become actionable. And the other thing I would say is, you know, in this age of alternative facts and mistrust of data, you know, we've sort of realizing the just having more information out there doesn't actually make people wiser and better able to reason. It can actually be a lot of noise that muddies the signal and confuses people. So we think Alation by also using human computer interaction to help separate the signal from the noise and the quality from the garbage can help stop the garbage in garbage out and make people more rational and more curious and have more trust than what there. Hearing understanding >> build that Paige rang kind of metaphor is interesting because the human gestures, whether it's work or engaging on the data, is a signal tube, not just algorithmic meta data extraction. >> Absolutely anything you do with data and any tool, even outside of Alation. Alation will capture that and use it to guide future behavior for you and your appears to be better and smarter. >> Fifty million dollars. Where's this all going to lead to wins the next innovation. What do you guys see? The future for rAlation? >> Well, you know, I, uh I was just thinking before the show I used to be an apple kind of in the golden Age when Apple was really innovative. And there was the joke where they released something new and say, Redman, start your photocopier. So in this interview, I'm going to be a little close to the chest about the specifics, but we're releasing. But I will tell you we have a room that we're really excited about to go to a broader and broader audience that impactor customers more fully >> well you feel free to say one more thing? >> Yeah. I think the secret to the future is Aaron. Thanks for coming on. >> Really preachy. Congratulations on the funding. He has got a very innovative formula. Good luck. And we'll be following you guys. Thanks, but come on, keep commerce. Thanks so much. Eric Kalb, co founder and VP of designing Alation. Interesting formula. Great. Successful. Former great innovation. Alation. Check him out. I'm Jennifer here in Palo Alto for cube conversation. Thanks for watching.

>> Announcer: Live from Las Vegas, it's theCUBE. Covering AWS Reinvent 2017, presented by AWS, intel, and our ecosystem of partners. >> Welcome back to theCUBE's continuing coverage of AWS Reinvent 2017. This is day two for us. Incredible day one. We had great buzz on day two. Great announcements coming out from AWS today. I'm Lisa Martin with my cohost Keith Townsend, and we're excited to be joined by CUBE alumni, Aaron Kalb, the head of product and a founder of Alation. Welcome back to the show. >> Thanks so much for having me. I'm excited to be here. >> So speaking of excitement, you can hear the buzz behind us. Interesting about Alation, the first data catalog designed for human collaboration. What gap did Alation see in the market five years ago when you started? >> That's a great question, Lisa. So, yeah, we're the first data catalog, period, and we're excited to see a lot of other people kind of using that label, I believe it validates this as a space, and I think that everybody needs, and I think our approach, as you said, was to really to approach it from the human side, to say the data might be generated by machines or stored on machines, but it's not meant to ultimately be consumed by machines. Even if there's algorithms that's pulling it in, it's to ultimately serve human interests. So the goal was to design from the human back and really think, what does this data mean? Can I trust it? Is it gonna drive the processes correctly? >> So Aaron, I have seen that term quite a bit, and data catalog, for me, means one specific thing. Can you kind of wrap that up for us? >> What is a data catalog? >> That's a really great question, Keith, and I think what's interesting is we took a lot of inspiration in the early days actually from Amazon.com, right? So Amazon is an amazing modern product catalog. You can go in, type in English and see a variety of products that match that keyword. And for each one you can see whose bought it before, how many stars did they give it? Is it good? So it helps you find, understand, and trust, and get the right product for your need. We want to do that same thing for data. How do you found a trustworthy data asset, understand what it is, and put it to use? So that's exactly the goal. >> So, a simple problem is I've worked with a ton of researchers in the Big Pharma industry, data across the world basically. And a lot of data sets, repetitive. A team in Germany is working with one set of data, team in New Jersey working with another one, how does your solution help those researchers find the data that they're looking for? >> Exactly right. So the problem is many different data sets, many different things claiming to be true. Some of them are just plain wrong. Sometimes the answer might be one thing in Germany but something else elsewhere, and they're both valid. And so you've hit the nail on the head. The way people use data contains a lot of hints about the way you should use data. So just like Amazon, again, because we're here. And it'll say, oh, customers who bought what you're about to buy also bought this, and that can help you discover something useful. We try to expose we call behavior IO. Let the past behavior of the most knowledgeable people in the organization drive the future behavior. That's a big part of what we do. So one of the things I was reading about you guys on your website and some editorials is, a lot of data lakes fail. Why is that? How is Alation different? >> That's a great question. So I think what's interesting about a data lake is it's kind of like having a huge basement, right? And it can make you adopt a hoarder mentality, you say, oh it's so cheap to store everything, we'll just store it, and then when we need it we'll figure it out then. Well, the truth is, it's not always how it goes. Often you store so many things, it's cheap to store it, but when that actual human who has an actual analytical question they want to answer or an actual business process they want to improve, goes looking for the data, all they see are all these unlabeled boxes. Right? So I think the key is to think about how do you make information searchable, discoverable, understandable, trustworthy? And what's great is a lot of people are migrating from their on-premise data lakes to the Clouds, and obviously (mumbles) a big leader in where that's going. It gives you an opportunity to ask, just like when you move houses to say, let me look at what I've got, and can I adopt an approach? You know, what do I actually need? You might keep it all, but what's gonna be in the top shelf? What's gonna be in the basement? And how do you make everything accessible? >> So Aaron, can you talk a little bit about today's announcements? A lot of machine learning, analytics announcements from AWS. However, I don't know what I already have. So how can I make use of that data? Can you help talk about how Alation helps to leverage some of these new tools from AWS? >> Absolutely. So, we've had a bunch of customers on AWS Stack already, and increasingly so. Fundamentally our customers are people who do analysis. A lot of them are using S3, Redshift, the like. And people are hosting on the Cloud increasingly. And it's exactly the problem you described. It's I know I have it somewhere, but I can't get my head around what I already have. What region is it in? >> Aaron: Exactly. >> Is it in a region, is it in my data center, where is it? >> Exactly. so whether that data is in Redshift, in S3, or somewhere else. Maybe it's, you know, in a Postgres or SQL Server or Oracle Server. (mumbles) hosted one. Whatever it is, we crawl and index everything you have, just the way Google crawls and indexes everything out on the web, and we make it searchable, and we put information about who's used it and how good it is front and center, just the way you can say, oh this is a five-star clock on Amazon, I'm gonna go click buy it now. >> So one challenge with data lakes is security around that data. So data catalog, I get meta data around the data that I have, but some of that data is sensitive. How do you guys handle security around the data catalog itself? >> Absolutely. So we respect all the security and privacy settings that exist that are on the data itself, and we just sort of surface those in the catalog. Some of our customers say, look, we want to let people know what exists so they can ask for permission. Others say, even having awareness of this data is too much for us. And you mentioned, Pharma, that'll vary by industry. >> Where do you guys get involved in the customer conversation? You said many customers of yours are already using AWS for different things, but where does Alation come into the conversation? Are you brought in by AWS? Are you brought in by customers? Where are they on this journey towards leveraging the Cloud for the things that they need, agility, the speed, and the cost reduction? >> Absolutely. So our promise is we help you find, understand, and trust your data wherever it lives and whoever you are, democratizing it. So customers choose the right infrastructure for their needs, given cost, given performance. Obviously Amazon is increasingly a part of that. But that's a choice they make, and we resolve to handle that wherever it is. And as of customers, our customers are so smart, we learn so much from them. We're meeting a bunch of CIOs, both the prospects and also talking some current customers like Expedia today here at AWS lunch with our investor Costanoa and another at dinner tonight. And folks like Chegg and Invoice2go who've been longstanding AWS customers using S3, using Redshift, and actually in Chegg's case, they have a lot of homegrown tooling that they developed on the backend, but they said Alation is the best place to surface that and have it be the central portal for business users and analysts who might not be able to otherwise access things that are just available via (mumbles) >> So how are you, Alation, and AWS helping a customer like Chegg extract ROI quickly? >> Yeah, it's a great question, so, AWS is really great for cost containment. You have all this data and all this processing, but you have peaks and you have troughs, and how do you make sure you're not overpaying (mumbles) so it's great for helping with storage and computation. And Alation helps with the human side, how do you get that upside by saying you have this data, that could effect the way you stock your shelves, the way you price your products or who you hire, what markets you go into. And that requires that last step. If you have the data but it isn't in the right hands at the right time or it's interpreted incorrectly, it has no value. So the two of them together (mumbles) end-to-end solution. >> So Aaron, with GDPR coming up quick, the enforcement of that coming up May 2018, customers have to be concerned about having data they shouldn't have. Does Alation help identify some of that data? >> Absolutely. So data catalog is fundamentally an inventory of everything you have, plus information about how it has been and could be consumed. We very much focus on the upside, potential of using that to drive better business choices and better analysis. But we have customers actually saying, oh, we can use that same information about what we have, who's using it, what's in it, to instead make sure that it's used compliantly with a regulation like GDPR to make sure that you aren't holding onto health records longer than you should or PII. And it's absolutely a very big use case for many of our customers. >> So data is touched by a lot of people in an organization. AWS has done a great job of really developing a lot of synergy with the developer community for a long time now. But we're also seeing some trends suggesting they're going up the stack. They want to get more enterprises, enterprises are at the precipice, as Andy Jassey said, of this mass migration to the Cloud. You mentioned, all of your work with AWS and the CIO events that you're having here. Where are you guys in a conversation with customers? Are you more now having to get to that C-suite as now their business are absolutely predicated upon the best use of data to identify ways to monetize new revenue streams. How influential is that C-level in this conversation. >> It's a great question. So I think what is interesting is, all companies, we sort of commoditized a basic business school, consultant, best practice knowledge. Everyone is kind of already doing that. To get to the next level our customers are recently telling us it is only by finding key insights in data that they're gonna beat out the competition and stay relevant. I mean, look what Amazon and Netflix have done to the industries that, they weren't as data driven, and have that kind of agility around data. So everybody wants to do the same thing. So CIOs, CDOs, chief data officers, we're seeing them crop up more and more and being more and more empowered in the organization. Because it's seen as central to hitting revenue targets and making an impact, which is what customers want to do. And I mentioned CISOs as well with the question that you asked, Keith, about security. >> The CISOs, the chief information security officers. >> Aaron: Yeah, absolutely. Yeah, absolutely, so I think usually often a CISO will report into a CIO, often you see it as adjacent to them, there's somebody who needs to have the confidence, as they do, in Alation's process of mirroring what's in the data source, not introducing security holes. Potentially even taking a step forward and saying, as I implement GDPR and other policies, how do I use a comprehensive automated inventory like Alations to make sure that process isn't just started but actually finished and avoid the fines and the adverse events. We absolutely see across the C-suite a lot of interest. >> So let's go one step below the CIO, and I think the CIO understands this. This data is the new oil. Very, very straightforward. But now you're getting into the enterprise architect, the VP of infrastructure, and they have to implement these technologies. What have been some of the rewards and challenges with those conversations? >> That's a great question. Right, so here at AWS Reinvent we have a very technical audience, very infrastructure minded. Those are folks that we love to engage with, but our primary audience is the business. >> Keith: Right. >> Right. And so I think what's interesting is, the problem we solve for the more infrastructure-minded executives is how do I deal with these business users? How do I turn this relationship that feels adversarial, where they're putting strain on my system, they're upset about cost overruns, we don't speak the same language with the same values. Alation can be a great bridge. Because we do all of this automated extraction and tying to the sources where they are, and kind of meet the industry people where they live, but then can communicate the value in a clean interface that demonstrates real business ROI to the business. So we can kid of be an ambassador between those sides of the customer. >> I love that, being an ambassador. Aaron, your passion for Alation, what you do, your engagement with customers is palpable. So we thank you for joining us on theCUBE, and wish you guys the best of luck with what you're doing here at AWS Reinvent. >> Lisa, thank you so much for having me. >> Lisa: Awesome. >> Keith: Great job, Aaron. >> Thank you for watching. We are live at AWS Reinvent 2017 with 42,000 other people. I'm Lisa Martin, for my cohost Keith Townsend and Aaron Kalb, stick around. We'll be right back.