 Hey, welcome to this CUBE conversation. I'm Lisa Martin today talking to a CUBE alumni who's been on many times talking about data, all things data. Please welcome Satyan Sangani, the co-founder and CEO of Elation. Satyan, it's great to have you back on the CUBE. Hi Lisa, it's great to see you too. It's been a while. It has been a while. And of course in the last year, we've been living in this virtual world. So I know you've gotten to be on the CUBE during this virtual world. Hopefully someday soon, we'll get to actually sit down together again. There's some exciting news that's coming out of Elation. Talk to us about what's going on. What are you announcing? So we're announcing that we are releasing our Elation cloud service, which actually comes out today and is available to all of our customers. And as a consequence, are going to be the fastest, easiest deploy and easiest to use data catalog on the marketplace and using this release to really double down on that core differentiation. So the value prop for Elation has always been about speed to deployment, time to value. Those are really been what you've talked about is the fundamental strengths of the platform. How does the cloud service double down on that value prop? Well, if you think about data, our basic premise and the reason that we exist is that people could use data with so many of their different decisions. People could use data to inform their thinking. People can use data in order to figure out what decision is the best decision at any given point in time, but often they don't. Often gut instinct or whatever's most fast or easy to access is the basis off of which people decide to do what they do. And so if you want to get people to use data more often, you've got to make sure that the data is available, that the data is correct and that the data is easy to find and leverage. And so everything that we can do at Elation to make data more accessible to allow people to be more curious is what we get excited about because unlike paying your payables or unlike figuring out whether or not you want to be able to have greater or lesser inventory, those are all things that a business absolutely has to do, but people don't have to use data. And so to get people to use data, the best thing you can do is to make it easy and to make it fast. And speaking of fast, that's one of the things I think the last year has taught us is that real-time access to data is no longer a nice to have. It's really a competitive differentiator. Talk to me about how you enable customers to get access to the right data fast enough to be able to do what so many companies say and that is actually make data-driven decisions. Yeah, no, that's absolutely right. So it really is an entire continuum. The first and most obvious thing that we do is we start with the user. So if you're a user of data, you might have to hunch through a myriad of reports, thousands of tables in a database, hundreds of thousands of files in a data lake, and you might not know where to find your answer and you might have the best of intentions, but if you don't have the time to go through all of those sources, the first thing you might do is go ask your buddy down the hall. Now, if your buddy down the hall or your colleague over Zoom can't give you the time of day or can't answer your question quickly enough, then you're not gonna be able to use that data. So the first thing and the most obvious thing that we do is we have the industry's best search experience and the industry's best browse experience. And if you think about that search experience, that's really fueled by our understanding of all of the data patterns in your data environment. We basically look at every search, we look at every log within a company's data environment to understand what it is that people are actually doing with the data. And that knowledge, just like Google has PageRank to help it inform which are the best results for a given webpage, we do the exact same thing with data. And so great search is the basis of what we do. Now, above and beyond that, there's a couple of other things that we do, but they all get to the point of getting to that end search experience and making that perfect so that people can then curate the data and leverage the data as easily as possible. Sounds like that's really kind of personalized based on the business in terms of the search, looking at what's going on. Talk to me a little bit more about that and how does that context help fuel innovation? Yeah, so to build that context, you can't just do historically and traditionally what's been done in the data management space. Lots of companies come to the data management world and they say, well, what we're going to do is we're going to hire, we've got this great software, but sending this software up is a journey. It takes two to three to four years to set it up and we're going to get an army of consultants and everybody's going to go and assert quality of data assets and measure what the data assets do and figure out how the data assets are used. And once we do all that work, then in four years we're going to get you to a response. The real key is not to have that context to be built sort of through an army of consultants and an army of labor that frankly, nine times out of 10 never gets to the end of the road, but to actually generate that context day one by understanding what's going on inside of those systems and learning that by just observing what's happening inside of the company. And we can do that. Excellent, and as we've seen the acceleration in the last year of digital transformation, how much of that accelerant was an accelerator revelation putting this service forward and what are customers saying so far? Yeah, it's been incredible. I mean, what we've seen in our existing accounts is that our expansions have grown up, gone up by over 100% year over year with the crisis in place. Obviously you would hypothesize that these catalogs, these sort of accessibility and search tools and data in general would be leveraged more when all of us are virtual and all of us can't talk to each other. But it's been amazing to see that we've found that that's actually what's happening. People are actually using data more. People are actually searching for data more. And that experience and bringing that to our customers has been a huge focus of what we've been trying to do. So we've seen the pandemic. In many cases it's obviously been bad for many people but for us it's been a huge accelerant of customers using our product. Talk to me about Alation with AWS. What does that enable your customers to achieve that they maybe couldn't necessarily do on-prem? Yeah, so customers obviously don't really care anymore or as much as they used to about managing the software internally. They just wanna be able to get whatever they need to get done and move forward with their business. And so by leveraging our partnership with AWS, one, we've got elastic compute capability. I think that's obviously something that they bring to the table better than perhaps any other in the market. But much more fundamentally, the ability to stand up Alation and get it going now means that all you have to do is go to the AWS marketplace or call up an Alation rep and you can within a matter of minutes get an Alation instance that's up and running and fit for purpose for what you need. And that capability is really quite powerful because now that we have that elasticity and the speed of deployment, customers can realize the value so much more quickly than they otherwise might have. And that speed is absolutely critical as we saw a lot last year. That was the difference between the winners and those that were not going to make it. Talk to me a little bit about creating a data culture. We talk about that a lot. It's one thing to talk about. It's a whole other thing to put it in place, especially for legacy institutions that have been around for a while. How do you help facilitate the actual birth of a data culture? Yeah, I mean, I think we view ourselves as a technology, as a catalyst to our best customers and our best customer champions. And when we talk to chief data officers and when we talk to data leaders within various organizations that we service, organizations like Pfizer, organizations like Salesforce, organizations like Cisco, what they often tell me is, look, we've got to build products faster. We've got to move at the speed and the scale of all of the startups that are nipping at our heels. And how do we do that? Well, we've got to empower our people. And the way that we empower our people is by giving them context. And we need to give them the data to make the right decisions so that they can build those products and move faster than they ever might have. Now, those are amazing intentions, but those same leaders also come and say, I've just been mired in risk and I've been mired in compliance and I've been mired in doing all of these data genitorial projects. And it's really hard for me to get on the offense with data. It's really hard for me to get proactive with data. And so the biggest thing that we do is we just help companies be more proactive much more easily because what they're able to do is they're able to leave a lot of that genitorial work, lead a lot of that discovery work, lead a lot of that curation work to the software. And so what they get to focus on is, how is it that I can then drive change and drive behavioral change within my organizations so that people have the right data at their disposal? And that's really the magic of the technology. So I was reading the Alation State of Data Culture report that was just published a few weeks ago. This is this quarterly assessment that Alation does looking at the progress that enterprises have made in creating this data culture. And the number that really struck out, it was 87% of respondents say data quality issues are a barrier to successful implementation of AI in their organizations. How can Alation help them solve that problem? Yeah, I think the first is, whenever you've got a problem, the first thing you've got to do is acknowledge that you've got a problem. And a lot of the time people, leaders will often jump to AI and say, well, hey, everybody's talking about AI. The board level conversation is AI. Mackenzie's talking about AI. Let's go do some AI. And that sounds great in theory. And of course, we all wanna do that more. But the reality is that many of these projects are stymied by the basic plumbing. You don't necessarily know where the data's coming from. You don't know if people have entered it properly in the source systems or in the systems that are online. Those data often get corrupted in the transformation processes or the processes themselves don't run appropriately. And so you don't have transparency. You don't have any awareness of what people are doing, what people are using, how the data is actually being manipulated from step to step, what that data lineage is. And so that's really where we certainly help many of our customers by giving them transparency and an understanding of their data landscape. Ironically, what we find is that data leaders are super excited to get data to the business, but they often don't themselves have the data to understand how to manage the data itself. Wow, that's a conundrum. Let's talk about customers because I was looking on the website and there's some pretty big metrics based business outcomes that Elation is helping customers drive. I wanted to kind of pick through some examples from your perspective. First one is 364% ROI. Second one is 70% less time for analysts to complete projects. Workforce productivity stat is huge. Talk to me about how Elation is helping customers achieve business outcomes like that. Yeah, so if you think about a typical analytical project, you would think that most of the time is spent inside of the analytical tool, inside of your Excel, inside of your Tableau where you're thinking about the data and you're analyzing it, you're thinking deep thoughts and you're trying to hypothesize, you're trying to understand. But the reality is going back to the data quality issue that most of the time is spent with figuring out which are the right data sets because at one of our customers, for example, there were 4,000 different types of customer transaction data sets that spoke to the exact same data. Which data set do I actually use out of a particular database? And then once I figured out which ones to use, how do I construct the appropriate query and assumptions in order to be able to get the data into a format that makes sense to me? Those are the kinds of things that most analysts and data scientists struggle with. And what we do is we help them by not having them reinvent the wheel. We allow them to figure out what the right data set is fast, how to manipulate it fast, so that they can focus most of their time on doing that end analytical work. And that's where all the ROI, or a lot of the ROI is coming from because they don't now have to reinvent the wheel, they can do the work and they can move on with a much faster business decision, which means that that business moves significantly faster. And so what we find is that for these very highly priced resources, some data scientists who make $200, $300, $400,000, fully loaded for our company, those people can do their job 74% faster, which means they can get not only the answer faster, but they can get many more tasks done for over a given period of time. Well, that just opens up a potential suite of benefits that the organization will achieve, not just getting the analyst productivity cranked up in a big way, but also allowing the organization to be more agile, which many organizations are striving to be, to be able to identify new products, new services, what's happening, especially in a changing chaotic environment like we've been living in the last year. Yeah, absolutely. And they also can learn, not only can they help themselves figure out what new products to launch, but they can also help themselves figure out where their risks happen to be and where they need to comply because it could be the case that analysts are using data sets that they ought not to be using or the business is using the data incorrectly. And so you can find both the patterns, but also the anti-patterns, which means that you're not only moving faster, but you're moving forward with less risk. And so we've seen so many failures with data governance regimes where people have tried to assert the quality of data and figure out the key data elements and develop a business glossary. And there's that great quote, like I want a data governance, but all I got is a data glossary. That all happens because they just don't have enough time in the day to do the value added work. They only have enough time in the day to start doing the data cleaning and all of the janitorial work that we as a company really strive to allow them to completely eliminate. So wrapping things up here, Elation Cloud Service, tell me about when it's available, how can customers get it? So it's available today, which is super exciting. Customers can get it either through the AWS Marketplace or by calling your Elation representative. You can do that by coming to our website and that's super easy to do and getting a demo and moving forward. But we try to make it as easy as possible and we really want to get out of the way of allowing people to have a seamless frictionless experience and are super excited to have this cloud service that allows them to do that even faster than they were able to do before. And we all know how important that speed is. Well Satya, congratulations on the announcement of Elation Cloud Service. We appreciate you coming on here and sharing with us the news and really what's in it for the customers. Thank you Lisa, it's been phenomenal to catch up and great seeing you. Likewise, for Satya and Sangani, I'm Lisa Martin, you're watching this CUBE Conversation.