 So everyone, welcome to this CUBE conversation here in Palo Alto. I'm John Furrier, co-host of theCUBE. I'm here with Aaron Calab, who's the co-founder and VP of design and adulation. Great to see them on some fresh funding news. Aaron, thanks for coming in and spending the time. Good to see you again. Great to see you, John. Thanks for having me. So, big news. You guys got a very big round of financing. You guys are going to the next level as a startup, certainly coming out of that startup phase and the growth phase. Super exciting news. You guys are doing some very innovative things around data, around community, around people and really kind of cracking the code on this humanization, democratization of data, but actually helping businesses. So 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 $50 million round, a sapphire-led the round and we also had re-ups from all of our existing investors and as a co-founder, you always have big dreams for growth and it's just validating to have a community of investors who kind of see that future too, as well as our great community of over 100 customers now who want to kind of build this data, democratize the future with us. We've been following you guys since the founding. Obviously watching you guys. Great use of capital, 50 million is a lot of capital. So obviously validation check, good job. But now you go to a whole other level, growth. What's the capital going to be deployed for? What's going on with the company? Where do you guys eye in terms of the innovation? What's the key focus? Yeah, it's a great question. So obviously we have revenue from our customers but getting this extra infusion from VC let's just supercharge our development. It's growth, it's going to more customers both domestically and abroad, going to a broader user base and more enterprise wide adoption within those customers as well as innovation in the core product. New technology, great design and features that are really going to change their organizations, access and use data to make better decisions. What was the key learnings as you guys went into this round of funding, obviously the validation to go through due diligence and 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 50 million? Yeah, I'm glad you asked about that. I think that the key thing that's changed that's enabled 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 didn't even know what was going to be called data catalog in our first few months, you know 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 what's the data catalog, why would I ever even look at that? And it's just turned a corner. Now things in part are things like Gartner telling companies in the next year by 2020 if you have a data catalog you're going to see twice the ROI from your existing data investments than if you don't. Stories like that are making companies say of course you're going to have data catalog, it just turned out a dime. Now they're asking which data catalog should we get? Why is yours the best? And this change of the market maturing I think is the biggest change we've seen. Yeah, one thing that we've observed and I want to get your reaction to this is that obviously with cloud computing the economics are phenomenal. You see scale, obviously data science work in the cloud we see great success there. Now there's multiple clouds, multi-cloud is a big trend but also the validation that it's not just all cloud anymore. The on-premises activity still is relevant although it might have a cloud operations really kind of changes the role of data. You mentioned the data catalogs kind of being kind of having a common mainstream visibility from the analysts like Gartner and others and Wikibon as well. It makes data the center of the innovation and now you have data challenges around okay where's the data deployed? Where am I using the data? Because data scientists want ease of data. They want quality data. They want to make sure their algorithm whether it's machine learning component or software actually is running on good data. So data effectiveness is now part of the operations of most businesses. What's your reaction to that? What's your thoughts? Is that how you see it? Is there something different there? What's going on with the whole data at the center? Absolutely, you get on two key themes for us. One is that idea of the center and the other is your point about data quality and data trust. So centrality we think is really essential. You know we're seeing cataloging technology crop up more and more. A lot of people are coming out with catalogs and 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, the 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 it's one of Alation's key differentiators early on was being that central index much like Google is sort of the front page to the internet even though it's linking to web 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 on it 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 this is another place where we really took some inspiration from Google and Perry Winnigrad at Stanford before that. You know he observed, you know if you remember back before Google search sucked frankly, right? The results on top were not the most relevant and not the most trustworthy and the reason was those algorithms were based on saying how often does your keyword appear in that website relative to 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 you know that isn't the best result for you. And what Google did was turn that around with PageRank and say let's use the signals that other people are leaving behind about the pages they find valuable to get the best result on top. And in relation to the exact same thing, our patented proprietary behavior technology lets us say who's using this data, how are they using it, is it reputable and that enables us to get the right data and the trustworthy data in front of decision makers. And you call that behavioral IO? Behavior IO, that's right. I mean certainly I remember Google algorithmic search was poo poo'd at first, you had to be a portal. Everyone kind of, my age you kind of remember those days and the results were keyword stuff by spammers but algorithmic search accelerated the quality. So I got to ask you the behavioral IO to kind of unpack that a little bit. Go a little deeper. What does that mean for customers? Because now obviously as people start thinking, okay, I need to catalog my data because now I need to have replication, all kinds of these technical things that are going on around integrity of the data. But why behavioral IO? What's the angle on that? What's the impact of the customer? Why is this important? Absolutely, so it might help to work through an example. You know, we joke about, you might be looking around in your SharePoint drive and you find an Excel file called Q3 numbers, final, you know, underscore final. And you know, okay, that seems like the final numbers. And then you see next to it when it says underscore final, underscore final, underscore final. Let's say, 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, right? If everyone's linking to the Wikipedia page, that's a more reliable page than one that just has, you know, paid for a higher placement, right? So what it means in organization is with Alation we'll 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 relevance and trustworthiness we find both are indicated more strongly by who's using it and how than by the data itself. Are you seeing adoption with data scientists and people who are wrangling data or data analysts that if the data is not high quality, they abandon the usage? Is there any kind of stats around that? Or is that we're hearing a lot of people say, hey, you know, I'm not going to really work on the data. If I'm not going to do all this heavy lifting on the front end, that the data quality is 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 data curators saying, this is endorsed data, this is certified data, this is applicable for this context. But we also do this automatic behavior IO where we parse the query logs. These logs were put there for audit and debugging purposes but we're mining that for behavioral insight and we'll show them side by side. And what we see is over time, 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 an Alation steward slaps a deprecation or a warning on the data asset because of technology like trust check we talked about last time I was here. That technology, that's the kind of, 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 data is no longer being used and everyone's guided to the right path. One of the things I'm really impressed with you guys on is you have a great management team and an overall team with mixed disciplines. Okay, I think last time I talked about your role Stanford and the human side of the world but you bring up the search analogy which is interesting because you have search folks, you got hardcore data geeks all working together and if you think about discovery and navigation which is the Google paradigm, I need to find a webpage and go go go to it. You guys are 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 Elation, bought your service and offering and what happened after and what was it like before? So talk about some of that anecdote because I think you're onto something pretty big here with this discovery actionable data perspective. Yeah, well one of our values at Elation is that we measure our success through customer impact. You know, not through financing or other milestones that we are excited about them. So I would love to talk about our customers. One example is of a business impact is an example that our champion at Safeway Albertsons describes where after Safeway was acquired by Albertsons, they'd been sort of pioneers of sort of digital loyalty and engagement and there was a move to kind of stop that in its tracks and switch to just mailing people, big books of coupons that are customizing deals for you based on your buying behavior. And they talk about getting a 30X ROI on the dollars they spent on Elation by basically proving the value of their program and kind of maximizing their relationship with their customers. But the story is they're even more exciting to me than just business impacts and dollars and cents when we can really have a positive impact on people's lives with data. Just a few examples of that. Munich re-insurance, the biggest re-insurer and also a primary insurer in Europe had some coverage in Forbes about the way that they use Elation, other data tools to be able to help people get back on their feet more quickly after earthquakes and other natural disasters. And similarly, there was 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 to even invest in those if they didn't get that increased efficiency in their analytics from Elation and their other data tools. So it's not just one little vertical, it's kind of, I mean data is horizontally scalable. It's not like one industry is going to leverage Elation. Absolutely, so I mentioned just now insurance and healthcare and retail. We're also in tech. We're in basically every vertical you can imagine and even multiple sectors. I've been focusing on industry, but there's another case that you can read about at the city of San Diego, where they're doing an open data initiative enabling people to figure out everything from where parking is easiest or hardest to anything else. So behavioral IO and it's all about context and behavior, role of data and all this is kind of fundamental to businesses. That's right, it's all about taking everything about how people are 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 potential customer and I've heard of Elation, got the buzz out there, why would I need you? What are some signals that would indicate that I should call Elation? What's some of that core, what's the pitch? Yeah, it's a great question. I sometimes joke with the team that every five minutes another enterprise reaches that point where they can't do it the old way anymore and they need Elation. And the reason for that is that data is growing exponentially and people can only grow at most linearly. So I compare it a bit again to the days of Yahoo, when the internet was small you can make a table of contents for it but as there came to be trillions of web pages you needed an automatic index with PageRank to make sense of it. So I would say once you find that your analytics team has spread out and they're spending 80% of their time calling up other people to find where their relevant data is or ask to your point, is this data high quality? Should I even spend my time on it? That's probably not money as well spent with these highly paid people spending all their time scrounging. If you want them to switch from scrounging to finding, understanding and trusting their data for quick and accurate analysis, give us a call. So basically the pitch is if you want to be like Yahoo, do it the old way. We know what happened to Yahoo. If you want to be like Google, do algorithmic and have data correlation and you'll be around for a while. Very well said, we do think that. Maybe you don't want to say that, that's my words. And that's part of turning that corner. I think in the beginning we were trying to tell people this could be a nice to have and now customers are coming to us realizing it's a must have to stay relevant. And if you've made all these investments in data infrastructure and data people but you can't connect the dots as 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 your customers in what you want. Well, Aaron, congratulations. Certainly as the co-founder, it's great success. I know how hard it is to do startups. You guys have worked hard. And again, while I'm following you guys it's been interesting to see that growth. And there's innovation involved. Creative, a lot of energy, you guys do a good job. So final question. Talk about the secret sauce of elation. What's the key innovation formula? And now that you've got the funding where are you going to double down on? Where's the innovation going to come next? So the innovation formula and where's the innovation in the future? Absolutely, innovation has been critical for us to get here and our customers didn't just buy the exciting futures with behavior and trust check that we had but also we're buying into the idea that we're going to continue to be the leaders and to innovate and we're going to do that. So I think the secret sauce which we've had in the past and we're going to continue to innovate in this vein is to be really conscious of what are computers great at and what are humans uniquely good at? What are humans like doing? And trying to have the human and computers work together to really help the human achieve their goals, right? So back to the Google example, there's a bunch of systems for collaboratively ranking things but it takes work to write a review on the Alper Amazon. Google had the insight that we could leverage that people are already doing and make value out of that and we're going to continue to do that. The other kind of innovation you'll see is bringing elation to a wider and wider audience with less and less technical skill needed. So I came from Syria at Apple and the idea is you'd have to learn a programming language to query a database, you can just speak in English. That helps you 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 as we want to have an app called theCUBE Siri which is, hey, Cube, what's the innovation in Silicon Valley and have it just spit out a video? Only kidding. Final question, just to double down on that piece because I think the human interaction is a big part of what you're saying. I've always loved that about what your vision is but this points to a major problem you're seeing whether it's media, the news cycle these days, people are challenging the efficacy of finding the research and there's real deep research on the media side we're 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 is kind of where you guys are hitting. Talk about that dynamic, am I getting that right and is that important? Because 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 for being data driven. We have on the internet trillions of web pages, more than the library of Alexandria a hundred times over and we have in databases millions of columns and trillions of rows 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 can understand it and so in the same way that Google became the mechanism by which the internet becomes accessible we think that elation for organizations is becoming the way that data can become actionable and the other thing I would say is in this age of alternative facts and mistrust of data we've sort of realizing that 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 elation 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 and garbage out and make people more rational and more curious and have more trust than what they're hearing understanding. And building that page rank kind of metaphor is interesting because the human gestures, whether it's work or engaging on the data is a signal too not just algorithmic metadata extraction. Absolutely, anything you do with data in any tool even outside of elation, elation will capture that and use it to guide future behavior for you and your peers to be better and smarter. $50 million, where's this all going to lead to? When's the next innovation? What do you guys see the future for elation? Well, you know, I was just thinking before the show I used to be at Apple kind of in the golden age when Apple was really innovative and there was the joke where they released something new and say, Redmond, start your photocopier. So in this interview I'm going to be a little close to the chest about the specifics of what we're releasing but I will tell you we have a roadmap we're really excited about to go to a broader and broader audience to impact our customers more fully. Well, you feel free to say one more thing. Yeah, one more thing. And then one more thing. The secret to the future is, yeah. Aaron, thanks for coming on. I really appreciate it. Congratulations on the funding. You guys got a very innovative formula. Good luck and we'll be following you guys. Thanks for coming on this Cube Conversation. Thanks so much. Aaron Kalb, co-founder and VP of design at elation. Interesting formula, great successful formula, great innovation at elation. Check them out. I'm John Furrier and Pella Walter for Cube Conversation. Thanks for watching.