We recently announced $50M in Series C funding to supercharge our growth, cement our leadership position, and innovate so data catalogs can create even deeper and broader value than they are today. We’re delighted to watch leading organizations like Daimler, eBay, Hilton Hotels, LinkedIn, Munich Re, and Pfizer trust the Alation Data Catalog to connect analytics to decision-making every single day.
I had the pleasure of chatting with John Furrier of theCUBE about how our recent round of funding will fuel innovation within the Alation Data Catalog. Check out our conversation below.
Here’s a transcript of the interview:
John: Welcome to this CUBE Conversation here in Palo Alto. I’m John Furrier, co-host of theCUBE. I’m here with Aaron Kalb, who is the co-founder and VP of design at Alation. Great to see them on some fresh funding news. Aaron, thanks for coming in and spending the time. Good to see you again.
Aaron: Good to see you, John. Thanks for having me.
John: So, big news. You guys got a very big round of financing. You guys are going to the next level as a start-up, certainly coming out of that start-up phase and growth phase. Super exciting news. You guys are doing some innovative things around community, around people, and really kind of cracking the code on this humanization, the democratization of data, and 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. It’s a lot of cash.
Aaron: Yeah, so we’re very excited to have raised a $50 million round. Sapphire led the round, then we also had re-ups from all of our existing investors. You know as a co-founder, you always have big dreams for growth, and it’s always validating to have a community of investors who can see that future too. As well as our great community of over 100 customers now who want to build this data-democratized future with us.
John: We’ve been following you guys since the founding. Obviously, watching you guys. Great use of capital. Fifty million is a lot of capital, so obviously, validation, check. Good job. But now, you go to a whole other level of growth. What’s the capital going to be deployed for? What’s going on with the company? What are you guys eyeing in terms of innovation? What’s the key focus?
Aaron: Yeah, it’s a great question. So, obviously we have revenue from our customers, but getting the extra infusion from VCs lets us just supercharge our development. It’s growth: it’s going to more customers, both domestically and abroad; going to a broader user base; more enterprise-wide adoption within those customers. As well as innovation in the core product: new technology, a great design, and features that are really going to change the organizations accessing data to make better decisions.
John: What was the key learning 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.
Aaron: I’m glad you asked about that. I think the key thing that’s changed that’s enabled this next phase is that the data catalog market has really came into its own. Right? In the beginning, in the early days, we were knocking on doors trying to say—We didn’t even know it was going to be called “data catalog” in our first few months. Even though we had the technology, we said, “Hey, we’ve got this thing and we know it’s useful. Please buy it. Please want it.” And the question was, “What’s a data catalog? Why would I ever even look at that?”
It’s just turned a corner: Now, thanks in part to 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 we want a data catalog.” It just turned on a dime. Now they’re asking, “Which data catalog should we get? Why is yours the best?” This change of the market maturing, I think is the biggest change we’ve seen.
John: One thing we’ve observed, and I want to get your reaction to this, is that safe 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-clouds 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 may have a cloud operations. It really kind of changes the role of data.
You mentioned the data catalogs having a common mainstream visibility from the analyst, like Gartner and others. Wikibon as well. It makes data the center of the innovation. 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. 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?
Aaron: Absolutely. You hit 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.
Centrality, we think, is really essential. We’re seeing cataloging technology crop up more and more. A lot of people are coming out with catalogs or catalog add-ons to their products. 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. One of Alation’s key differentiators from early on was being that central index. Much like Google is the front page for the Internet, even though it’s linking to web pages all over the place.
The other thing in terms of that data quality and data trustworthiness has been a differentiator. This is something that was part of our technology when we launched that we didn’t put the label on it till later; it was the idea of Behavior I/O. That’s kind of looking at previous human behavior to influence future human behavior to be better.
This is another place where we really took some inspiration from Google and Terry Winograd at Stanford before that. He observed, if you remember back before Google, search sucked, frankly. Right? The results on top were not the most relevant; were not the most trustworthy. The reason was, those algorithms were based on saying, “how often does your keyword appear in that website relative to other words?”, so you would 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 that isn’t the best result for you.
What Google did was turn that around with page rank 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.” Alation does the exact same thing. Our patented, proprietary, Behavior I/O 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.
John: And you call that Behavioral I/O?
Aaron: Behavior I/O, that’s right.
John: Certainly, I remember Google algorithmic search was poo pooed at first. You had to be a portal. Everyone my age kind of remembers those days. The results were keyword stuff by spammers, but arithmetical search accelerated the quality. I’ve got to ask you, the Behavioral I/O, to kind of unpack that a little bit. Go a little deeper. What does that mean for customers? Because now I see, as people start thinking, “okay, I need to catalog my data because now I need to have replication, all kinds of all these technical things that are going on around integrity of the data.” Why Behavior I/O? What’s the angle on that? What’s the impact of the customer? Why is this important?
Aaron: Absolutely. So, it might help to work through an example. You know, we joke about how you might be looking around in your SharePoint drive and find an Excel file called Q3numbers_final_final and you’re like “Okay that seems like the final numbers.” Then you see right next to it another one that says _final_final_final and say, “Okay is that one final?” It turns out what data says about itself is less reliable than what other people say about the data. Same thing with Google. If everyone’s linking to Wikipedia page, that’s a more reliable page than one that just has paid for a higher placement. Right? What it means in an organization is, with Alation, we’ll tell you, “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.
John: So relevance is key there.
Aaron: 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.
John: 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? Are there any kind of stats around that? We’re hearing a lot of people say, “Hey you know, I’m not going to really work on the data. I’m not going to do all this heavy lifting on the front end if data quality is not there.”
Aaron: Absolutely. We see a really cool upward spiral. In Alation, we have a mix of manually human curated metadata where you have data stewards that are curators saying, “This is endorsed data. This is certified data. This is applicable for this context.” We also do this automatic Behavior I/O where we parse the query logs. These logs were put there for audit and debugging purposes, but we were mining that for behavioral insight, and we’ll show them side-by-side. 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.
We also see an upward spiral where if on day one, people are using data that isn’t trustworthy, that’s stale or miscalculated, as soon as an Alation steward slaps a deprecation or a warning on the data asset, because of technology like TrustCheck which we talked about last time I was here, that technology, that’s the ‘O’ part of Behavior I/O, we then stop the future behavior from being on bad data, and we see an upward spiral where suddenly the bad data’s no longer being used and everyone’s guided to the right path.
John: One thing 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 we talked about your role at Stanford in 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 web page and 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. Explain some customer impact antidotes. People who bought Alation, bought your service and offering. What happened after and what was it like before? Talk about some of those anecdotes. Because I think you’re onto something pretty big here with this discovery actionable data prospective.
Aaron: Yeah. One of our values at Alation is that we measure our success through customer impact. Not through financing or other other milestones, though we are excited about them. 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 Safeway was acquired by Albertsons, they’d been sort of pioneers 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 instead of customizing deals for you based on your buying behavior. They talk about getting a 30x ROI on the dollars they spent on Alation by basically proving the value of their program and maximizing their relationship with their customers.
But the stories that are even more exciting to me than just business impacts in dollars and cents is when we can leave a positive impact on people’s lives with data. There’s a few examples of that. Munich Reinsurance had some coverage in Forbes about the way that they used Alation, and other data tools to be able to help people get back on their feet more quickly after earthquakes and other natural disasters.
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 and analytics from Alation and other data tools.
John: So, it’s not just one little vertical. It’s kind of I mean, data is, horizontally scalable. It’s not like one industry’s going to leverage Alation.
Aaron: 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 study 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.
John: So, Behavior I/O and it’s all about context and behavioral role of data and all this is kind of fundamental to businesses.
Aaron: 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.
John: So, if I’m a potential customer and I’ve heard of Alation, got the buzz out there. Why would I need you? What is some signals that would indicate that I should call Alation? What’s some of that core? What’s the pitch?
Aaron: 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 Alation. 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 so small that you could make a table of contents for it, but as there came to be trillions of webpages, you needed an automatic index with Page Rank to make sense of it.
I would say once you find that your analytics team is spread out and they’re spending 80% of their time calling up other people to find where the relevant data is or asking, 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 of their time scrounging. If you want to get them to switch from scrounging to finding, understanding and trusting their data for quick and accurate analysis, give us a call.
John: Basically, the pitch is if you want to be like Yahoo, do it the old way. We know what happened Yahoo. If you want to be like Google, do algorithmic and have data, go Alation you’ll be around for a while.
Aaron: Very well said. We do think that.
John: Maybe you wouldn’t say that. That’s my words.
Aaron: That’s part of turning that corner. I think in the beginning we were telling people this would be nice to have and now customers are coming to us saying it’s a must-have to stay relevant. 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 is all wasted and you’re going to not be able to compete against your competitors and impact your customers the way you want.
John: Well, congratulations. Certainly as the co-founder, it’s great success. I know how hard it is to do startups. You guys have worked hard. Again while 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 Alation. What’s the key innovation formula and now that you 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 is the innovation of the future?
Aaron: Absolutely. Innovation has been critical for us to get here and our customers didn’t just buy the exciting features with Behavioral I/O and TrustCheck that we had, but are also buying into the idea that we’re going to continue to be the leaders and to innovate, and we’re going to do that. 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 and what humans like doing. 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 Yelp or Amazon. Google had the insight that we could leverage what people are already doing and make value 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. I came from Siri at Apple and the idea was you didn’t 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.
John: 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. I’m only kidding. Final question, just to double-down on that piece. I think that 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 maybe it’s a problem you’ve seen, whether it’s media, the new cycle these days, people are challenging the efficacy of finding the research. There’s real deep research on the media side.
We’re seeing scale on data. Scale is a huge challenge. You mention 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? Is that important? Because, certainly scale is table stakes these days.
Aaron: That is super insightful, John, because I think human cognition and human thought is the bottleneck for being data driven. Right? We have on the Internet trillions of web pages. More than the library at Alexandria… hundred times over. 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. 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 come actionable.
The other thing I would say is in this age of alternative facts and mistrust of data, we’re 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. 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 in what they’re hearing and understanding.
John: Building that page rank metaphor is interesting because the human gesture whether it’s work or engaging on the data is a signal too, not just algorithmic metadata extraction.
Aaron: Absolutely. Anything you do with data in any tool—even outside of Alation—Alation will capture that and use it to guide future behavior for you and your peers to be better and smarter.
John: $50 million… where’s this all going to lead to? When’s the next innovation? What do you guys see the future for Alation?
Aaron: Well you know, I was just thinking before the show, I used to be at Apple in the Golden Age when Apple was really innovative and there was the joke where they would release something new and say, “Redmond, start your photocopiers.” In this interview I’m going to be a little ‘close to the chest’ about the specifics we’re releasing, but I will tell you that we’re really excited about going to a broader and broader audience that impacts our customers more fully.
John: Feel free to say one more thing.
Aaron: And one more thing.
John: One more thing.
Aaron: And the secret to the future is…
John: Aaron, thanks for coming on. I really appreciate it. Congratulates on the funding. You guys have got a very innovative formula. Good luck and we will be following you guys. Thanks for coming on this CUBE Conversation. Appreciate it.
Aaron: John, thanks so much.
John: Aaron Kalb, Co-Founder and VP of design at Alation. Interesting formula, great successful formula. Great innovation, Alation. Check them out. I’m John Furrier in Palo Alto for CUDE Conversation. Thanks for watching.