>> From Cambridge, Massachusetts, it's theCUBE, covering MIT Chief Data Officer and Information Quality Symposium 2019, brought to you by SiliconANGLE Media. >> Welcome back to Cambridge, Massachusetts everybody, you're watching The Cube, the leader in tech coverage. My name is Dave Vellante here with my cohost Paul Gillin. This is day one of our two day coverage of the MIT CDOIQ conferences. CDO, Chief Data Officer, IQ, information quality. Colin Mahoney is here, he's a good friend and long time CUBE alum. I haven't seen you in awhile, >> I know >> But thank you so much for taking some time, you're like a special guest here >> Thank you, yeah it's great to be here, thank you. >> Yeah, so, this is not, you know, something that you would normally attend. I caught up with you, invited you in. This conference has started as, like back office governance, information quality, kind of wonky stuff, hidden. And then when the big data meme took off, kind of around the time we met. The Chief Data Officer role emerged, the whole Hadoop thing exploded, and then this conference kind of got bigger and bigger and bigger. Still intimate, but very high level, very senior. It's kind of come full circle as we've been saying, you know, information quality still matters. You have been in this data business forever, so I wanted to invite you in just to get your perspectives, we'll talk about what's new with what's going on in your company, but let's go back a little bit. When we first met and even before, you saw it coming, you kind of invested your whole career into data. So, take us back 10 years, I mean it was so different, remember it was Batch, it was Hadoop, but it was cool. There was a lot of cool >> It's still cool. (laughs) projects going on, and it's still cool. But, take a look back. >> Yeah, so it's changed a lot, look, I got into it a while ago, I've always loved data, I had no idea, the explosion and the three V's of data that we've seen over the last decade. But, data's really important, and it's just going to get more and more important. But as I look back I think what's really changed, and even if you just go back a decade I mean, there's an insatiable appetite for data. And that is not slowing down, it hasn't slowed down at all, and I think everybody wants that perfect solution that they can ask any question and get an immediate answers to. We went through the Hadoop boom, I'd argue that we're going through the Hadoop bust, but what people actually want is still the same. You know, they want real answers, accurate answers, they want them quickly, and they want it against all their information and all their data. And I think that Hadoop evolved a lot as well, you know, it started as one thing 10 years ago, with MapReduce and I think in the end what it's really been about is disrupting the storage market. But if you really look at what's disrupting storage right now, public clouds, S3, right? That's the new data league. So there's always a lot of hype cycles, everybody talks about you know, now it's Cloud, everything, for maybe the last 10 years it was a lot of Hadoop, but at the end of the day I think what people want to do with data is still very much the same. And a lot of companies are still struggling with it, hence the role for Chief Data Officers to really figure out how do I monetize data on the one hand and how to I protect that asset on the other hand. >> Well so, and the cool this is, so this conference is not a tech conference, really. And we love tech, we love talking about this, this is why I love having you on. We kind of have a little Vertica thread that I've created here, so Colin essentially, is the current CEO of Vertica, I know that's not your title, you're GM and Senior Vice President, but you're running Vertica. So, Michael Stonebreaker's coming on tomorrow, >> Yeah, excellent. >> Chris Lynch is coming on tomorrow, >> Oh, great, yeah. >> we've got Andy Palmer >> Awesome, yeah. >> coming up as well. >> Pretty cool. (laughs) >> So we have this connection, why is that important? It's because, you know, Vertica is a very cool company and is all about data, and it was all about disrupting, sort of the traditional relational database. It's kind of doing more with data, and if you go back to the roots of Vertica, it was like how do you do things faster? How do you really take advantage of data to really drive new business? And that's kind of what it's all about. And the tech behind it is really cool, we did your conference for many, many years. >> It's coming back by the way. >> Is it? >> Yeah, this March, so March 30th. >> Oh, wow, mark that down. >> At Boston, at the new Encore Hotel. >> Well we better have theCUBE there, bro. (laughs) >> Yeah, that's great. And yeah, you've done that conference >> Yep. >> haven't you before? So very cool customers, kind of leading edge, so I want to get to some of that, but let's talk the disruption for a minute. So you guys started with the whole architecture, MPP and so forth. And you talked about Cloud, Cloud really disrupted Hadoop. What are some of the other technology disruptions that you're seeing in the market space? >> I think, I mean, you know, it's hard not to talk about AI machine learning, and what one means versus the other, who knows right? But I think one thing that is definitely happening is people are leveraging the volumes of data and they're trying to use all the processing power and storage power that we have to do things that humans either are too expensive to do or simply can't do at the same speed and scale. And so, I think we're going through a renaissance where a lot more is being automated, certainly on the Vertica roadmap, and our path has always been initially to get the data in and then we want the platform to do a lot more for our customers, lots more analytics, lots more machine-learning in the platform. So that's definitely been a lot of the buzz around, but what's really funny is when you talk to a lot of customers they're still struggling with just some basic stuff. Forget about the predictive thing, first you've got to get to what happened in the past. Let's give accurate reporting on what's actually happening. The other big thing I think as a disruption is, I think IOT, for all the hype that it's getting it's very real. And every device is kicking off lots of information, the feedback loop of AB testing or quality testing for predictive maintenance, it's happening almost instantly. And so you're getting massive amounts of new data coming in, it's all this machine sensor type data, you got to figure out what it means really quick, and then you actually have to do something and act on it within seconds. And that's a whole new area for so many people. It's not their traditional enterprise data network warehouse and you know, back to you comment on Stonebreaker, he got a lot of this right from the beginning, you know, and I think he looked at the architectures, he took a lot of the best in class designs, we didn't necessarily invent everything, but we put a lot of that together. And then I think the other you've got to do is constantly re-invent your platform. We came out with our Eon Mode to run cloud native, we just got rated the best cloud data warehouse from a net promoter score rating perspective, so, but we got to keep going you know, we got to keep re-inventing ourselves, but leverage everything that we've done in the past as well. >> So one of the things that you said, which is kind of relevant for here, Paul, is you're still seeing a real data quality issue that customers are wrestling with, and that's a big theme here, isn't it? >> Absolutely, and the, what goes around comes around, as Dave said earlier, we're still talking about information quality 13 years after this conference began. Have the tools to improve quality improved all that much? >> I think the tools have improved, I think that's another area where machine learning, if you look at Tamr, and I know you're going to have Andy here tomorrow, they're leveraging a lot of the augmented things you can do with the processing to make it better. But I think one thing that makes the problem worse now, is it's gotten really easy to pour data in. It's gotten really easy to store data without having to have the right structure, the right quality, you know, 10 years ago, 20 years ago, everything was perfect before it got into the platform. Right, everything was, there was quality, everything was there. What's been happening over the last decade is you're pumping data into these systems, nobody knows if it's redundant data, nobody knows if the quality's any good, and the amount of data is massive. >> And it's cheap to store >> Very cheap to store. >> So people keep pumping it in. >> But I think that creates a lot of issues when it comes to data quality. So, I do think the technology's gotten better, I think there's a lot of companies that are doing a great job with it, but I think the challenge has definitely upped. >> So, go ahead. >> I'm sorry. You mentioned earlier that we're seeing the death of Hadoop, but I'd like you to elaborate on that becuase (Dave laughs) Hadoop actually came up this morning in the keynote, it's part of what GlaxoSmithKline did. Came up in a conversation I had with the CEO of Experian last week, I mean, it's still out there, why do you think it's in decline? >> I think, I mean first of all if you look at the Hadoop vendors that are out there, they've all been struggling. I mean some of them are shutting down, two of them have merged and they've got killed lately. I think there are some very successful implementations of Hadoop. I think Hadoop as a storage environment is wonderful, I think you can process a lot of data on Hadoop, but the problem with Hadoop is it became the panacea that was going to solve all things data. It was going to be the database, it was going to be the data warehouse, it was going to do everything. >> That's usually the kiss of death, isn't it? >> It's the kiss of death. And it, you know, the killer app on Hadoop, ironically, became SQL. I mean, SQL's the killer app on Hadoop. If you want to SQL engine, you don't need Hadoop. But what we did was, in the beginning Mike sort of made fun of it, Stonebreaker, and joked a lot about he's heard of MapReduce, it's called Group By, (Dave laughs) and that created a lot of tension between the early Vertica and Hadoop. I think, in the end, we embraced it. We sit next to Hadoop, we sit on top of Hadoop, we sit behind it, we sit in front of it, it's there. But I think what the reality check of the industry has been, certainly by the business folks in these companies is it has not fulfilled all the promises, it has not fulfilled a fraction on the promises that they bet on, and so they need to figure those things out. So I don't think it's going to go away completely, but I think its best success has been disrupting the storage market, and I think there's some much larger disruptions of technologies that frankly are better than HTFS to do that. >> And the Cloud was a gamechanger >> And a lot of them are in the cloud. >> Which is ironic, 'cause you know, cloud era, (Colin laughs) they didn't really have a cloud strategy, neither did Hortonworks, neither did MapR and, it just so happened Amazon had one, Google had one, and Microsoft has one, so, it's just convenient to-- >> Well, how is that affecting your business? We've seen this massive migration to the cloud (mumbles) >> It's actually been great for us, so one of the things about Vertica is we run everywhere, and we made a decision a while ago, we had our own data warehouse as a service offering. It might have been ahead of its time, never really took off, what we did instead is we pivoted and we say "you know what? "We're going to invest in that experience "so it's a SaaS-like experience, "but we're going to let our customers "have full control over the cloud. "And if they want to go to Amazon they can, "if they want to go to Google they can, "if they want to go to Azure they can." And we really invested in that and that experience. We're up on the Amazon marketplace, we have lots of customers running up on Amazon Cloud as well as Google and Azure now, and then about two years ago we went down and did this endeavor to completely re-architect our product so that we could separate compute and storage so that our customers could actually take advantage of the cloud economics as well. That's been huge for us, >> So you scale independent-- >> Scale independently, cloud native, add compute, take away compute, and for our existing customers, they're loving the hybrid aspect, they love that they can still run on Premise, they love that they can run up on a public cloud, they love that they can run in both places. So we will continue to invest a lot in that. And it is really, really important, and frankly, I think cloud has helped Vertica a lot, because being able to provision hardware quickly, being able to tie in to these public clouds, into our customers' accounts, give them control, has been great and we're going to continue on that path. >> Because Vertica's an ISV, I mean you're a software company. >> We're a software company. >> I know you were a part of HP for a while, and HP wanted to mash that in and run it on it's hardware, but software runs great in the cloud. And then to you it's another hardware platform. >> It's another hardware platform, exactly. >> So give us the update on Micro Focus, Micro Focus acquired Vertica as part of the HPE software business, how many years ago now? Two years ago? >> Less than two years ago. >> Okay, so how's that going, >> It's going great. >> Give us the update there. >> Yeah, so first of all it is great, HPE and HP were wonderful to Vertica, but it's great being part of a software company. Micro Focus is a software company. And more than just a software company it's a company that has a lot of experience bridging the old and the new. Leveraging all of the investments that you've made but also thinking about cloud and all these other things that are coming down the pike. I think for Vertica it's been really great because, as you've seen Vertica has gotten its identity back again. And that's something that Micro Focus is very good at. You can look at what Micro Focus did with SUSE, the Linux company, which actually you know, now just recently spun out of Micro Focus but, letting organizations like Vertica that have this culture, have this product, have this passion, really focus on our market and our customers and doing the right thing by them has been just really great for us and operating as a software company. The other nice thing is that we do integrate with a lot of other products, some of which came from the HPE side, some of which came from Micro Focus, security products is an example. The other really nice thing is we've been doing this insource thing at Micro Focus where we open up our source code to some of the other teams in Micro Focus and they've been contributing now in amazing ways to the product. In ways that we would just never be able to scale, but with 4,000 engineers strong in Micro Focus, we've got a much larger development organization that can actually contribute to the things that Vertica needs to do. And as we go into the cloud and as we do a lot more operational aspects, the experience that these teams have has been incredible, and security's another great example there. So overall it's been great, we've had four different owners of Vertica, our job is to continue what we do on the innovation side in the culture, but so far Micro Focus has been terrific. >> Well, I'd like to say, you're kind of getting that mojo back, because you guys as an independent company were doing your own thing, and then you did for a while inside of HP, >> We did. >> And that obviously changed, 'cause they wanted more integration, but, and Micro Focus, they know what they're doing, they know how to do acquisitions, they've been very successful. >> It's a very well run company, operationally. >> The SUSE piece was really interesting, spinning that out, because now RHEL is part of IBM, so now you've got SUSE as the lone independent. >> Yeah. >> Yeah. >> But I want to ask you, go back to a technology question, is NoSQL the next Hadoop? Are these databases, it seems to be that the hot fad now is NoSQL, it can do anything. Is the promise overblown? >> I think, I mean NoSQL has been out almost as long as Hadoop, and I, we always say not only SQL, right? Mike's said this from day one, best tool for the job. Nothing is going to do every job well, so I think that there are, whether it's key value stores or other types of NoSQL engines, document DB's, now you have some of these DB's that are running on different chips, >> Graph, yeah. >> there's always, yeah, graph DBs, there's always going to be specialty things. I think one of the things about our analytic platform is we can do, time series is a great example. Vertica's a great time series database. We can compete with specialized time series databases. But we also offer a lot of, the other things that you can do with Vertica that you wouldn't be able to do on a database like that. So, I always think there's going to be specialty products, I also think some of these can do a lot more workloads than you might think, but I don't see as much around the NoSQL movement as say I did a few years ago. >> But so, and you mentioned the cloud before as kind of, your position on it I think is a tailwind, not to put words in your mouth, >> Yeah, yeah, it's a great tailwind. >> You're in the Amazon marketplace, I mean they have products that are competitive, right? >> They do, they do. >> But, so how are you differentiating there? >> I think the way we differentiate, whether it's Redshift from Amazon, or BigQuery from Google, or even what Azure DB does is, first of all, Vertica, I think from, feature functionality and performance standpoint is ahead. Number one, I think the second thing, and we hear this from a lot of customers, especially at the C-level is they don't want to be locked into these full stacks of the clouds. Having the ability to take a product and run it across multiple clouds is a big thing, because the stack lock-in now, the full stack lock-in of these clouds is scary. It's really easy to develop in their ecosystems but you get very locked into them, and I think a lot of people are concerned about that. So that works really well for Vertica, but I think at the end of the day it's just, it's the robustness of the product, we continue to innovate, when you look at separating compute and storage, believe it or not, a lot of these cloud-native databases don't do that. And so we can actually leverage a lot of the cloud hardware better than the native cloud databases do themselves. So, like I said, we have to keep going, those guys aren't going to stop, and we actually have great relationships with those companies, we work really well with the clouds, they seem to care just as much about their cloud ecosystem as their own database products, and so I think that's going to continue as well. >> Well, Colin, congratulations on all the success >> Yeah, thank you, yeah. >> It's awesome to see you again and really appreciate you coming to >> Oh thank you, it's great, I appreciate the invite, >> MIT. >> it's great to be here. >> All right, keep it right there everybody, Paul and I will be back with our next guest from MIT, you're watching theCUBE. (electronic jingle)