>> from Cambridge, Massachusetts. It's three Cube covering M. I T. Chief data officer and information quality Symposium 2019. Brought to you by Silicon Angle Media. >> Welcome back to M I. T. CDO I Q everybody, you're watching the cube we got. We go out to the events we extract the signal from the noise is day one of this conference. Chief Data Officer event. I'm Dave, along with my co host, Paul Gillen. Stuart Bond is here is a research director of International Data Corporation I DC Stewart. Welcome to the Cube. Thanks for coming on. Thank you for having me. You're very welcome. So your space data intelligence tell us about your swim lane? Sure. >> So my role it I. D. C is a ZAY. Follow the data integration and data intelligence software market. So I follow all the different vendors in the market. I look at what kinds of solutions they're bringing to market, what kinds of problems. They're solving both business and technical for their clients. And so I can then report on the trends and market sizes, forecasts and such, And within that part of what I what I cover is everything from data integration which is more than traditionally E T l change data capture data movements, data, virtualization types of technologies as well as what we call date integrity of one. And I'm calling data intelligence, which is all of the Tell the metadata about the data. It's the data catalogs meditating management's data lineage. It's the data quality data profiling, master data intelligence. It's all of the data about the data and understanding really answering what I call a entering the five W's and h of data. It's the who, what, where, when, why and how. Data. So that's the market that I'm covering and following, and that's why I'm >> here. Were you here this morning for Mark Ramsey's Yes, I talk. So he kind of went to you. Heard it started with the D W kind of through E T L under the bus. Well, MGM, then the Enterprise data model said all that failed. But that stuff's not going away, and I'm sure they're black. So still using, you know, all those all that tooling today. So what was your reaction to that you were not in your head and yeah, it's true or saying, Well, maybe there's a little we'll have what we've been saying. The mainframe is gonna go away for years and >> still around, so I think they're obviously there's still those technologies out there and they're still being used. You can look at any of the major dtl vendors and there's new ones coming to the market, so that's still alive and well. There's no doubt that it's out there and its biggest segment of the market that I followed. So there's no source tooling, right? Yes, >> there's no doubt that it's still >> there. But Mark's vision of where things are going, where things are heading with, with data intelligence really being at the Cory talk about those spiders talked about that central depository of information about knowledge of the data. That's where things are heading to, whether you call it a data hub, whether you call it a date, a platform, not really a one big, huge data pop for one big, huge data depository, but one a place where you can go to get the information but natives you can find out where the data is. You could find out what it means, both the business context as well as the technical information you find out who's using that data. You can find out when it's being used, Why it's being used in. Why do we even have it and how it should >> be used? So it's being used >> appropriately. So you would say that his vision, actually what he implemented was visionary skating. They skated to the puck, so to speak, and that's we're going >> to see more of that. Where are seeing more of that? That's why we've seen such a jump in the number of vendors that air providing data catalogue solutions. I did, Uh, I d. C has this work product calling market glance. I did that >> beginning of 2018. >> I just did it again. In the middle of this year, the number of vendors that offer data catalogue solutions has significantly interest 240% increase in the number of vendors that offer that now itself of a small base. These air, not exhaustive studies. It may be that I didn't know about all those data catalogue vendors a year and 1/2 ago, but may also be that people are now saying that we've got a data catalogue, >> but you've really got a >> peel back the layers a little bit. Understand what these different data catalysts are and what they're doing because not all of them are crediting. >> We'll hear Radar. You don't know about it. 99% of the world mark talked this morning about some interesting new technologies. They were using Spider Ring to find the data bots to classify the data tools wrangle the data. I mean, there's a lot of new technology being applied to this area. What? Which of those technologies do you think has the greatest promise right now? And how? How how automated can this process become? >> It's the spider ring, and it's the cataloging of the data. It's understanding what you've got out there that is growing crazy. Just started to track that it's growing a lot that has the most promised. And as I said, I think that's going to be the data platform in the future. Is the intelligence knowing about where your data is? You men go on, get it. You know it's not a matter of all. The data is one place anymore. Data's everywhere Date is in hybrid cloud. It's in on premise. It's in private. Cloud isn't hosted. It's everywhere. I just did a survey. I got the results back in June 2019 just a month ago, and the data is all over the place. So really having that knowledge having that intelligence about where your data is, that has the most promise. As faras, the automation is concerned. Next step there. It's not just about collecting the information about where your data is, but it's actually applying the analytics, the machine learning and the artificial intelligence to that metadata collection that you've got so that you can then start to create those bots to create those pipelines to start to automate those tasks. We're starting to see some vendors move in that area, moving that direction. There's a lot of promise there >> you guys, at least when I remember. You see, the software is pretty robust taxonomy. I'm sure it's evolved over the years. So how do you sort of define your space? I'm interested in How big is that space, you know, in terms of market size and is a growing and where do you see it going? >> Right. So my my coverage of data integration and data intelligence is fairly small. It's a small, little marketed. I D. C. I'm part of a larger team that looks a data management, the analytics and information management. So we've got people on our team like a damn vessel. Who covers the analytics? Advanced Analytics show Nautical Palo Carlson. He's been on the cable covers, innovative technologies, those I apologize. I don't have that number off the top. >> Okay, No, But your space, my space is it. That's that Software market is so fragmented. And what I d. C has always done well, as you put people on those fragments and you know, deep in there. So So how you've been ableto not make your eyes bleed when you do that, challenging so the data and put it all together. >> It's important. Integration markets about 66 and 1/2 1,000,000,000 >> dollars. Substantial size. Yeah, but again, a lot of vendors Growing number of events in the markets growing, >> the market continues to grow as the data is becoming more distributed, more dispersed. There's no need to continue to integrate that data. There's also that need that growing >> need for that date intelligence. It's not >> just, you know, we've had a lot of enquiries lately about data being fed into machine learning artificial intelligence and people realizing our data isn't clean. We have to clean up our data because we're garbage in garbage. Out is probably more important now than ever before because you don't have someone saying, I don't think that day is right. You've got machines were looking at data instead. The technology that's out there and the problem with data quality. It's on a new problem. It's the same problem we've had for years. All of the technology is there to clean that data up, and that's a part of what I saw. I look at the data quality vendors experience here, sink sort in all of the other data quality capabilities that you get from in from Attica, from Tahoe or from a click podium. Metal is there, and so that part is growing. And there's a lot of more interest in that data quality and that data intelligence side again so the right data can be used. Good data can be used to trust in that data. Can the increase we used for the right reasons as well That's adding that context. Understand that Samantha having all that metadata that goes around that data so that could be used. Most of >> it is one of those markets that you may be relatively small. It's not 100,000,000,000 but it it enables a lot of larger markets. So okay, so it's 66 and 1/2 1,000,000,000 it's growing. It is a growing single digits, double digits. It's growing. It's hovering around the double dip double. It is okay, it's 10%. And then and then who were the, You know, big players who was driving the shares there? Is there a dominant player there? Bunch of >> so infirm. Atticus Number one in the market. Okay, followed by IBM. And I say peas right up there. Sass is there. Tell End is making a good Uh, okay, they're making a nice with Yeah, but there there's a number of different players. There's There's a lot of different players in that market. >> And in the leading market share player has what, 10%? 15%? 50%? Is it like a dominant divine spot? That's tough to say. You got a big It's over 1,000,000,000,000,000,000 right? So they've got maybe 1/6 of the market. Okay, so but it's not like Cisco as 2/3 of the networking market or anything like that. And what about the cloud guys? A participating in this guy's deal with >> the cloud guys? Yeah, the ClA got so there are some pure cloud solutions. There's a relative, for example. Pure cloud MBM mastered a management there. There's I'd say there's less pure cloud than there used to be. But, you know, but someone like an infra matic is really pushing that clouds presence in that cloud >> running these tools, this tooling in in the cloud But the cloud guys directly or not competing at this >> point. So Amazon Google? Yes, Those cloud guys. Yes. Okay, there, there. Google announced data flow back in our data. Sorry. Data fusion back. Google. >> Yeah, that's right. >> And so there they've got an e t l two on the cloud now. Ah, Amazon has blue yet which is both a catalog and an e t l tool. Microsoft course has data factory in azure. >> So those guys are coming on. I'm guessing if you talk to in dramatic and they said, Well, they're not as robust as we are. And we got a big install base and we go multi cloud is that kind of posturing of the incumbents or yeah, that's posturing. And maybe that's I don't mean it is a pejorative. If I were, those guys would be doing the same thing. You know, we were talking earlier about how the cloud guys essentially killed the Duke. All right, do you Do you see the same thing happening here, or is it well, the will the tool vendors be able to stay ahead in your view, >> depends on how they execute. If they're there and they're available in the cloud along with along with those clapper viers, they're able to provide solutions in the same same way the same elasticity, the same type of consumption based pricing models that pod vendors air offering. They can compete with that. They still have a better solution. Easton What >> in multi cloud in hybrid is a big part of their value problems that the cloud guys aren't really going hard after. I mean, this sort of dangling your toe in the water, some of them some of the >> cloud guys they have. They have the hybrid capabilities because they've got some of what they're what they built comes from on premises, worlds as well. So they've got that ability. Microsoft in particular >> on Google, >> Google that the data fusion came out of >> You're saying, But it's part of the Antos initiative. Er, >> um, I apologize. Folks are watching, >> but soup of acronyms notices We're starting a little bit. What tools have you seen or technology? Have you seen making governance of unstructured data? That looks promising? Uh, so I don't really cover >> the instructor data space that much. What I can say is Justus in the structure data world. It's about the metadata. It's about having the proper tags about that unstructured data. It's about getting the information of that unstructured data so that it can then be governed appropriately, making structure out of that, that is, I can't really say, because I don't cover that market explicitly. But I think again it comes back to the same type of data intelligence having that intelligence about that data by understanding what's in there. >> What advice are you giving to, you know, the buyers in your community and the sellers in your community, >> So the buyer's within the market. I talk a lot about that. The need for that data intelligence, so data governance to me is not a technology you can't go by data governance data governance is an organizational disappoint. Technology is a part of that. To me, the data intelligence technology is a part of that. So, really, organizations, if they really want a good handle, get a good handle on what data they have, how to use that, how to be enabled by that data. They need to have that date intelligence into go look for solutions that can help him pull that data intelligence out. But the other part of that is measurement. It's critical to measure because you can't improve what you're not measuring. So you know that type of approach to it is critical Eve, and you've got to be able to have people in the organization. You've got to be able to have cooperation collaboration across the business. I t. The the gifted office chief Officer office. You've gotta have that collaboration. You've gotta have accountability and for in order for that, to really be successful. For the vendors in the space hybrid is the new reality. In my survey data, it shows clearly that hybrid is where things are. It's not just cloud, it's not just on promise Tiebreak. That's where the future is. They've got to be able to have solutions that work in that environment. Working that hybrid cloud ability has got to be able to have solutions that can be purchased and used again in the same sort of elastic type of method that they're able to get consumers able to get. Service is from other vendors in that same >> height, so we gotta run. Thank you so much for sharing your insights and your data. And I know we were fired. I was firing a lot of questions. Did pretty well, not having the report in front of me. I know what that's like. So thank you for sharing and good luck with your challenges in the future. You got You got a lot of a lot of data to collect and a lot of fast moving markets. So come back any time. Share with you right now, Okay? And thank you for watching Paul and I will be back with our next guest right after this short break from M I t cdo. Right back