>> from Boston, Massachusetts. It's the queue covering active eo 2019. Data driven you by activity. >> Welcome back to Boston. Everybody watching the Cube, the leader and on the ground tech coverage. My name is David Locke. They still minimus here. John Barrier is also in the house. We're covering the active FIO data driven 19 event. Second year for this conference. It's all about data. It's all about being data driven. Charlie Quanis here. He's the director of data and a I offering management and IBM. Charlie, thanks for coming on The Cube. >> Happy to be here. Thank you. >> So active Theo has had a long history with IBM. Effect with company got started at a time the marketplace took a virtual ization product and allowed them to be be first really and then get heavily into the data virtualization. They since evolved that you guys are doing a lot of partnerships together. We're going to get into that, But talk about your role with an IBM and you know, what is this data and a I offering management thing? >> He absolutely eso data and a I is our business unit within IBN Overall Corporation, our focus and our mission is really about helping our customers drive better business outcomes through data. Leveraging data in the contacts and the pursuit of analytics and artificial intelligence are augmented intelligence. >> So >> a portion of the business that I'm part of his unified governance and integration and you think about data and I as a whole, you could think about it in the context of the latter day. I often times when we talk about data and I we talk about the foundational principles and capabilities that are required to help companies and our customers progress on their journey. They II and it really is about the information architecture that we help them build. That information architectures essentially a foundational prerequisite around that journey to a i. R. Analytics and those layers of the latter day I r. Collecting the data and making sure you haven't easily accessible to the individual's need it organizing the data. That's where the unified governance in Immigration folio comes into play. Building trusted business ready data, high quality with governance around that making shorts available to be used later, thie analyzed layer in terms of leveraging the data for analytics and die and then infuse across the organization, leveraging those models across the organization. So within that context of data and I, we partnered with Active Theo at the end of 2018. >> So before we get into that, I have started dropped. You know, probably Rob Thomas is, and I want a double click on what you just said. Rob Thomas is is famous for saying There is no way I without a training, no, no artificial intelligence without information architecture so sounds good. You talk about governance. That's obviously part of it. But what does that mean? No A without a. >> So it is really about the fundamental prerequisites to be able to have the underlying infrastructure around the data assets that you have. A fundamental tenet is that data is one of your tremendous assets. Any enterprise may have a lot of time, and effort has been spent investing and man hours invested into collecting the data, making sure it's available. But at the same time, it hasn't been freed up to be. A ploy used for downstream purpose is whether it's operational use cases or analytical cases, and the information architecture is really about How do you frame your data strategy so that you have that data available to use and to drive business outcomes later. And those business outcomes, maybe results of insights that are driven out of the way the data but they got could also be part of the data pipeline that goes into feeding things like application development or test data management. And that's one of the areas that were working with that feeling. >> So the information architecture's a framework that you guys essentially publish and communicate to your clients. It doesn't require that you have IBM products plugged in, but of course, you can certainly plug in. IBM products are. If you're smart enough to develop information architect here presumably, and you got to show where your products fit. You're gonna sell more stuff, but it's not a prerequisite. I confuse other tooling if I wanted to go there. The framework is a good >> prerequisite, the products and self of course, now right. But the framework is a good foundational. Construct around how you can think about it so that you can progress along that journey, >> right? You started talking about active fio. You're relationship there. See that created the Info sphere Virtual data pipeline, right? Why did you developed that product or we'll get into it? >> Sure, it's all part of our overall unified covers and integration portfolio. Like I said, that's that organized layer of the latter day I that I was referring to. And it's all about making sure you have clear visibility and knowing what they had assets that you have. So we always talk about in terms of no trust in use. No, the data assets you have. Make sure you understand the data quality in the classification around that data that you have trust the data, understand the lineage, understand how it's been Touch Haussmann, transformed building catalog around that data and then use and make sure it's usable to downstream applications of down street individuals. And the virtual data pipeline offering really helps us on that last category around using and making use of the data, the assets that you have putting it into directly into the hands of the users of that data. So whether they be data scientist and data engineers or application developers and testers. So the virtual data pipeline and the capabilities based on activity sky virtual appliance really help build a snapshot data provide the self service user interface to be able to get into the hands of application developers and testers or data engineers and data scientist. >> And why is that important? Is it because they're actually using the same O. R. O R. Substantially similar data sets across their their their their work stream. Maybe you could explain that it's important >> because the speed at which the applications are being built insights are being driven is requiring that there is a lot more agility and ability to self service into the data that you need. Traditional challenges that we see is you think about preparing to build an application or preparing to build an aye aye model, building it, deploy it and managing it the majority of the time. 80% of the time. Todd spilled front, preparing the data talking, trying to figure out what data you need asking for and waiting for two weeks to two months to try to get access to that data getting. And they're realizing, Oh, I got the wrong data. I need to supplement that. I need to do another iteration of the model going back to try to get more data on. That's you have the area that application developers and data scientists don't necessarily want to be spending their >> time on. >> And so >> we're trying to shrink >> that timeframe. And how do we shrink? That is by providing business users our line of business users, data scientist application developers with the individuals that are actually using the data to provide their own access to it, right To be able to get that snapshot that point in time, access to that point of production data to be able to then infuse it into their development process. They're testing process or the analytic development process >> is we're we're do traditional tooling were just traditional tooling fit in this sort of new world because you remember what the Duke came out. It was like, Oh, that enterprise data warehouses dead. And then you ask customers like What's one of the most important things you're doing in your big data? Play blind and they'd say, Oh, yeah, we need R w. So I could now collect more data for lower costs keep her longer low stuff. But the traditional btw was still critical, but well, you were just describing, you know, building a cube. You guys own Cognos Obviously, that's one of the biggest acquisitions that I'm being made here is a critical component. Um, you talk about data quality, integration, those things. It's all the puzzle fits together in this larger mosaic and help us understand that. Sure >> and well, One of the fundamental things to understand is you have to know what you have right, and the data catalogue is a critical component of that data strategy. Understanding where your enterprise assets sit, they could be structured information that may be a instruction information city and file repositories or e mails, for example. But understanding what you have, understanding how it's been touched, how it's been used, understanding the requirements and limitations around that data understanding. Who are the owners of that data? So building that catalog view of your overall enterprise assets fundamental starting point from a governess standpoint. And then from there, you can allow access to individuals that are interested in understanding and leveraging that date assets that you may have in one pool here challenges data exists across enterprise everywhere. Right silos that may have rose in one particular department that then gets murdered in with another department, and then you have two organization that may not even know what the other individual has. So the challenge is to try to break down those silos, get clarity of the visibility around what assets so that individuals condemned leverage that data for whatever uses they may have, whether it be development or testing or analytics. >> So if I could generalize the problem, Yeah, too much data, not enough value. And I'll talk about value in terms of things that you guys do that I'm inferring. Risk reduction. Correct uh, speed to insights. Andan. Ultimately, lowering costs are increasing revenue. That's kind of what it's all >> the way to talk about business outcomes in terms of increase revenue, decrease costs or reduce risk, right in terms of governance, those air the three things that you want to unlock for your customers and you don't think about governance and creating new revenue streams. We generally don't think about in terms of reducing costs, but you do think about it oftentimes in terms of reducing your risk profile and compliance. But the ability to actually know your data built trust and then use that data really does open up different opportunities to actually build new application new systems of engagement uses a record new applications around analytics and a I that will unlock those different ways that we can market to customers. Cell two customers engage our own employees. >> Yes. So the initial entry into the organism the budget, if you will, is around that risk reduction. Right? Can you stand that? I got all this data and I need to make sure that I'm managing a corner on the edicts of my organization. But you actually seeing we play skeptic, you're really seeing value beyond that risk reduction. I mean, it's been nirvana in the compliance and governance world, not just compliance and governance and, you know, avoiding fees and right getting slapped on the wrist or even something worse? Sure, but we can actually, through the state Equality Initiative and integration, etcetera, etcetera Dr. Other value. You actually seeing that? >> Yes. We are actually, particularly last year with the whole onslaught of GDP are in the European Union, and the implications of GDP are here in the U. S. Or other parts of the world. Really was a pervasive topic on a lot of what we were talking about was specifically that compliance make sure you stay on the right side of the regulation, but the same time investing in that data architecture, information, architecture, investing in the governance programme actually allowed our customers to understand the different components that are touching the individual. Because it's all about individual rights and individual privacy. It's understanding what they're buying, understanding what information we're collecting on them, understanding what permissions and consent that we have, the leverage their information really allowed. Our customers actually delivered that information and for a different purpose. Outside of the whole compliance mindset is compliance is a difficult nut to crack. There's requirements around it, but at the same time, they're our best effort requirements around that as well. So the driver for us is not necessarily just about compliance, But it's about what more can you do with that govern data that you already have? Because you have to meet those compliance department anyway, to be able to flip the script and talk about business value, business impact revenue, and that's everything. >> Now you So you're only about what, six months in correct this part of the partnership? All right, so it's early days, but how's it going and what can we expect going forward? >> Don't. Great. We have a terrific partner partnership with Octavio, Like tippy a virtual Or the IBM virtual data pipeline offering is part of our broader portfolio within unified governance and fits nicely to build out some of the test data management capability that we've already had. Optimal portfolio is part of our capability. Said it's really been focused around test data management building synthetic data, orchestrating test data management as well. And the virtual data pipeline offering actually is a nice compliment to that to build out our the robust portfolio now. >> All right, Charlie. Well, hey, thanks very much for coming in the house. The event >> has been terrific. It's been terrific. It's It's amazing to be surrounded by so many people that are excited about data. We don't get that everywhere. >> They were always excited about, Right, Charlie? Thanks so much. Thank you. Thank you. All right. Keep it right there, buddy. We're back with our next guest. A Valon Day, John. Furry and student Amanda in the house. You're watching the cube Active eo active Fio data driven. 2019. Right back