 Live from Las Vegas. It's theCUBE. Covering Informatica World 2018. Not to you by Informatica. Hello and welcome back to theCUBE. We are broadcasting from Informatica World 2018, the Venetian in Las Vegas. I'm Peter Burris. Once again my co-host is Jim Kabilis, Wikibon SiliconANGLE. And at this segment we're joined by Matthew Cox, who's the director of data and technology services at McAfee. Welcome to theCUBE, Matthew. Thank you very much. Glad to be here. So you're a user, so you're on the practitioner side. Tell us a little bit about what you're doing at McAfee then. So from a technology standpoint, I mean my role, per se, is to create and deliver an end to end vision and strategy for data, data platforms and services around those. But always identify and align to measurable business outcomes. And so my goal is to leverage data and bring meaning of data to the business. And help them leverage for data-driven decisions or toward business outcomes and business goals. So you're working both with the people who are managing the data or administering the data, but also the consumers of the data and trying to arbitrate and match needs. Absolutely, so the first part of my career, I was in IT for many years and then I moved into the business. And so for probably the last 10 years I've been in sales and marketing in various roles. And so it gives me kind of a unique perspective in that I've lived their life and probably more importantly, I understand the language of business. And I think too often, in our IT roles, we get into an IT speak and we aren't translating that into the world of the business. And I have been able to do that. So I'm really acting as a liaison and kind of bringing what I've seen in the business to IT and helping us deliver solutions that drive business outcomes and goals. What strategic initiatives are you working at McAfee that involve data? Well, we have a handful. Number one, I would say that our first goal is to build out our hub and spoke model with MDM and really delivering our... Our master data manager, correct. Delivering our, I mean, because in MDM that is where we define our accounts, our contacts, we build our upward linking parents and our account hierarchies and we create that customer master that's the one lens, right? That we want to see our customers across all of our ecosystem. And so we're finishing out that hub and spoke model which is kind of a industry best practice for both real time and batch type integrations. But on top of that, you know, MDM is a great platform and it gives you that that the end to end data flow is another area that we've really put a priority on and making sure that as we move data throughout the ecosystem, we are looking at the transformations, we're looking at the data quality, we're looking at governance to make sure that what started on one end of the spectrum looked the same or appropriately was transformed by the time it gets to the other side as well. You know, I'll say data quality three times, data quality, data quality, data quality. You know, for us, it's really about mastering the domain of data quality and then looking at other areas of compliance. I mean, GDPR just being one, right? There's a number of compliance areas around data, but GDPR is the most relevant one at this time. There's compliance, there's data quality, but also there must be operational and analytical insights to be gained from using MDM. Can you describe how McAfee, what kind of insights you're gaining from utilization of that technology in your organization? Sure, well, there's, you know, and MDM's a piece part of that, right? So I can talk about how the account hierarchy gives us a full view, right? Now you've got other products like data quality that bolt on that allow us to filter through and make sure that that data looks correct and is augmented and appended correctly. But MDM gives us that wonderful foundation of understanding, you know, the lens of an account, no matter what landscape or platform we're leveraging, right? So if I'm looking at reporting, if I'm looking at my CRM system, if I'm looking at my marketing automation platform, I can see account A consistently, right? So what that allows me to do is not only have analytics built that I can have the same answers, right? Because, you know, if I give a different number for company A in every platform, we've got a problem, right? I should be seeing the same information across the landscape. But importantly, it also drives the conversation between the different business units, right? So I can have marketing talk to sales, talk to operations about company A, and they all know who we're talking about. And historically, that's been a problem for a lot of companies because a source system would have company A a little bit differently or would have it, the data around it differently or see it differently from one spectrum to the next. And we're trying to make that one lens consistent. So MDM allows you to have that one consistent legs based on the customer. But McAfee, I'm sure, is also in the midst of finding new ways of sources of data, new ways of using data, like product information, how it's being used for improving products, improving service quality. How is it, how is that hub and spoke approach able to accommodate some of the evolving challenges or evolving definitions and needs of data since so much of that data often is localized to specific activities that after you're performed. And in the business, there is a lot of data that happens very specific to that silo, right? So I have certain data within, say, marketing that I really is only marketing data, right? So one of the things that we do is we differentiate data, right, and this even kind of goes to governance, right? Even saying there's some data as an organization is kind of our treasure that we want to make sure we manage consistently across the landscape of the ecosystem. There's some data that's very specific to a business function that doesn't need to proliferate around. So we don't necessarily have the type of governance that wouldn't necessitate the level of governance that an ecosystem level data attribute would. So MDM provides, in that hub and spoke is what's really powerful for that, it was it relates to that account domain, right? Because you talk about product, right? Product is another area we may go look at at some point adding a product domain into MDM, but today with our customer domain and kind of our partners as well, it gives us the ability to, with this hub and spoke topology, to do real time and batch was before it may have been a latency as we moved information around if things could get either out of sync or there'd be a delay. With that hub and spoke, we're able to now have a real time integration, real time interaction, so I can see changes at the spoke, right? So the spoke pops back to hub, hub delivers that back out again so I can have something happening in marketing, translate that to sales, very quickly translate that out to service and support. And that gives me the ability to have clarity, consistency and timeliness across my ecosystem. And the hub and spoke helps drive that. Well, tell us about, you just alluded to it, sales and marketing, how is customer data as an asset that you manage through your MDM and environment? How is that driving better engagement with your customers? Well, it drives better engagement. First of all, you said an important thing, which is asset, right? So we are very keen on viewing data as an asset. I mean, systems come and go, platforms come and go, right? You know, CRM tool today, CRM tool number two tomorrow, but data always is, right? So one of the things that we've done is try to house and put a label on data as an asset, something that needs to be managed, it needs to be maintained, it needs to be, have an investment to, right? And govern, because if you don't, then it's going to decline in value over time, right? Just like a physical asset, like a building, if you don't maintain it and invest, it deteriorates. The same with data. And what's really important about getting data from a customer standpoint is that the more we can align quality data, right? Again, looking at that, not all data, trying to govern all data is very difficult, right? But there's a treasure of data that helps us make decisions about our customers. But having that data aligned consistently to a lens of an account that's driven by MDM, proliferate across our ecosystem so that everyone knows how to act and react accordingly with regards to their function, gives us a very powerful process that we can engage our customers. So that customer experience becomes consistent as well. Right, if I'm talking to someone in sales and they understand me differently than I'm talking to someone in support versus talking to someone in marketing or another organization, it creates a differentiated customer experience, right? So if I can get that, how's that customer data aligned to one lens of a customer? That provides that ubiquity and a consistency from a view with our customers. Talk to us about governance and stewardship of the data. Who owns that data? Is it customer data? Is it sales? Is it marketing? Or is there another specified data steward who manages that data? Well, there's several different roles that you've got to hit through. So stewardship, right? So we have within my data and technology services organization, we have a stewardship function, right? So we steward data, act on data, we take those, there's processes that we put in place, right? That's your default process and that's how we steward data and augment data over time. We do take very specific requests from sales and marketing, more likely when it comes to an account from marketing, I'm sorry, from sales, who sales will guide, move this, change this, alter that. So from a domain perspective, one of the things they're working through right now is domain, data domains and who has, I don't know if you're familiar with racing models, but who is responsible, who's accountable, who's consulted, who just receives an interest or gets information about it. But understanding how those data domains play against data is very, very important. We're working through some of that now, but typically from a customer data, we align more towards sales because they have that direct engagement. But part of it also is that differentiated view, right? There's, who has the most authority, the most knowledge about the top 500, top 1,000, top 2,000 customers is different than the people at customer 10,000, right? So we usually have different audiences that play who helps us govern and steward that data. So one of the tensions, one of the tensions that's been in place for years as we tried to take, as we tried to codify and capture information about engagement was who put the data in, what was the level of quality that got in there? And in many respects, the whole CRM thing took a long time to work, precisely because what we did is we moved data entry jobs from administrators into sales people and they rebelled. So as you think about the role of the quality plays and how you guide your organization to become active participants in data quality, what types of challenges do you face in communicating to the business, how to go about doing that and then having your systems reflect what is practical and real in the rest of the organization? Well, there's, it's a number of things. First of all, you have to make data relevant, right? If the data that three people are entering is not relevant and isn't meaningful to them then the quality isn't going to be there because they don't have a purpose or a reason to engage it. So the first thing is help make the data be relevant to the people who are your data creators, right? And that's also to your business leaders, right? You also want the business leaders coming to you and talking about data, not just systems, right? And that's one of the things we're working toward as well. But as part of that though is giving them tools to ease the process of data create, right? If I can, if I can go into my CRM tool instead of having to type in a new account, if I can click on a tool and say, hey, send to CRM or add to CRM. So it's literally more of a click and action that moves data. So I ensure that I have a good quality source that moves into my data store, right? That removes that person from being in the middle and making those typing mistakes or error mistakes. So it's really about the data create process and putting a standard there, which is very important, but also then having your cleansing tools and capabilities in your back end like the MDM or a data stewardship function. So by making the activity valuable you create incentive for them to stay very close to quality considerations. Absolutely, because at the end of the day, they use that old term garbage in, garbage out. And we try and be very clear with them, listen, some day you're going to want to see this data and you probably should take the time to put quality effort in the beginning. Got it, one last quick question. If you think about five years, how is your role going to change? 30 seconds. I think the role is going to change in going from an IT centric view where I'm looking at tools and systems to driving business outcomes and addressing business goals and really talking to the business about how do they leverage data as a meaningful asset to move their business forward versus just how am I deploying stewardship governance and systems and tools? Excellent, Matthew Cox, McAfee, data quality and utilization. Absolutely. Once again, you're watching theCUBE. We'll be back in a second.