 Live from Cambridge, Massachusetts, it's The Cube at the MIT Chief Data Officer and Information Quality Symposium with hosts Dave Vellante and Jeff Kelly. Welcome back to Cambridge, Massachusetts, everybody. This is Dave Vellante at Wikibon.org. I'm here with Jeff Kelly, who's Wikibon's big data analyst. This is Silicon Angles, The Cube. Live, Mobile Studio. We bring to all shapes and sizes of events. No event is too small. About three, four hundred people at this event, Jeff, would you say? Something around here. It's a great event. We were here last year. It's the hashtag M-I-T-I-Q, which stands for Information Quality, and the focus, of course, is on information quality, although last year really was a big theme around the Chief Data Officer and it has really evolved into a Chief Data Officer event. Informatica is one of the sponsors of the event. Dominic Sartorio is here. Informatica is all about information quality, Dominic. That's right. So thanks very much for making some time and slipping into The Cube here. Glad to have you. Oh, thanks for having me. Yeah, so talk about Informatica's interests in this conference. I guess it's kind of obvious, but I want to talk about that and what you see as the CDO role and how that's emerging. Right. Well, Informatica, as you know, has had a long history in data management and data integration. It started as an ETL vendor, but we've grown as the industry around data has grown. In the last few years, we've observed how many enterprises, most of them are our customers, treat data more strategically. They treat it as a critical asset to the business. And in more recent years, especially the last two or three years, we have found that organizations taken so seriously, they establish a C-level role, the Chief Data Officer, with the responsibility of ensuring that data is a valuable asset and be trusted by the business. So we've found that that is a key stakeholder in our relationship with those customers. And hence, that brings us to a point such as this, so we can network and learn from that. And we were talking off camera. To date, it's been very industry-specific. I think you were throwing, your numbers suggest that around, would you say, 20% of organizations? About 20% of organizations, enterprises, now have one or more Chief Data Officers. And that's grown tremendously by our own surveys. It was low teens last year, single digits the year before. It started as being more focused in data-driven industries with a lot of regulatory requirements like financial services, public sector. But more recently, we've seen it now in all industries. We're seeing it in retail and manufacturing. We're seeing it in oil and gas. So industries that you may not really think of being regulatory driven, but nonetheless need data to drive better business results. In your experience, in most cases, is that CDO an independent role? Or does it report into the CIO? It varies, actually. Sometimes it reports to the CIO. But I'd say a majority of the time, certainly more than half, it actually reports up to a business function like a Chief Marketing Officer or a Chief Operating Officer. And sometimes you may have multiple CDOs per line of business. So we found that the CDO role and the role, excuse me, generally the role of accountability to ensure that data has value to the business is most successful when it's actually embedded in the business. Because the business knows better than anybody else exactly what they need out of their data. What does it need for data to be trustworthy in a form that business and users cannot make the most of themselves? Dominic, in those situations where you're seeing, I'll call it, I don't mean a pejorative, but a CDO creep. We have multiple CDOs. You saw that certainly with the IT, the CIO function. Is there an Uber? Data's are an Uber CDO? Or is it more sort of a line of business driven? What are you seeing there? It almost depends on the class or category of data you're dealing with. There's certain data that has enterprise-wide relevance, customer data. Or if you're a retailer or product data, there's certain data that you need to centrally manage so that everybody in the organization has that common trusted view. And that should be centrally managed. There should be one overall owner, executive, accountable for ensuring the trust of that data and the organization policies around it. And other kinds of data may only be relevant to a given business function or a given line of business. And that's okay to manage locally. No need to over-engineer that kind of data. So let's dig in a little bit about what you're seeing in terms of the actual responsibilities of a CDO. So I think we most would agree, certainly it's around data governance and data quality, making sure you've got trusted data throughout the organization. But there's also the component of actually making use of that data. Is there maybe a component around the actual tools and technologies used to process data? How are you seeing that the responsibility is specific to CDO's role over the last couple years? Yeah, and it's still evolving. But there are some patterns that we're starting to see. One is they do own data governance, and governance includes both the people, the process, and the choice of tools and technologies used to both define and enforce those policies. They also have some accountability over what are the results of business results of that data. So they may own the analytics function. They may own the business intelligence and data warehousing and other tools that are used for that. They may also own some degree of the operations of disseminating data and ensuring the right data gets to the right people at the right time. They've often that manifests itself as a master data management function, a customer hub or a product hub, for example. So that's part of the ownership that I've seen under the Chief Data Office. But I think separately, but also very importantly, I also see CDO's as being the Chief Data Evangelist in the organization. Building a culture of accountability and valuing data as an asset, educating different business groups about why it's important for them to take effective ownership of their data so we can work better. Yes, talk a little bit more about that. The role of the CDO when it comes to actually, not just evangelizing, but also kind of being a, I've heard it called the Chief Diplomacy Office. We've got an immediate conflict between you've got the business, you've got operations, you've got IT, you could have disputes over data ownership over objectives of data-related projects. Talk about some of those relationship-building skills that a CDO might need. So often when a new CDO joins the company and where they get promoted to the role if they're internal, what led that role to exist in the first place is generally a vague sense among the senior executives that data is important, but they're not going to know down in the trenches of how to actually execute and implement that. So you have to bring in the CDO whose first job is to kind of figure it out. So usually the successful CDO tries not to boil the ocean. You know, they start small. They look at what is the most critical business processes or business problems that need good quality data in order to be most effective. Frequently it's a regulatory requirement, but it doesn't have to be. So let's start there. And that's usually the quickest win that they can achieve. And because it is a critical business function where the importance of data is pretty unambiguous, it's pretty easy to build the organizational support around it. Then you build the policies and processes to be successful there. And once you've demonstrated straight its success, then you can highlight that, use that as a banner you can wave with other organizations, with other domains of data. And then you can gradually build your sphere of influence that way. So that's why a CDO is effective. It starts small. And just in terms of your... What's your opinion on the establishment of the CDO generally? The idea of establishing a new CDO position is not something to take lightly. Based on what you've seen in your customer base, those customers that have established CDO versus those that haven't, are you seeing overall a beneficial move? Are we still too early to tell? What is your opinion about just the sheer existence of the position? Absolutely it's beneficial. The fact that the role exists demonstrates that there definitely is a culture change, maybe almost a societal change going on in valuing data as its own asset. For a long time organizations have viewed obviously finances as an asset, human resources as an asset, real estate facilities, etc. These are all assets that for a long time have had a C level or equivalent with an organization's job is to get value out of it. Data has always been important to organizations, but it's only recently that I think people are starting to realize it. So having a C level person there with an organization around them, I think is great. It raises more awareness around data being a critical asset to new organizations. I wonder if we could talk a little bit about Informatica and its role in this whole big data meme. Yeah. It's been an interesting company been around for a long time. Went through the dot-com bubble and had a big ascendancy and has really come back in a pretty big way. What's driven that? Obviously the analytics pieces has been a driver, an execution of the things, but I wonder if you could talk about that journey a little bit and where you fit. Right. So I've seen it more as an evolutionary trend than a revolution. I think a lot of industry players and vendors like to think of this as a revolutionary thing. There are some new technologies such as Hadoop that enable processing data much greater values than before. But the part of this that's evolutionary is that I actually see there's been a gradual rollout of a combination of technologies that enable processing data much more broadly or in much greater volumes and being able to process a wide varieties of data including unstructured and social data. So do think of all the sensors and devices out there that are in the networks and just don't talk about the internet of things, talk about mobile devices that makes data much more accessible to the average consumer. And there are also societal changes. So, you know, new generations entering the workplace that grew up immersed in computing and immersed in data. So you have a combination of these things that have been happening gradually, both technologies and also societal and generational changes that resulted in more data being available and being used by more consumers for more use cases and a greater variety of things. So for Informatica, we've also treated this as kind of an evolutionary way. Our technology for processing data, the guts of it, which we call the Vibe data processing engine, really hasn't changed significantly in 15 years. But what has changed is the scale at which it can operate, the number of use cases it can operate. You can write it in Hadoop, you can write it in the cloud. So the sheer diversity of use cases that we've made it relevant for. So that's how we view big data. It's an evolution of both technology, society trends, and also breadth of use cases that data is useful. But it feels like there's a tailwind for a company like yours. You know, I think, I've often said a lot of the promises of the enterprise data warehouse were not lived up to in the last decade. And now, all of a sudden, the promises are back, front, and center. And this seems to be light at the end of that. The more than light, it seems to be, like I say, a big tailwind. So that has had to help your business. I agree with what you were saying, that combinatorial effect of all these mega trends. How is it that you guys have been able to take advantage of that? Whereas others seem to somehow, if you're a hot startup, if you're cloud air and you can raise, you know, 700 million, okay, great, you're going to get a good valuation for a company. But, you know, some of the visualization guys, obviously there's guys like Splunk, but you guys are a traditional company that has been able to benefit from that. Why is that? Where some others have struggled. Yeah, we started as basically a one-use case company, ETL, and now it made shock folks to hear this. It's now a relatively small minority use case for us, you know, revenue-wise. And, you know, we've gone out of our way to establish good strategic relationships at senior levels of our organization. And we see and understand, what are the different things you're doing with data? It's not enough to just load your data warehouse. That data needs to be clean and trusted. It's not enough to just trust it. It also needs to be secure. And it's not enough to just always have your data warehouse all the time. Sometimes you need to put it in other environments or technologies to be more accessible. Sometimes you need to archive it. So by engaging with our customers in a more strategic way, we're able to see that there are these other patterns and other use cases that many of our customers want to manage more holistically. You know, they don't see this as one or more projects in isolation want to manage them holistically. So I think that we've done well to be responsive to customer needs and then be able to invest in the relevant use cases and technologies as they come along. All right, Dominic, we'll leave it there. Thanks very much for taking time out for everybody. Jeff Kelly and I and Paul Gillum will be back right after this word. This is The Cube. We're live from MIT in Cambridge.