 Hi, I'm Peter Burris and welcome to another CUBE Conversation from our studios here in Palo Alto, California. We've got another great conversation today. Specifically, we're going to talk about some of the trends and changes in data catalogs, which are emerging as a crucial technology to advance data-driven business on a global scale. And to do that, we've got Elation here. Specifically, Stephanie McReynolds who's the Vice President of Marketing and Elation. Stephanie, welcome back to theCUBE. Thank you, it's great to be here again. So, Stephanie, before we get into this very important topic of the increasing obviously role or connection between knowing what your data is, knowing where it is in business outcomes in a data-driven business world, let's talk about Elation. What's the update? Yeah, so we just celebrated yesterday, in fact, the sixth anniversary of the incorporation of the company. And reflecting on some of the milestones that we've seen over those six years, one of the exciting developments is we went from initially about seven production implementations a couple years after we were founded to now over a hundred organizations that are using Elation. And in those organizations over the last couple of years, we've seen many organizations move from hundreds of users to now thousands of users. An organization like Scout24 has 70% of the company as self-services analytics users and a significant portion of those users now using Elation. So we're seeing companies in Europe, like Scout24 who's in Germany, companies like Pfizer in the United States, Unic Reinsurance in the financial services industry, also hit about 2,000 users of Elation. And so it's exciting to look at our origins with eBay as our very first customer who's now up to about 3,000 users. And then these more recent companies adopt Elation, all of them now getting to a point where they really have a large population that's using a data catalog to drive self-services analytics and business outcomes out of those self-services analytics. So a hundred first rate brands as users, international expansion, sounds like Elation's really going places. What I want to do though is I want to talk a little bit about some of the outcomes that these companies are starting to achieve. Now, we have been on the record here at Silicon Angle of the Cube, Wikibon for quite some time, trying to draw a relationship between business, digital business, and the role that data plays. Digital business transformation in respect is about how you evolve the role that data plays in your business to become more data-driven. It's hard to do without knowing what your data is, where it is, and having some notion of how it's being used in a verified, trusted way. How are you seeing your companies start to tie the use of catalogs to some of these outcomes? What kind of outcomes are folks trying to achieve first off? Yeah, you're right, just basic table stakes for turning an organization into an organization that relies on data-driven decision-making rather than intuitive decision-making requires an inventory. And so that's table stakes for any catalog, and you see a number of vendors out there providing data inventories. But what I think is exciting with the customers that we work with is they are really undertaking transformative change, not just in the tooling and technology their company uses, but also in the organizational structure, in data literacy programs, and driving towards real business impact and real business outcomes. An example of an Elation customer who's been talking recently about outcomes is Pfizer. Pfizer was covered in a Wall Street Journal article recently, also was speaking at Tableau Conference about how they're using a combination of the Elation data catalog with Tableau on the front end and a data science platform called DataIQ in an integrated analytics workbench that is helping them with new drug discovery. And so for populations of ill individuals who may have a rare form of heart disease, they're now able to use machine learning and algorithms that are informed by the Tata catalog to catch 1%, 2% of heart disease patients who have a slight deviation from the norm and can deliver drugs appropriately to that population. Another example of a business outcome would be with an insurance company, very different industry, right? But Munich re-insurance is a huge global re-insurance company. So we think about hurricanes or the fires we had here in the United States. They actually support first line insurers by re-insuring them. They're also founding new business units for new types of risks in the market. An example would be a factory that is fully controlled by robots. Think about the risk of having that factory be taken over by hackers in the middle of the night where there's not a lot of employees on the floor. Munich re-insurance is leveraging the data catalog as a collaboration platform between actuaries and individuals that are knowledgeable in the business to define what are the data products that could support entirely new business units like for cyber crimes and investing in those business units based on the innovation they're doing using the data catalog as a collaboration platform. So these are two great examples of organizations that a couple of years ago started with a data catalog but have driven so many more initiatives than just analyst productivity off of that implementation. Those are great outcomes. One of the talking about robots in the factory, automated factory, one thing if they went, hey, why would make for some interesting viral videos. That's right, that's right. But coming back, but the reason I say that is because in many respects these practices, these relations with the outcomes, the outcomes are the real complex thing. You talk about becoming more familiar with data, using data differently, becoming more data driven. That requires some pretty significant organizational change. And it seems to me, and I'm querying you on this, that the bringing together these users to share their stories about how to achieve these data driven outcomes made more productive by catalogs and related technologies, communities must start to be forming. Are you seeing communities form around achieving these outcomes and utilizing these types of technologies to accelerate the business change? So what's really interesting at an organization like Munich Reinsurance or at Pfizer is there's an internal community that is using the data catalog as a collaboration platform and as kind of a social networking platform for the data nerd. So if I am a brand new user of self-service analytics, I may be a product manager who doesn't know how to write a SQL query yet, who doesn't know how to go and wrangle my own data. They never want to learn how to do it. They never want to, they never want to. Who may not know how to go and validate data for quality or consistency. I can now go to the data catalog to find trusted resources of data assets, be that a dashboard or report that's already been written, or be that raw data that someone else has certified or just has used in the past. So we're seeing this social influence happen within companies that are using data catalogs where they can see from the data catalog pages who's used, who's validated this data set so that I now trust the data. And then what we've seen happen just within the last year and a half or so is these organizations, the sponsors of the data catalog, these organizations are starting to share best practices naturally with one another and saying, hey, across organizations. Across organizations. And so there has been a demand for our relation to get out into the market and help catalyze the creation of communities across different organizations. We kicked off within the last two months a series of meetings that we've called Revelation. An opportunity. R-E-V-A-L-A-T-I-O-N. That's right, R-E-V-A-L-A-T-I-O-N. And the thinking behind the name is if you can start to share best practices in terms of how you create a data driven culture across organizations, you can begin to really get breakthrough speed, right? In making this transformation to a data driven organization. And so I think what's interesting at the Revelation events is folks are not talking just about how they're using the tool, how they're using technology. They're actually talking about how do we improve the data literacy of our organizations and what are the programs in place that leverage maybe the data catalog to do that. And so they're starting to really think about how does not just the technical architecture and the tooling change in their organizations, but how do we close this gap between having access to data and trusting the data and getting folks who maybe aren't too familiar with the technical aspects of a data supply chain, how do we make them comfortable in moving away from intuitive decisions to data driven decisions? Yeah, so the outcome really is not just the application of the tool, it's the new behaviors in the business that are associated with data driven. But to do that, you still have to gain insight and understand what kinds of practices are best used with the tool itself. So it's got to be a combination. But Elation has been, if I can say this, Elation's been on this path for a while. Not too long ago, you came on the cube and you talked about trust check, which was an effort to establish conventions and standards for how data could be verified and validated so that it would be easy to use so that someone could use the data and be certain that it is what it is without necessarily having to understand the data. Something could be very good, for example, for folks who are very focused on the outcome and not focused on the science of the data associated with it. So is this part of, is revelation, trust check? Is this part of the journey that you're on to try to get people to see this relationship between data-driven business and knowing more about your data? It absolutely is. It's a journey to get organizations to understand what is the power that they have internally within this data and close the gap which is in part organizational but in part for individuals, users, psychological and how do you get to a trusted decision? And so you'll continue to see us invest in features like trust check that highlight how technology can make recommendations, can help validate and verify what the experts in the organization know and propagate that more widely. And then you'll also see us share more best practices about how do you start to create, write organizational change and how do you start to impact the psychology of fear that we've had in many organizations around data? And I think that's where elation is uniquely placed because we have the highest number of data catalog customers of any other vendor I'm familiar with in the space and we also have a unique design approach. When we go into organizations and talk about adopting a data catalog it's as much about how do our products support psychological comfort with data as well as how do they support the actual workflow of getting that query completed or getting that data certified. And so I think we've taken a bit of a unique approach to the market from the beginning where we're really designing holistically for not just how do you execute a software program that supports workflow but how do you start to think about how the data consumer actually adopts that best practices and starts to think differently about how they use data in a more confident way? Well, I think the first time that you and I talked in the queue was probably 2016 and I was struck by the degree to which elation as a tool and the language that you used in describing it was clearly designed for human beings to use it as opposed to for data. And I think that that is a unique proposition because at the end of the day the goal here is to have people use data to achieve outcomes and not just to do a better job of managing data. And that doesn't mean that, I mean, we have a ton of machine learning and AI in the product so that doesn't take away from the power of those algorithms to speed up human work and human behavior. But we really believe that the algorithms need to complement human input and that there should be a human in the loop with decision making and that the algorithms should then propagate the knowledge that we have of experts in the organization and that's where you get the real breakthrough in business outcomes when you can take input from a lot of different human perspectives and optimize an outcome by using technology as a support structure. In a way that's familiar and natural and easy for others in your organization. That's right, that seems, you know, if you go back to when we were all introduced to Google it was a little bit of an odd thing to go ask Google questions and get results back from the internet. We see data evolving in the same way. Elation is the Google for your data in your organization. At some point it'll be very natural to say, hey Elation, what happened with Revenue last month? And Elation will come back with an answer. So I think that that feature is in sight where it's very easy to use data. You know you're getting trusted responses. You know that they're accurate because there's either a certification program in place that the technology supports or there's a social network that's bubbling this information up to the top that is a trusted source. And so that evolution in data needs to happen for our organizations to broadly see analytic driven outcomes. Just as in our consumer or personal life, Google had to show us a new way to evolving, you know to kind of the answer machine on the internet. Excellent, Stephanie McReynolds, Vice President of Marketing, Elation talking to us about building communities to become more of a, to achieve data-driven outcomes utilizing data catalog technology. Stephanie, thanks very much for being here. Thanks for inviting me. And once again, I'm Peter Burris and this has been another Cube Conversation. Until next time.