 Live from the wigwam in Phoenix, Arizona, it's theCUBE, covering Data Platforms 2017. Brought to you by Cubull. Hey, welcome back everybody. Jeff Frick here with theCUBE. I'm joined by George Gilbert from Wikibon and we're at Data Platforms 2017. Small conference down at the historic wigwam resort just outside of Phoenix, talking about kind of a new approach to big data, really, and a cloud-native approach to big data and really kind of flipping the old model on its head and we're really excited to be joined by Tripp Smith. He's the CTO of Clarity Insights up on the panel earlier today, so first off, welcome Tripp. Thank you. Thank you for being here. For the folks that aren't familiar with Clarity Insights, give us a little background. So Clarity is a peer-played data analytics professional services company. That's all we do. We say we advise, build, and enable for our clients. So what that means is data strategy, data engineering, and data science, and making sure that we can, you know, action the insights that our customers get out of their data analytics platforms. Not a real busy area these days. Yeah, it's growing pretty well. Good for you. So a lot of interesting stuff came up on the panel, but one of the things that you reacted to, I reacted to as well from the keynote, was this concept of, you know, before you had kind of the data scientists with the data platform behind them being service providers to the basic business units and really turning that model on its head, giving access to the data to all the business units and people that want to consume that and making the data team really enablers of kind of a platform play. Seemed to really resonate with you as well. Yeah, absolutely. So if you think about it, you know, a lot of the focus on legacy platforms was driven by kind of scarcity around the resources to deal with data. So, you know, you created this almost pyramid structure with IT and architecture at the top, and they were the gatekeepers and kind of the single door where insights got out to the business. So, you know, in the big data world and with cloud, with elastic scale, we've been able to turn that around and actually create much more collaborative friction in parallel with the business, putting the data engineers, data scientists and business focus analysts together and making them more of partners than just customers of IT. Right, very interesting way to think of it as a partner. It's a very different mindset. The other piece that came up over and over in the Q&A at the end was how do people get started? How are they successful? So you deal with a lot of customers, right? That's your business. What are some stories I wonder you can share of best practices when people come, they say, you know, we obviously hired you, wrote a check. But how do we get started? Where do we, you know, where do we go first? What are you, how do you help people out? You know, we focus on self-funding analytics programs. You know, getting those early wins tend to pay for more investment in analytics. So if you look at the ability to scale out as a starting point, then, you know, aligning that business value and the roadmap in a way that's going to, you know, both demonstrate the value along the way and contribute to that capability is important. You know, I think we also recommend to our clients that they solve the hard problems around security and data governance and compliance first because that allows them to deal with, you know, more valuable data and put that to work for their business. So is there any kind of low hanging fruit that you see time and time and time again that just is like, we can do this. We know it's got huge ROI and it's either neglected because they don't think it's valuable or it's neglected because it's in the back room or is there any, you know, kind of easy steps that you kind of find some patterns? Yeah, absolutely. So we go to market by industry vertical. So within each vertical, we've defined kind of the value maps and ROI levers within that business and then align a lot of our analytic solutions to those ROI levers and in doing that, you know, we kind of focus this on being able to build, you know, a small multifunctional team that can work directly with the business and then deliver that in real time, you know, in an interactive way. Right. Another thing you just talked about security and governments, are we past, are we past the kind of security concerns about public cloud? Does that even come up as an issue anymore? You know, I think there was a great comment today that, you know, if you had money, you wouldn't put it in your safe at home. You'd put it in a bank. I miss that one. That's a good one. You know, the cloud providers are really focused on security in a way that they can invest in it that an individual enterprise really can't. So, you know, in a lot of cases, you know, moving to the cloud means letting the experts take on the area that they're really good at and letting you focus on your business. Right. Interesting they had, you know, Amazon is here, Google's here, Oracle's here, and Azure's here, and you know, AWS reinvent one of my favorite things is Tuesday night with James Hamilton, which I don't know if you've ever been. It's a can't miss presentation, but he talks about, you know, the infrastructure investments that Amazon, AWS can make, which again, compared to any individual enterprise, are tremendous in not only in security, but networking and all these other things that they do. So, you know, it really seems at the scale that these huge cloud providers have now reached, give some such an advantage over any individual enterprise, whether it's for security or networking or anything else. So, it's a very different kind of a model. Yeah, absolutely. Or even the application platform, like Google now having Spanner, which has the scale advantage of Cassandra or HBase, but the transactional capabilities of a traditional RDBMS. I guess my question is, once a customer is considering Q-Ball as a cloud first, you know, data platform, how do you help the customer evaluate it relative to the distros that started out on-prem, and then the other cloud native ones that are from Azure and Google and Amazon? You know, I think that's a great question. It kind of focuses back on, you know, letting the experts do what they're really good at. You know, my business may not be differentiated by my ability to operate and support Hadoop, but it's really putting Hadoop to work in order to solve those business problems that makes me money. So, when I look at something like Q-Ball, it's actually going to that expert and saying, hey, own this for me and deliver this in a reliable way, rather than me having to solve those problems over and over again myself. And do you think that those problems are not solved to the same degree by the cloud native services? So, I think there's definitely an ability to leverage cloud native services, but there's also this aspect of administration and management and understanding how those integrate within an ecosystem that I don't think necessarily every company's going to be able to approach in the same way that a company like Q-Ball can. And so, again, being able to shift that off and having that kind of support gives you the ability to focus back on what really makes a difference for you. So, Tripp, we're running out of time. We've got a really tight schedule here. I'm just curious. It's a busy conference season. Big data is all over the place. How did you end up here? What is it about this conference and this technology that got you to come down to the hundred and I think it's only 106 today, whether to take it in? What do you see that's kind of a special opportunity here? Yeah, you know, this is, Data Platforms 2017 has been a really great conference just in the focus on being able to, you know, look at cloud and look at this differentiation outside of the realm of inventing new shiny objects and really putting it to work for new business cases and that sort of thing. All right. Well, Tripp Smith, thanks for stopping by theCUBE. Excellent. Thank you guys for having me. All right. It's George Gilbert. I'm Jeff Frick. You're watching Data Platforms 2017 from the historic Wigwam Resort in Phoenix, Arizona. Thanks for watching.