 Good morning everybody and welcome to Big Data SV. Come down and hang out with us today as we have continued conversations. Will this trend, this Big Data trend, solve the problems that decision support and business intelligence couldn't solve? We're going to talk about that today. Gentlemen, welcome to the queue. We're setting up for the digital business era. What do people really want to do in this Big Data analytics? I want to ingest a lot of information. I want to enrich it. I want to analyze it. I want to take actions and I want to go park it. Leveraging everything that is open source to build models and put models in production. We talk a little bit like it's Google box for your data. So I no longer have to send daily data dumpster partners making simply query the data themselves. We've taken the two approaches of enterprise analytics and sort of self-service and tried to create a scenario where you kind of get the best of both worlds. The epicenter of this whole data management has to move to cloud. It saves you a lot of time and effort. You can focus on more strategic projects. Do you agree it's kind of bifurcated? It is. There's the Spotify's and the Uber's and the AirBnB's that are crushing it and then there's a lot of traditional enterprises that are still still pipe and struggle it. Marketing people, operations people, finance people, they need data to do their jobs. Their jobs are becoming more data driven but they're not necessarily data people. They're depending on the vendor landscape to provide them with an entry level set of tools. Don't make me work harder. And add new staff. Solve the problem. Yeah, it's all about solving problems. A lot more on machine learning now and artificial intelligence and frankly a lot of discussion around ethics. Data governance. It is in fact a business imperative. Marketers want all the customer data they can get, right? But there's social security numbers, PII. Who should be able to see and use what? Because if this data is used inappropriately then it can cause a lot of problems. Creating that visibility is very important. The biggest casualty is going to be their customer relationship if they don't do this because most companies don't know their customers fully. The key to digital transformation is really a lot around the concept of real time. If anybody deals with a data that's in motion you lose because I'm analyzing as it's happening and then you would be analyzing it after at rest. Speed is so important these days and the new companies that are grasping data aggressively putting it somewhere where they can make decisions on it on a day-to-day basis, they're winning. Come on down, be part of our audience. We also have a great party tonight where you can network with some of our experts and analysts. Our expectation is that as the tooling gets better we will see more people be able to present themselves truly as capable of doing this and that will accelerate the process. To me one of the first things a CDO has to do is understand how a company gets value out of its data. You can either run away from that data and say look I'm going to not, I'm going to bury my head in the sand, I'm going to be a business, I'm just going to forget about that data stuff and that's certainly a way to go. It's a way to go away. It's easy to get overwhelmed for companies but it's like you have to pick somewhere. You don't have to go sit in the basement for a year having something that is the unicorn in the business. It's small quick wins. We're not afraid of making mistakes. If we provision infrastructure and we don't get it right the first time we just change it. You know that's something that we would just never be able to do previously in the data center. When companies get started with the right first project they can build on that success and invest more, right? Whereas you know if you're not experimenting and trying things and moving you're never going to get better. Thanks for watching everybody. This is The Cube. We're live from Big Data SV. And we're clear. Thank you.