 Live from San Jose in the heart of Silicon Valley, it's theCUBE, covering DataWorks Submit 2017, brought to you by Hortonworks. Hi everybody, this is George Gilbert. We're watching theCUBE. We're at DataWorks 2017. I'm with my good friend Shri Raghavan from Teradata. And Shri, let's kick this off. Tell us, bring us up to date with what Teradata's been doing in the era of big data and advanced analytics. First of all, George, it's always great to be back with you. I've done this before with you and it's a pleasure coming back and I always have fun doing this. So thanks for having me and Teradata on theCUBE. So a lot of things have been going on in Teradata. As you know, we are the pioneer in the enterprise data warehouse space. We've been so for the past 25 plus years and we've got an incredible amount of goodwill in the marketplace with a lot of marquee customers and all that. And as you also know, in the last five or seven years or so, between five and seven years, we've actually expanded our portfolio significantly to go well beyond the enterprise data warehouse and to advanced analytics. We've got solutions for the code and code, the big data advanced analytics space. We've acquired organizations which have significant amount of core competence with enormous numbers of years of experience of people who can deliver solutions and services. So it's fair to say as an understatement that we have come a long way in terms of being a very formidable competitor in the marketplace with the kinds of, not only are core enterprise data warehouse solutions but also advanced analytics solutions both as products and solutions and services that we've developed over time. So I was at the influence summit not this year but the year before and what struck me was you guys articulated very consistently and clearly the solutions that people build with the technology as opposed to just the technology. Let's pick one like customer journey that I remember that was used last year. And tell us sort of what are the components in it and sort of what are the outcomes you get using it? Sure. First of all, thanks for picking on the point because it's a very important point that you mentioned, right? It's not, in today's world, it can't just be about the technology. We just can't go on and articulate things around our technology and the core competence but we also have to make a very legitimate case for delivering solutions to the business. So our, in fact, our motto is business solutions that are technology enabled. We have a strong technology underpinning to be able to deliver solutions like customer journey. Let me give you a view into what customer journey is all about, right? So the idea of the customer journey, it's actually pretty straightforward. It's about being able to determine the kind of experience a customer is having as she or he engages with you across the various channels that they do business with you at. So it could be directly they coming to the store, it could be online, it could be through snail mail, email, what have you. The point is not to look at customer journey as a set of disparate channels through which they interact with you but to look at it holistically across the various areas of encounters that they have with you and engagements they have with you, how do you determine what their overall experience is and more importantly, once you determine what their overall experience is, how can you have certain kinds of treatments that are very specific to the different parts of the experience and make their experience and engagement even better? Okay, so let me jump in for a second there. We've seen a lot of marketing automation companies come by and say, you know, or come and go having said over many generations, we can help you track that. And they all seem to like target either ads or email or there's like the touch points are constrained. How do you capture a broader, you know, a broader journey? Yeah, to me it's not just that touch points being constrained although all the touch points are constrained. To me it's almost as if those touch points are looked at very independently and it's very orthogonal to it, right? I look at only my online experience versus a store experience versus something else, right? And the assumption in most cases is that they're all not related. You know, sometimes I may not come directly to the store, right? But the reason why I'm not coming to the store is because to buy things because, you know, I have seen an advertisement somewhere which says, look, go online and purchase a product so whatever the case might be. Point is, each part of the journey is very interrelated and you need to understand this as well. Now, the question that you asked is, how do you, for instance, collect all this information? Where do you store it? And how do you relate it? Exactly, and how do you connect the various point of interaction, right? So for one thing, let me just sort of go a little bit tangential and go into some of the architecture, the architecture, if you will, that allows us to be able to, first of all, access all of this data. As you can imagine, the types and the sources of data are quite a bit, pretty disparate, particularly as a number of channels by which you can engage with me as an organization has expanded, so do the number of sources. So, you know, we have to go to place A where there's a lot of CRM information, for instance, or place B where there's a lot of online information, web logs and web servers and what have you, right? So, we have to go to, for instance, some of these guys would have put all this information in the big data lake, or they could have stored it in an EDW and in Enterprise Data Warehouse. So, we've put in place a technology in architecture which allows us to be able to connect to all these various sources, be it Teradata products or non-Teradata, third-party sources, we don't care. We have the capability to connect all these different data sources to be able to access information. That's number one. Number two is how do you normalize all of this information? So, as you can well imagine, right? Web log servers are very different in their data makeup as opposed to CRM solutions, highly structured information. So, we need a way to be able to bring them together to connect a singular user ID across the different sources. So, we have filtering data filters in place that extracts information from web logs. Let's say it's a XML file. So, we extract all that information and we connect it. We ultimately, all of that information comes to you in a structured manner. And can it be real-time reactive? In other words, when someone comes to a channel where you need to anticipate and influence? Very good question. In fact, I think we will be doing a big disservice to our customers if we did not have real-time decisioning in place. I mean, the whole idea is for us to be able to provide certain treatments based on what we anticipate your reactions are going to be to certain, let's say, if it's a retail store, let's say to certain product coupons we place, which says, you know, come online and based on your behavior, we think there's a 90% chance that tomorrow morning you're going to come back, you know, through our online portal and buy the products. And because of the fact that our analytics allows us to be able to predict your behavior, tomorrow morning, as soon as you land up on the online portal, we will be able to provide certain treatment to you that takes advantage of that. Absolutely. Techy question. Because you're anticipating, does that mean you've done the prediction month batch? Absolutely. Yeah, yeah. And so you're just serving up the answer? Yeah, the business level answer is absolutely. In fact, we have, as part of our advanced analytics solution, we have pre-built algorithms that take all this information that I talked about, we're connected all the information across the different sources, and we apply algorithms on top of that to be able to deliver predictive models. Now, these models, once they're actually applied as and when the data comes in, you know, you can operationalize them. So the thing to be very clear here, a key part of the Teradata story, is that not only are we in a position to be able to provide the infrastructure which allows you to be able to collect all the information, but we provide the analytic capabilities to be able to connect all of the data across the various sources and at scale to do the analytics on top of all that disparate data to deliver the model and as an important point to operationalize the model and then to connect it back in the feedback loop. We do the whole thing. That's, there's a lot to unpack in there. And I called our last guest dense, but I was actually trying to say we had to unpack a dense answer. So it didn't come out quite that, quite right. So I won't make that mistake. That's a very backhanded compliment there. So, explain to me though, I know from all the folks who are trying to embed predictive analytics in their solutions, that the operationalizing of the model is very difficult, to integrate it with the system of record. How do you guys do that? So good point. There are two ways about which we do it. One is we have something called the App Center. It's called the Teradata App Center. The App Center is a core capability of some of the work we've done so far. In fact, we've had it for the last, I don't know, four years or so. We've actually expanded it across to include a lot of the apps. So the idea being the App Center is that it's a framework for us to be able to develop very specific apps for us to be able to deliver the model so that next time, as in when real time data comes and when you connect to a database for instance. So the way the app works is that you set up the app. There's a code that we've created. It's all prebuilt code that you put behind the app. And it runs, the app runs. Every time the data is refreshed, you can run the app and it automatically comes up with visualizations which allow you to be able to see what's happening with your customers in real time. So that's one way to operationalize. In fact, if you come by to our booth, we can show you a demo as to how the App Center works. The other way by which we've done it is to develop a software development kit where we actually have created an operationalization. So I'll give you an example, right? We developed an app, a real time operationalization app where the folks in the call center are assessing whether you should be given a loan to buy a certain kind of car, used car, brand new car, what have you, the case might be. So what happens is a call center person takes information from you, gets information about what your income level is, how long you've been working in your existing job, what have you. And those are parameters that are passed into the screen. By the way, I should just say on the income level, it's way too low for my taste. Those are comments I'll take later. Offline. But I mean, you got a brand new Armani suit, so you're not doing badly. But so what happens is as and when the data goes into the parameters, right? The call center person just clicks on the button and the model which sits behind the app picks up all the parameters, runs it and spews out a likelihood score, saying that this person is 88% likely. So an app center is not just a full intent app, it also can be a model. App center can include the model which can be used to operationalize as and when the data comes in. It's a very core part of our offering. In fact, app center is, I can't stress how important, I can't stress enough how important it is to our ability to operationalize our various analytic models. Okay, one more techie question in terms of how that's supported. Is the app center running on Aster or the models? Are they running on Aster, the old Aster database or Teradata? Well, just to be clear, right? So the Aster solution is called Aster Analytics of which one form factor contains a database. But you have Aster, which is on Hadoop. You have Aster on the cloud. You have Aster software only. So there's a lot of difference between two, right? So app center sits on Aster, but right now it's not just the Aster app center. It's called the Teradata app center, which sits on, the idea is that it will sit on Teradata products as well. So again, it's a really core part of our evolution that we've come up with. We're very proud of it. On that note, we have to wrap it up for today, but to be continued. Time flies when you're having fun? Yes. So this is George Gilbert. I am with Sri Raghavan from Teradata. We are at DataWorks 2017 in San Jose, and we will be back tomorrow with a whole lineup of exciting new guests. Tune in tomorrow morning. Thanks.