 Live from Munich, Germany. It's theCUBE coverage. DataWorks Summit Europe 2017. Brought to you by Hortonworks. Hey, welcome back everyone. We're here live in Munich, Germany for DataWorks 2017 Summit. Formerly known as Hadoop Summit, now called DataWorks. I'm John Furrier with theCUBE, my co is Dave Vellante here for two days at a wall-to-wall coverage. Our next guest is Daveeem, who's our head of advanced analytics at Denska Bank. Welcome to theCUBE. Thank you. Just to remember, but also talking here at the event and bringing all your folks here, your observation. I mean, Hadoop is not going away. Certainly we see that. But now, as John Christ, who was emceeing, was on earlier, said, opening up the aperture to analytics is really where the action is. Your reaction to that. I completely agree. Because again, Hadoop is basically just the basic infrastructure, right? Components, built-on components, and things like that. But when you really utilize it, is when you add the advanced analytics frameworks. There are many out there. I'm not going to favor one over another. But the main thing is you need that to really leverage Hadoop. And at the same time, I think it's very important to realize how much power there actually is in this. For us in Danskabang, getting Hadoop, getting the advanced analytics framework has really proven quite a lot. And allowed us actually to dig into our core data, transaction data, for instance, which we haven't been able to for decades. So take me through, because you guys are an interesting use case, because you're advanced, you got a lot of, you're getting at the data, which is cutting edge. But you're going through this transformation, and you have to because you're on the front lines. Take us inside the company, without giving any way to trade secrets, and describe the environment. What's the current situation, and how is it evolving from an IT standpoint, and also from the relationship with the stakeholders in the business side? Yeah. So again, we are a bank with 20,000 employees. So of course, in a large organization, you have silos, and people feeling, okay, this is my domain, this is my kingdom. Don't touch it. Don't approach me. Oh, you can approach me, talk to me, you have to convince me, otherwise don't talk to me at all. So we get that quite a lot. And to be honest, from my point of view, if we do not lift as a bank, we're not going to succeed. If I have success, if my organization of almost 60 people have success, that's good in itself, but we're not going to succeed as a bank. So for me, it's quite important that I go down and break down these barriers, and allow us to come in, tell the business units, tell them what sort of capabilities do we bring, and include them. That is actually the main key. I don't want to replace them or anything like that. So organizational challenge is to get the mindset shifted. How about process gaps and product gaps? Because you almost see the sequence, kind of a group hug, if you will, organizational mindset, kind of a reset or calibration, and then identify processes and then product gaps seem to be the next transition. Absolutely, absolutely, and there are some gaps. Still, even though we've been on this journey for a considerable amount of time, there are still gaps, both in terms of processes and products, because again, even though we have top management buy-in, it doesn't go through all the way down to the middle layer. So we still struggle with this from time to time. How do you break down those barriers? What do you do? What's your strategy? I'm humble, to be honest. I go in, I tell them, listen you guys, I have some capabilities that I can add to your capabilities. I want you to leverage me to make your life easier. I want to lift you as an organization. I don't care about myself. I want you to be better at what you're doing. So Nadine, the money business and the technology business have always had a close relationship, but it was like in 2010, after we came out of the downturn, it was like this other massive collision. You had begun experimenting with cloud to shift CapEx to OpEx. The data thing hit in a big way. Obviously mobile became real. So talk about the confluence of those technologies, specifically in the context of your big data journey. Where did you get started and how did it evolve? So actually it fit in quite nicely because we were coming out of this down period, right? So there was extreme amount of focus on cost. So of course at the time where we wanted to go into this journey, a lot of people were asking, okay, how much does it cost? What's the big strategy and so on? And how's the roadmap going to look like and what's the cost of the roadmap? The thing is, if you buy some off the shelf commercial product, it's quite expensive. We can easily talk like half a billion or something like that for a full end to end system. So with this, you were allowed or we were allowed to start up with relatively small funding and I'm actually talking about just like a million dollars roughly and that actually allowed us a substantial boost in the capability department in allowing us to show what kind of use cases we could build and what kind of value we could bring to Thanksgiving. So did you started with understanding Hadoop? Is that right? Was that the starting point? In a fairly small research team set up. So we did the initial research. We looked at, okay, what could this bring? We did some initial, what we call proof of value. So small, small pilot projects looking at, okay, this is the data. We can leverage it in this way. This is the value we can bring. How much can we actually boost the business? So everything is directly linked to business value. For instance, one of the use cases was within customers, understanding customer behavior, directly linking it to marketing, do more targeted marketing and at the end get more results in terms of increased sales. And this is, we just started the journey 2009, 2010. Is that right? Or was it later? No, we started this somewhat later. Okay, yeah. The initial research was in 14. In 14, okay. All right, so 14 you sort of became familiar with. And then I imagine like many customers who said, okay, wow, this stuff is complicated, but we're taking it in small chunks, low risk. Let's get some value. Marketing is an obvious use case. I would imagine fraud is another obvious use case. So then how did that evolve? I mean, it's only a few years now, but you've imagined you've evolved very quickly. Extremely quickly. Actually, within two months of the research, we actually saw a huge benefit in this area. And directly we went with the material to the senior members of the different boards we wanted to affect. And actually it was, you could call it luck, but maybe we were just well prepared and convincing. So we actually directly got funding at that point in time. They said, listen, this is very promising. Here you go. Start off with the initial slightly larger projects, prove some value, and then come back to us. Initially they wanted us to do two things. Look into the customer journey or doing deeper customer behavior analytics. And the second was within risk, doing things like text mining, financial statements, getting some deeper into that, doing some web crawling on the financial data, such as Bloomberg, et cetera. And then pull it into the system. To inform your investments. Yes. Okay, as a financial institution. Absolutely. And from an architecture and infrastructure standpoint, we talked about starting at Hadoop. Has it evolved? How has it evolved? Where do you see it going? It has evolved quite a lot in the past couple of years. And again, to be honest, it's like every quarter something new is happening and we need to do some adjustments even to the core architecture. And with the introduction of HDB3 and later this year, I think we're going to see a massive change once again. Hortonworks already calls it a major change or a major release. But actually the things they are doing is extremely promising. So we want to take that step with them. But again, it's going to affect us. What's exciting about that to you? The thing that's very exciting is we are now at like a balance point where we are, we have played quite a lot. We have released a couple of production great solutions but we have really not reached the full enterprise potential. So getting like into the real deep stuff with living under heavy SLAs, regulation stuff, all these kind of things is not in place yet from my point of view. You know, we talk a lot about in theCUBE and in our company about these emergent workloads. You had batch, interactive, and then we go to World Wet Back to Batch with Hadoop. And now you have this continuous workload, streaming, real-time workloads. How is that affecting your organization generally and specifically you're thinking about architecture? Is that, how real is that and where do you see that in the future? It's the core, to be honest. Again, one of the main things we are trying to do is look into, so gone are the days with heavy, heavy batches of data coming in because if you look at weblogs for instance, so when customers interact with our web or our tablet solution or mobile solution, right, the amount of data generated is humongous. So no way on earth you can think about batches anymore. So it's more about streaming the data all the way in, doing real-time analytics and then produce results. What would you say are your biggest big data challenges, problems that you really want to attack and solve? So what we really want to attack is getting all sorts of data into the system, right? So you can imagine, as a bank we have 2,000 plus systems. We have approximately 4,000 different points that delivers data. So getting all that mass into our data lake, it's a huge task. We actually underestimated it. But now we have seen we have to attack it and get it in because that is the gold. Data is the future gold. So we need to mine it in. We need to do analytics on top of it and produce value. And then once you get it in there, you're, I'm sure you're anticipating that you want to make sure it doesn't go stale, doesn't become a swamp, doesn't get frozen. John likes to talk about data oceans. Which is really the long-term vision I presume, right? So yeah, and that is a key as well because with the GDPR for instance, we need to have full mapping and full control of all the data coming in. We need to be able to generate metadata. We need to have full data lineage. We need to know what all the data where it came from, how it's interconnected, relations, all that. And that's what, two years away from implementation? Is that about right? It's going to take a while, of course. But again, the key thing is we make the framework so all the data coming in step by step has that. Yeah, but so GDPR though, it goes into effect, 19, is that correct? It's actually May 18. May 18, oh, so it's much tighter time frame than I thought. Yeah, you're under the gun. Okay, observation here at this event, I'll see a lot of IoT for you, that's people, right? People and things are kind of the edge of the network. The intelligent edge is a big, big topic, very dynamic, a lot of things happening, a lot of opportunities for you to be this humble service provider to your constituents, but also your customers. How do you guys view that? What's the current landscape look like as you look outside the company and look at what's happening around you, the world? A lot of cool things are going on, to be honest. And especially in IoT, right? I mean, even though we are a core bank still, there are a lot of sensors we can use. I talked a bit about, under the keynote, about ATMs, right? So we're also looking at how can we utilize this technology? How can we enable our customers? And if you look at our apps, they also generate extreme amounts of data, right? The mobile solution that we have, it gives away GPS location and things like that. And we want to include all that data in. And at the end of the day, it's not for our gain, we are not always looking at making the next buck, right? It's also about being there for the customer, providing the services they need, making their banking life easier. And your ecosystem is evolving and rapidly adding new constituents to your network because you think about the consumer with the phone, the mobile app alone, nevermind the point of sale opportunities at the ATM, now a digital augmented reality experience could be enabled where you now have FinTech suppliers and potentially other suppliers in this now digital network. That can be relational with you. Yes. And our job is to make sure that we leverage that, right? Acquiring a banking license is extremely difficult, but we have it. And what we need to do is to engage these FinTechs, partners, even other banks and say, listen guys, we invite you in, utilize our services, utilize our framework, right? Utilize our foundation and let's build something upon that. If you had to explain to Dean this FinTech startup trend, okay, because it is super hot, what is it? I mean, how would you describe someone who's not in the banking world? Because most people would scratch their heads and say, isn't that banking? But now this ecosystem is developing a new entrepreneurial activity and they're skyrocketing with success because they have either a specialty focus, they do something extremely well. It may or may not be in a direct big space for the bank, but a white space, use cases. So is it good? Is it bad? What's the current state of the FinTech situation? From my part of you, it's awesome. And the reason is, these guys are pushing us. Remember, we are a 150 plus year old bank, right? And sometimes we do tend to just pat on our back and say, okay, this is going good, right? But these guys are coming in, giving some competition and we love it. Give an example of a FinTech capability. So randomly bringing up some examples to highlight what FinTech is. So what we've seen in, for instance, the German market is the FinTech's coming in, utilizing some of the customer data and then producing awesome new applications, whether it is a new net bank where a customer can interact with it at a much, much more smoother way, right? Some of the banks tend to over clutter things, not make it simple. So things like where you can put in, you can look at your transactions in a Google map, for instance. You can see how much do you spend at this location. You can move around. I mean, you can say- You can literally follow the money. Yeah, you follow the money. Yeah, so this is your home base. You go out here, you spend this amount of money and maybe even add more on it. So let's say you do your grocery shopping over here, but if I moved all my business from this brand or a company to this company, how much could I save? Imagine if you could just drag and drop it and see, okay, I could actually save a couple of thousand bucks. Awesome. And machine learning is going to totally change the game with augmented intelligence. AI is called artificial intelligence or augmented intelligence, depending upon your definition. Exactly. This is a good thing for consumers. It is. It is. And thinking about disruption, we talked about this. What are your thoughts on blockchain? What is your research showing? You playing around with Hyperledger at all? Yes, we are. And blockchain, it's also quite interesting, right? We're doing lots of research on that. And what is shown actually is that this is a technology that we can also use, and we can actually also really utilize even the security aspects of it. If you just take that, you could really implement that, right? And the ability to... Yeah, identity aspect, it's federating identity around fraud. Exactly. There's another area you could innovate on. I mean, I'm bullish on blockchain. A lot of people are skeptical, but Dave knows I'm really, I love blockchain because it's not about Bitcoin per se. It's about the underlying opportunity. It just seems fascinating. Dave, you know, I got my soapbox on the blockchain. We've never really looked at Bitcoin as just a currency, as more of a technology platform. It is. I have always been fascinated with the security angle. No, I mean, virtually unhackable, put that in quotes. No need for a third party to intermediate. So many positive fundamentals. Now it's guys like you figuring out, okay, the practitioner's saying, here's how we're going to implement it and commercialize it. And actually it fits in quite well with the things like GDPR, right? Because this is also about opening up. The same was PSD2, exposing the customer data, making it available for the general public. And ultimately the goal is, so you as a consumer, me as a consumer, we own our data. Nadine, thank you so much for coming on theCUBE and sharing your practitioner situation and your advice as well as commentary. I'll give you the last word. As you and your team embark from DataWorks 2017 and head back to the ranch, so to speak, and then bring back some stuff, what are you going to work on? What's the to-do item? What are you going to sharpen the saw and cut when you get back? So for us on the very, very short term, it's about taking our platform and our capabilities and move it into the real enterprise world. That is our first key milestone that we are going to go for. And I tell you, we're going to go all in for that. Because unless we do that, we are not able to really attack the core of banking, which requires this, right? Please remember that a consumer doing a transaction somewhere in the world, he cannot stand and wait for ages for something to be processed, right? It needs to be instantaneous. So this is what we need to do. And you think this event, you're armed up with product? Absolutely, absolutely, lots of good insight we've gotten from this, lots of potential, lots of networking guys and other companies that we can talk to about this. Also great recruiting, get some developers out there, too. A lot of great people. Congratulations on your success and thanks for sharing this great insight here on theCUBE. We're exposing the data to you live on theCUBE. SiliconANGLE.tv, I'm John Furrier. Dave Vellante, my co-host. More great coverage. Stay with us here live in Munich, Germany for DataWorks 2017 Summit. We'll be right back.