 Live from Boston, Massachusetts, extracting the signal from the noise. It's theCUBE, covering HP Big Data Conference 2015, brought to you by HP Software. Now your hosts, John Furrier and Dave Vellante. Hi, welcome back to Boston everybody. This is Dave Vellante and this is theCUBE. We go out to the events. We extract the signal from the noise. We're here at the HP Big Data Conference 2015. Andrea Fabrizia is here. He's with the analytics team. Within the CMS business, the communications media solutions business at HP. We've had Sargalay on many, many times. Andrea, welcome to theCUBE. It's great to have you. Thank you for coming by me. So talk about your role inside of the HP CMS business. Yeah, inside CMS business, I'm responsible for creating and managing all the big data and analytics portfolio for telecommunication market. So my responsibility is to using the HP product like idle, vertical autonomy and creating solutions specific for the communication market. And obviously managing the go-to market and the support activity. So this is really important. I mean, we've observed in Wikibon that our research shows that most analytic initiatives are very highly customized. Correct. Very complicated and expensive and time consuming. And there's a demand and I think a trend to take analytics capabilities and package them inside of apps, you know, packaged apps, specifically by industry, have templates and it sounds like that's what you guys are doing within the CMS organization. Is that correct? And can you talk a little bit more about the strategy? Yeah, absolutely. It's exactly what we do. I mean, telecommunication market has adopted big data also because they have a huge quantity of data quite recently and the first activity they do was roughly to load this data on the big data lake. But now for them, the big challenge is to understand how to use this data in efficient way, how to create the application they needed. And this is where we play. So we play the role in identify what are the typical problem that analytics can solve for telecommunication industry. Let me do an example. We are very active on defining and helping to do real-time personalized marketing. So managing the possibility to interact with the subscriber in a real-time basing it maybe with where the subscriber are. So if they are in a specific place, they continue to do specific offer. And this offer, I have to be personalized. So telecommunication market, it's looking for a new marketing that is not only mass market, but it's also a marketing basing on what your real preference, what you really want rather than what product I have to sell. And this is one of the top topics for telecommunication, improving the relationship with subscriber through the analytics. Another top topics for them is using analytics to be in big data, to be more efficient in their network management. Their network is very complicated. And moreover, now they have provided service by themselves. The network is used by OTT to provide additional service. And all the people consider the telcos as responsible for the service. If you have problem with Facebook, you don't call Facebook called center, you call your telco environment. So the telco have to expand the capability to diagnostic on the network, also including such kind of services. And this is an important area for them of analysis. Well it's interesting, because on the one hand, there's big threat, Facebook's and the WhatsApp's and the Skype's, over the top providers, the big threat to the telco industry, but the second hand, they have visibility on everything. So they have a huge opportunity. So your strategy is to try to give them better visibility so that they can take action on that. I want to come back to you, you mentioned real time. Yeah. Everybody talks about real time. How do you look at real time? What is the definition of real time? Is it before you lose the customer? Is it really in real time? Well, that's a good question because generally on the real time, there is a lot of these old people's intent about times different way. When we talk at real time, we're talking about having analytic capability below one second. So real time means really the possibility to identify below one second a problem and rise the right alarm too, and managing also the resolution in a short time. So in the telco space, so I mean, in other market, real time means probably three minutes, five minutes. You can read a lot of memory database that say we are real time or whatever. They are fast, but when you're talking about real time in the telco, real time in the network means below one second. And this is the target they are looking for, especially on managing the network because I mean, if you have a problem on your device, you don't want to wait three minutes for a resolution or that the customer can be informed in three minutes. You want to know immediately. You want to be connected immediately. That's the aspect. Last time I had SAR on Sargillai was at HP Discover in June, I guess it was June who gave me a little lesson on NFV. You are involved in analytics as it relates to NFV. So what's the relationship between analytics and NFV and how is it affecting positive change in the telco industry? Now that's a very good question because analytics is now a very important topic for telecommunication operator. They see in NFV, they see a great opportunity to move in a more cost effective platform and that sometimes have the level of flexibility to manage a new service in a very fast way. But analytics play an important role in NFV because the environment NFV will be much more complex than actual environment. So you can imagine that now you have all the function in a box, in a group of box. Tomorrow with NFV you have these functions spread out several computers, several virtual machine. That would be a benefit for them because they can scale in, scale out more efficiently. They can use standard machine. But at the same time, the complexity of managing all this infrastructure which might more complicated. And here, analytics can play a fundamental role to help telco to manage the complexity of NFV environment in real time way. So analytics can introduce the intelligence in the NFV environment to understand when they need to adding a virtual machine because this function is starting to be overloaded or when they think, okay, we're observing a strange trend on this service. This may be we can adding resources or we can start. So the analytics can be the intelligence of the NFV. That's the message we're taking. And the business outcome there is automation, lower cost. And then the other sort of note I would take or make is that it seems like NFV, the state of NFV today is very much sort of the hardware layer focused, dealing with that sort of hardware virtualization if you will. There's a real opportunity for software management. Do analytics play there as well? Exactly. Yeah, that's exactly the point. I mean, there are several steps. I mean, analytics sure can support on the hardware level to the hardware, let me say the virtual level to help to improve the capability of managing real time. So imagine that NFV is a big cloud and you need the capability to manage this cloud more efficient way. But also on the software and especially on the software-defined network, analytics play an important role because all these managing the great stuff is that now all the network can be virtualized not only in terms of hardware, but in terms of function. So you can decide that a packet can be routed through different system rather than other. And again, here there is an intelligence to define the best route for the traffic that analytics can provide. So does the Aruba acquisition change anything? Is it open up new opportunities for you? I mean, from a communication point of view, we are evaluating very deeply the acquisition with Aruba, especially in the direction we are serving on the market to use Wi-Fi location capability. I mean, Wi-Fi is playing a very important role in nowadays for anyone. I mean, anyone is always Wi-Fi connected or almost always. And using this information to support and making your service better for the scrub is great. So I mean, Wi-Fi allow you to have a more precise information about your location. So GPS give you a precision of, let me say, 50 meters or something like that. Radio networks do the same depending. Wi-Fi can really give you a precision between one meter to 10 meters depending on the technology used. And this can be really change the game. So imagine how many service you can provide using location information with so precision. And that's open a new, for example, marketing has a new perspective for this. And we are working with Aruba about that direction to use Wi-Fi technology for location capability. And that'll rip it through to your customers who can offer more services, more precise targeting. What's the, you mentioned Idle, Vertica, you know, Idle Autonomy, Vertica, we talked about Aruba. What's the, what are the piece parts that you're pulling together from HP to build the solutions? Obviously the main part we put together are Vertica as an analytic database that is extremely powerful in conjunction with Agilpa, because obviously Agilpa is an important piece of the solution. And we're using Idle to manage all the correlation and analysis on unstructured information. So that's are the three main component. Aruba plays an important role for providing the capability to adding additional information. It's more like me say Idle and Vertica are the engines. Aruba as other component in the network are the data sources. So that's the play role of these solutions. Andrea, you're from overseas, you're from Italy, telco diversity. I want to ask you about sort of differences between what's happening in sort of the U.S. world versus what's happening across the world. So Europe, APAC, maybe even within Japan itself, which has its own little ecosystem. How stark are the differences in telcos? And then specifically as it relates to data. I, my responsibility is worldwide. So I follow this market for the world HP on all the continent. And yes, I observing several different difference on the market, especially between Asia, Europe and America. Japan is more, I think is more, this now it's similar in some behavior to U.S. Let me explaining Asia now is, they have a big growing terms of numbers to describe there in the last part. So recently they focus was just adding network capability to support growing customer base. Now, most part of Asia is reaching the saturation level. I mean, the penetration level for the scrub is very high. Not at the level of U.S., but I mean, we're talking about 70%, 80%. So now they are moving to customer experience management solution. So they are looking to how to increase the quality of the network to managing the loyalty of the customer. And from another point of view, we are selling a lot of customer experience management solution. So solution, analytic solution, big data, collecting big data to manage better the network, to manage better the subscriber. The similar experience is in Europe. From one side there is a trend to improve the, let me say the experience of the customer. But Europe seems more interesting in managing loyalty. So trend management solution, understanding why the customer leave the company and how to block this aspect. So they improve the service part of this story, but more on this aspect. Japan and America are more focusing on marketing. So it's very, in America, all the telco are looking in the marketing capabilities of big data to support much more marketing and the standing better the subscriber. Also the legislation help in that direction because the privacy legislation is different. But generally speaking, American company are willing to invest much more on new technology and using this new technology to improve marketing capability. And how about other parts of the world? How about China? Let's talk about China a little bit. Maybe South America, Africa. Yes, South America. It's similar from this point of view to Asia. So they are looking to big data mostly for improving customer quality services. China is a very interesting market. In China we are serving all the effort together. So from one side they are still growing in terms of subscribers. So they are spending a lot of money in network, in enhancement, whatever. But we're serving a lot of projects both in customer quality, but also in the marketing. So we're serving a lot of activity around using big data for marketing purpose to improve the marketing selling new stuff to the customer. And how about Africa? I mean, it's still early days, but then you had all kinds of political unrest, but it seems like just from the standpoint of population and size of the geography is just should, in theory should be huge opportunities for telcos. But it's unstable in certain parts and uncertain. Africa is very, I think is from telco point of view is really a new frontier because it's an area where all the telco in Africa is growing a lot. In this moment they are growing mostly in from network point of view. So they expand the network to cover the subscription growing. So Africa is like Asia probably five years, 10 years ago. So an area where the penetration is really low and the main effort and the main direction of any telco is expanding the coverage, expanding so to get the new subscriber. So from the analytic point of view, let me say Africa is still a frontier that probably will be explored in probably five years from now. Go back to China. So you HP recently divested and developed a sort of partnership with operation in China. You sort of restructured that whole situation where the partner has a majority ownership you still maintain I think ownership. How does that affect your business at all? Well, we, it was mostly re-entered on the network side but this hasn't a big impact on our business. So we continue to have a very good growing in China, very good business on all the aspects. I mean analytic, NFE, they are very active also on NFE. They're doing several POC. So all the telco are experimenting NFE technology. So in the United States we're always using baseball analogies but we use a soccer if I can use that term, football analogy, right? So we say, oh, what ending are we in? When you think about analytics in telco, what part of the game are we in? Are we in the first half? Are we in the second half? Are we in extra time? Where are we? That's a good question. I mean, I think that we have in, I want to say in the middle because I think that the first alpha using the soccer example, they're not a big an expert on baseball. I mean, the first quarter in the baseball has gone. I mean, the first quarter was dedicated to collect and store the data. So that's what the telco does. So there was an anxious to say, okay, we have so many data. We have so many sources why we don't collect this data or whatever. Internet, any services. Now the second alpha is more important because now the real challenge for them is to leverage this data. So they have an amazing quantity of data. So you can imagine we have projects with several petabyte of data that is really a huge quantity of data. Now for them is the real jump. The second alpha next part of the game is to really leverage this data because they do some experience. They try to monetize like Google, but they are not Google. They try to understand really how to use this data because they try to, most of them try to explore Google approach model to monetize the data, but that's not their business. And now they are looking to the big data and especially analytics to improve, to automate their process. And I think this is the right direction. So really the data they have has a level of granularity that they will allow to improve their process. And I'm not only referring to network or IT projects, but I'm referring marketing projects too. So they can really be very effective and using this information also to create a new business model with their partner using the data. Excellent, we'll have to leave it there Andrea. Thanks very much for coming on. The CMS business unit really going after new opportunities within the telco industry. Really appreciate your insights. Okay, thank you. Thank you for inviting me. You're welcome. All right, keep right there, buddy. We'll be back after this short break. This is theCUBE, we're live on HP Big Data 2015 in Boston. Right back. Thank you.