 Welcome to Newsdesk on SiliconANGLE TV for Wednesday, October 17th, 2012. I'm Kristen Folletti. LinkedIn gets a facelift, Facebook is giving a few brands a sneak peek at a new marketing tool, and theCUBE's big data week is upon us. Joining us now with his breaking analysis is Wikibon analyst Jeff Kelly. Welcome Jeff. Hi, Kristen. Thanks for having me again. Since January 2009, LinkedIn's members have grown from 32 million to over 175 million. We've talked previously on the program about LinkedIn's growth. What do you attribute to LinkedIn's success? Well, you know, certainly it's a highly useful service really for, among other things, networking with colleagues, but also it's used, you know, used heavily for networking in terms of finding a new job. So, you know, we all know in this day and age, you know, a lot of jobs you get because of people you know, connections you might have, people you've worked with in the past, that kind of thing. And LinkedIn is the go-to destination to maintain relationships with all those people. You know, prior to LinkedIn it was kind of difficult to continue keeping in touch with colleagues. LinkedIn has kind of solved that problem, at least to the extent that you can, you know, be connected to them. You may not, you know, converse with them often or even chat often, but nevertheless you can maintain that kind of loose connection and call upon one another, you know, when you're in that job seeking mode. John Bronson, LinkedIn's product manager, has announced an overhaul of LinkedIn's profiles. What can he tell us about the changes we can expect on this core feature? Right. So, there appears to be, you know, some changes around the visualizations, just how the profile is going to look, makes it, I've heard it described as a little bit more Facebook-like, so maybe just a little bit more user-friendly. What intrigued me among the updates, however, was more of the, this idea that you're now going to be able to kind of overlay or cross-reference some of your data with those of your colleagues or connections in your network. So, for instance, you could identify which colleagues or which people in your network worked for a certain company at a certain time, may have worked together, may have worked on similar projects, depending on what they've included in their LinkedIn profile. So, it just helps you kind of get a better view of the relationships among your connections. And again, when it comes to finding either, you know, employment opportunities or simply just kind of making new connections for other types of business opportunities, all that kind of data really can really be helpful. What's the motivation behind the remodel? Who's LinkedIn attempting to compete with? I heard you mentioned Facebook. Are they attempting to directly compete with them? I don't think it's directly competing with them. I think what LinkedIn is is kind of Facebook for the enterprise, I think is what they're trying to be, I think, or Facebook for grown-ups, if you will. And I say that sort of tongue-in-cheek, but, you know, a little bit more, a little bit higher level kind of conversation you'll see on Facebook, not quite as much of the cheeky content that you might get on Facebook. So, but who are they trying to attract? I mean, they want to attract anyone and everyone who's, you know, in business and industry, in across the world really, in the US and elsewhere. So I think, you know, the other thing they're trying to do here, specifically around being able to kind of proprise reference your experience data, your products you've worked on, things like that, that I mentioned a moment ago, you know, LinkedIn at its heart is a big data company. They've got lots of data assets, and they're continually trying to find new ways to make use of that data to make their service more useful to their users, which ultimately makes it a more attractive destination for advertisers and other clients of LinkedIn. How do you think users are going to react to the new face of LinkedIn? You know, I think users for the most part are going to react favorably. You know, I think, you know, all of us kind of, most of us are on Facebook. So I think we see some of these new type of visualizations in the look and feel to kind of mirror that Facebook experience. I think most people will be comfortable with that. And I really think people are going to find the, again, the cross-referencing of the data very helpful. Again, you can think of perhaps you might be looking for a job. Maybe you've got an interview with someone you don't know at a new company. You know, if you can reference, if you can do a search and kind of understand who in your network you've worked with that person before, or maybe worked at that company around the same time that person you're interviewing with may have worked there. You know, you can essentially create connections, get some interactions going that way just to improve your chances. So I think people are going to really enjoy that type of capability now built into LinkedIn. Let's move to Facebook and this new marketing tool they're keeping under wraps. As it stands right now, what kind of information can brands access about Facebook users who like them? Well, that's a good question. So, you know, right now advertisers and clients of Facebook can understand who likes them, of course, and they can understand how that's trending over time, either increasing or dropping. They can understand who's talking about them. Kind of they can do potentially on their own if they want to do some kind of sentiment analysis about what's being said, said about them and Facebook profiles and things like that. So, you know, what's new here is that now Facebook is reportedly allowing a select group of their clients access to not just, hey, here's the people on Facebook that like you, but here's the other things that those people also like, the idea being that, you know, these clients can use that information to their advantage in terms of advertising and reaching, you know, more potential customers. Facebook has been internally allowing a select number of marketers to see their fans other interests like their favorite bands or TV shows. So how could this brand affinity tool help marketers? Well, you know, let's just take a simple example. And I'm not privy to, you know, which of the advertisers Facebook is making this data available to. But just, you know, for the sake of argument, let's say, you know, it's Macy's might be one of one of what's just say, hypothetically, you know, if Macy's knows that, you know, we've got such and such million people that like us and we know that a good proportion of those people also like, you know, pick your favorite television show. OK, well, there's an opportunity we should use to potentially advertise on that show, maybe do some kind of cross promotion with that show to extend our reach to to other people who watch that show, who would probably be interested in our Macy's services and products. So it's that ability to really understand what other what people that like your company also are interested in and trying to reach like minded people to essentially increase your customer base. Why haven't marketers been able to access this type of data in the past? Well, I mean, there are issues around privacy and there are, you know, issues. I mean, certainly, Facebook has got a lot on their plate. You know, they're growing. I think they just hit over a billion members. So there's there's a lot going on in terms of just supporting the that many users in terms of keeping their infrastructure up and running. You know, they this is, I think, a reaction, not a reaction, but a part of the story around Facebook finding new ways to monetize all that data they collect, you know, with the IPO failing miserably and a lot of bad press around Wall Street analysts say, we're not sure how they're going to monetize this data. Well, here's an example of how Facebook thinks they can do that. I think this is a good a good way to go in the sense that, you know, this is certainly information that marketers and advertisers love to have. And ultimately, you know, I'm bullish in the long run, long term on Facebook being able to monetize this data because there's just they have, you know, more data probably than anyone other than maybe Google. And, you know, we've learned in this big data era that it's not necessarily the smarter, smarter, the algorithms that wins. It's it's the it's the amount of data. The more data you have, you know, you can even have less sophisticated algorithms to do some really interesting types of analytics that can drive advertising marketing among other use cases. This seems like an obvious choice and a very valuable tool for marketers. So why is Facebook holding back on releasing such a money making feature? Well, I mean, anytime you release a new feature, there's the potential for, you know, hiccups, there's potential for a backlash from users not wanting their data to be used this way. So, you know, I think it's wise to roll it out slowly. And also, you know, you don't want to I'm sure there's really smart people inside of Facebook who have lots of ideas of different ways they can use this data to monetize this data, you know, and you don't want to roll them all out at once. You want to kind of do it in stages as it allows you really to focus on the ones specific initiatives one at a time, give it the attention they're due and then kind of keeping your clients wanting more and being able to deliver. So, you know, I would expect to see, continue to see updates like this over time, but, you know, I wouldn't expect them to all roll out in one kind of giant title. Big Data Week is coming up with Stratoconference and Hadoop World kicking off in NYC October 23rd through the 25th. What are you anticipating for next week? Well, it's going to be a very exciting week next week. We here at Wikibon and SiliconANGLE are going to be bringing the queue to two events next week. As a matter of fact, IBM's information on demand event where they're going to focus heavily on big data, both kind of the analytics side and the infrastructure side as it relates to IBM customers. And then later in the week, Wednesday and Thursday next week, we'll be at the Stratoconference plus Hadoop World. There are two conferences and one now and so that's in New York City at the end of the week towards the end of the week. You know, that's going to be really interesting because there's just, you know, the entire big data ecosystem really is going to be represented there. Lots of different vendors from startups that, you know, like companies like Platfora to larger vendors. ASAP is going to have a heavy presence. So it's really going to be an interesting mix of customers. It's a really good opportunity to understand what are some of the really cutting-edge trends happening in big data. Also to talk to some big data practitioners. So between the two events, we're going to really, you know, how it's going to be a big week, no pun intended around big data here. So yeah, definitely tune in. We're going to have live coverage Monday, Tuesday at IBM Information on Demand from Las Vegas and then Wednesday, Thursday, live from New York City at the Stratoconference. Well, Jeff, thanks so much for your time. Great talking with you, as always. Likewise. Thanks for having me on. For information on news of the day and the latest breaking analysis, stay tuned to News Desk right here on SiliconANGLE.TV.