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#HadoopNext: Accelerate data science with Hadoop
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0:04live from the Fairmont Hotel 0:06in San Jose Calif kids cue 0:09at Big Data sp 2050 0:12up 0:18did 0:22it 0:29over welcome back this is the cuba flagship program we go out the events 0:32this reclusive North I'm John very we're here at IBM 0:35talk about Big Data big data analytics and they were doing a first-ever 0:39crouch that's i'm ok caster live feed with IBM so 0:44guys gonna try this out is a good crowd chat dotnet slash 0:48Hadoop next and join the conversation and 0:52our guests here Rob Thomas vice president product development big data 0:55analyst at IBM and beth smith general manager 0:57I V and analytics platform guys welcome to welcome to queue 1:01thank you come back and so I be a mostly we're super excited to 1:04next week is out interconnect your because I got smashed up 1:07three shows for the mega shows and and harassments places cuz them from 1:12bosnia's I'm really excited about 1:14you know harassment and all the activity the social lounge in and whatnot but 1:17we've been following you guys the transformation IBM 1:20is really impressive you guys something like he the press in terms of 1:24some other performance eyes in the business but it's pumping right now you 1:27guys seem 1:28great positioning the stories are or any other huge customer base 1:31you services so with Big Data world which is 1:34tends to be start-up driven from the past few years over the past phase one 1:39the big companies came and and started saying hey you know this big market our 1:42customer see 1:43demanded that so your take on as we coming in to interconnect 1:47next next week what is perspective 1:50a big deal as the Watson as garnered headlines from 1:53powering toys to jeopardy 1:57to solving huge world problems that's a big data probably guys are not new to be 2:01days so when you look at this big data week here 2:04in Silicon Valley was to take sure 2:07so I'll start off in that bath United so our big focus is how we start to bring 2:12data to the masses and we start to think in terms of personas 2:16data science plays into increasingly important role 2:20around Big Data how people are accessing that the developer community 2:24and then obviously the wider business community which is the 2:27the clients that I been serving for years but announces that we made this 2:31week around 2:32duper really focused on the first two personas in terms of 2:36they decide just how they start to get better value outta 2:39Hadoop leveraging different tools will talk about some of those are 2:43and to really start to change it about do puzzle to me about insight 2:46it's not about infrastructure infrastructures interesting but what 2:49about what you're getting out a bit 2:50that's where we're approaching it that way any child well it has natural 2:54Italian strategy 2:55around eight o'clock at an engagement and eight is really about 2:59using the insights which a light Rob said it's about the value can get from 3:03the data 3:03and how that can be used in the transform professions and industries 3:08and I think when we bring it back to big data on the topic overdub 3:12I think frankly it has gotten to a point that clients are really 3:17beginning to say it's time to scale their see in the value in the technology 3:21what he can bring how it gives them some diversity in their data analytics 3:25platform 3:26and they're ready to announce scale arm there were close as a partner 3:29so the theme is Hadoop next okay so that 3:32Texas right for the next point which ok what's next is a phase 1 3:36okay we get some base position validation okay this new 3:39environments customers are 1 so what so what is next to me we're hearing 3:43things like in memories ha the spark is proving it is action 3:46in memory that that kinda says OK analytics at the speed businesses on 3:50that support you guys 3:51are all over that and we've heard some things for you guys so so what's how do 3:55we get to the next part we take 3:57Hadoop as a as a infrastructure opportunity and put into practice 4:01for solutions at what what are the key things that you guys see happening 4:05that must happen for the large customers to be successful 4:08so I think that actually ties into the announcements we made this week 4:11Open Data Platform on because that's about getting that core platform 4:16to ensure that their standardization around it there's interoperability a 4:20rounded 4:21and investor base and that vendors and clients are coming together to do that 4:26into 4:27really enable and facilitate the community to be able to standardize 4:32around 4:32then it's about the value on top around it 4:36center it's about the workload and what could be brought to bear 4:40to extend up that how do you apply it to real time streaming 4:44how do you add things like machine 4:46how do you deal with things like text analytics 4:49me we have our we have a client situation where 4:53arm the client took for 4:56billion tweets and were able to analyze that 5:00to a den of our over a hundred and ten million 5:05profiles individuals and then by 5:08integrating and analyzing that data with the clock internal data sources about 5:14seven or eight different data sources 5:16they were able to narrow into 1.7 million profiles that matched at least 5:22ninety per cent per session you know now they've got data that they can apply 5:27on buying patterns it's about that it's about going up the stack 5:30weekend for our mines privacy 5:34cream personas relevant data but personalization 5:37mean collective intelligence has been a high-concept we try not to be creepy 5:41you hip me cool but now 5:45so that brings us to the next level you guys Tom a cognitive on were you guys 5:48also system systems wreckers alter mister 5:53your data warehousing resources yes 5:57data but now it seems engagement real time 6:00in the moment immersive experience which is actually the social and/or 6:04mobile experience what does that mean how you guys get there how do you make 6:08it so it's 6:08better for the users more secure or I mean these are hot-button issues that 6:12kinda leaders right to that point so 6:15particular Cowboys have servers or your first question on Hadoop next 6:19so the duke was no longer just an IT discussion that's what I've seen change 6:23dramatically in the last 6:24six months I was with the CEO for the world's largest banks 6:28just three years ago and the CEO's asking about 6:32Hadoop so there's a great interest in this topic Ind 6:36so so why so why would a CEO even care I think one is 6:40people are starting to understand the use cases play so 6:43that talks about entity extraction so how you start to look at 6:46customer records that you have arm internally 6:50in your system the record your point john and then you you know how do you 6:53match that against what's happening in the social world which is more 6:57or the engagement peace 6:58so there's a clear use case around that the changes how clients 7:02you know work whether with their customers so so that's one reason 7:06second is huge momentum in this idea of a logical data warehouse 7:10we no longer think love the data infrastructure as always a warehouse or 7:14to database 7:15tied to something not tied to just for relational store so 7:19you can have a warehouse but you can scale in Hadoop you can provision data 7:23back and forth you can write queries from either side 7:25arm that's what we're doing is we're enabling clients to modernize 7:30their infrastructure with this type of a lot logical data warehouse approach 7:33when you take those kinda use cases and then you put 7:37the data science tools on top of that suddenly 7:40our customers can develop a deferral a ship with their customers 7:43and the crew was there to change the way that that they're doing business I bet I 7:47wanna get your comments we have the crowd check out chat at Nestle 7:50to do next and commentary coming in as the transfer industries billion tweets 7:54killer for customer experience so customer experience 7:57and then also the link about the data science 8:00into high gear so let's bring that now is that the data science logical 8:05you know store looking make sense with virtualization things moving around 8:08absence of a cognitive 8:09engines out the overlay on top of that customer experience in data science our 8:13the interplay 8:14because this came out in some the retail then New York City they have it was a 8:18great point-of-purchase personalization customer experience he decides 8:22it's all rolling together was at me unpack that force in 8:26simplified became how one delegate complex and get a big topic 8:30you know it's a big topic so arm a couple different point so first of all 8:34I think it is a bad out enabling the data scientist to be able to do what 8:38they 8:39a their specialty years and the technologies have advanced to allow them 8:43to do that 8:44and then it's about them having the 8:47the date on the different forms the data and the analytics at their fingertips to 8:51be applied 8:51I think the the other pointed in it though is that the lines are blurring 8:56between 8:57the person that is the data scientist and 9:01the business user that needs to worry about how do they attract 9:07new customers or how do they you know create new business models and what do 9:12they use as a part of 9:13do think we're also seeing that one blurring 9:16one other things that we're trying to do is 9:19is help the industry around growing skills 9:22so we actually have the day University we have what 230 9:27thousand participants arm and his own line for E 9:31education and we're expanding that topic now to 9:35again go up the stack to go into the things that data scientists want to deal 9:38with light machine learning 9:40to go into things that the business user Willie wants to now be able to 9:45arm capture supported she got kinda more 9:48you can view product question and/or come under question had ID instead 9:52and I DM event indeed she said talked about big medical example 9:56and whenever a pay-per-use cases but she made a comment in there active data 10:00activity is not a new term for the data geeks out there but we look at data 10:04science lag is really important Realty 10:06near real time is not gonna make it for airplanes people cross the street mobile 10:10devices 10:10real real time means like best secondly she's really important speed so 10:15active days be part that's akin you guys talk about passive active data and how 10:19that relates to 10:20computing and 10:22because it's all kinda company is not an obvious thing but she highlighted that 10:25in their presentation because as you can with medical 10:28medical care lassie virgin on in the moment 10:31think so you was at army Muniz that some country paying attention to 10:36is it viable as a doable so certainly a viable 10:39I mean its huge opportunity in and 10:42I supply the most famous story we have around that is the work that we did at 10:46the University Toronto 10:47at the Hospital for Sick Children where we were using real-time stream mean 10:51algorithms and a real time streaming engine to monitor 10:55on influence in the neonatal care facility 10:59in this was a million data points coming off the 11:02human body monitor in real time in 11:05so why is that relevant to mean it's pretty pretty basic actually if you 11:09extract the data you eat a list somewhere you load in a warehouse then 11:13you start to say what's going on 11:15way too late you know we're talking about you know at the moment you need to 11:19know what's happening in so 11:20it started as a lot was in the medical field 11:23with you notice an example that you mention bird real time 11:27is not going well beyond the medical field you know places from 11:30retail at the point of sale on how things are happening 11:33to even things like forming on surreal time is here to stay 11:37we don't really view that is it different from what I would describe 11:40those who do blacks because stream into me as part of what we're doing with to 11:44do 11:44and let's work which will talk about in a bit so 11:47it certainly it is it's a new paradigm for many clients but its 11:51going to be much more common actually if I can and there's a 11:55client North Rana State University it's where I went to school so it's a 11:59if it it's a client that talk about a lot but they 12:03in addition to what they do with their students they also work with a lot of 12:06businesses 12:07own arm different opportunities me that they may have and they have a big data 12:11and analytics 12:12soared above arm extended education 12:15business education on project as a partner that they are now 12:20I am prepared to be able to analyze 12:24one had a bye in near real time 12:27so the examples that you and Rob talked about 12:30love the real-world workloads that are going to exist where 12:34real time matters arm are there there's no doubt about it they're not going away 12:39and the technology is prepared to be able to handle the massive amount 12:43data and analytics that needs to happen right there in real time 12:46that's a great thing great point mean the flagship examples are 12:50kinda like lighthouses for people to look at it go ship the guy come into 12:53that Harbor if you will for other customers 12:55as yours and the early adopters you guys talk about where the mainstream market 13:00is right now see from the service's stamp when you get a great presence 13:03a lot of accounts we're the ships coming into which 13:06Arbor where the lighthouses I see medically missiles example to bring in 13:10the main customers is it the new absolute driving it what innovations 13:14and what are the forces and what are the customers doing in the mainstream right 13:18now where are they 13:19in the evolution moving to these kinda higher and examples 13:22so a mean so Hadoop I'd say this is the year to do 13:27where ClientID I'm serious about to do like I said it's now becoming a 13:30board-level topic 13:32on so its it's at the forefront right now 13:35I'll I see clients been very aggressive about trying out new use cases 13:40everybody really cross every interest industry is looking for one thing 13:44which is growth in the way that you get growth if your bank 13:47is you know we're gonna change your asset structure what you gonna change is 13:50how you engage clients and how you personalize offers 13:53if your retailer you're not gonna grow by simply adding more stores 13:57on might be a short term growth impact you're gonna change 14:00how you engaging with clients so these use cases are very real 14:05and they're happening though Hadoop is a boardroom discussion or big 14:08II the formula we have work to do were is that you know I 14:12i've seen your over and over again Lt where you see a lot from his 14:16companies that are private equity owned from the private equity guys have 14:20figured out that there's 14:21savings and there's innovation here every company I worked with that has 14:25private equity ownership 14:26Hadoop is a boardroom discussion and the ideas how we modernize the 14:30infrastructure 14:31because its it's because other forces though it's because I've mobile 14:35it's because I've cloud that comes to the forefront so absolutely 14:39so it was a good do so I do was great batch is great value movies is going on 14:42there 14:43boardroom in the private because when they're cutting edge probably like your 14:46investment one cellular 14:47pretty quickly yell speed is critical right I would infer that was coming from 14:51the private equity side 14:52speed is critical right so speed to value what does that mean 14:56for IBM your customers how do you guys to live with the speed to values that's 15:00more than things 15:01comes out all the premises of all the conversations as taking it is faster now 15:05so value in the business I will you guys sure so 15:09lot of different ways to approach that so we believe that 15:13as I said what I said before it's not just about the infrastructures about the 15:16inside 15:17we've got a lot of analytic capabilities into what we're doing around 15:21do and spark so that clients can get answers faster 15:25so one thing that we're going to be we have a session here Strada this week 15:29talking about our new innovations in big are 15:31which is are our algorithms which are the only our algorithms that you can run 15:36natively on Hadoop 15:37where your statistical programmers can suddenly start to 15:41from you know analyze data and you know drive that to decision-making as an 15:45example 15:46so we believe that by providing the analytic some top the infrastructure 15:50you can get you can change how clients are getting I R so we'll quickly 15:54arm we've got IBM Software so we've got our Hadoop 15:58infrastructure up on the cloud so anybody can go provision something to 16:01get started and 16:02hours which is not something that was the case even a couple years ago 16:06and so speed is important but the tools and how you get the Insight is 16:10equally important abouts Peter 16:13to value customer deployment standpoint is that the app's was it innovating on 16:17existing 16:18which would you sing well I think it's both 16:21actually arm and and so you talked earlier about system and engagement 16:25versus system of record 16:27you know and I think it into the day 16:29the arm for client is really about systems admin site which is some 16:32combination of that right we tend to think the systems and engagement or the 16:36neuwirth things in your applications and we tend to think the system's record the 16:41older ones but I think it's a combination 16:42and we see it show up in different ways so arm I'll take an example telco 16:47an we have a solution on the now factory 16:51and this is now about applying analytics 16:54in real time on on about 16:57the a network in the dynamics so that for example the operator 17:02has a better view love what's happening for their customers their 17:06in users and they can tell that an application has gone down 17:11and that customers have now switched all the Sony using 17:14a competitive application on a mobile devices you know that's 17:18different and that is that new applications 17:22or old or is it the combination and I think it the day it really comes to a 17:25combination 17:26love the systems that inside I'm just gonna write that down here inside the 17:30said the crowd chants so I gotta talk about the 17:33the holy grail for big data analytics and big data 17:37from your perspective ideas perspective and two where you guys are partner 17:41house the year the shower rich targets 17:44evacuee buyers acquisitions partnerships I mean it's really a program service ok 17:50and valley and 17:50and in the growth big day cloud mobile social 17:54things come together what is the holy grail from your perspective us the 17:58system's 17:59inside teases that out cognitive is a mess as we've heard 18:02so what is the holy grail and then what he is looking for in partnerships and 18:07within the community startups and/or other alliances 18:11sir to restore the was growing he also 18:15other so you know I think it into the day 18:18I'm it is about using technology for Business Value 18:23and business outcome I you know i i really think that's what 18:27the spirit and so if I tell you why we have for example 18:31increased are in attention 18:34dowsman around this topic is because I that it's because what Rob said earlier 18:38when he said the state that clients are now in 18:40arm so that's what i think is really important there 18:44and I think its only going to be successful if it's done 18:48based own standards and something that 18:52is in support love you know heterogeneous environments 18:57i mean that's the world technology that we live in and that's a critical element 19:01to that which leads to why we're apart 19:04the Open Data platform initiative so 19:08the the peace analytics 19:12I'm discuss our common are for example I was just mentioned the crowds at 19:16I make such as part revolution analytics which is not are which is different to 19:20me 19:20is /url angry have going on between the big guys you know I gives a big company 19:25with you guys see in that kinda area arms acquisition targets 19:29yeah I think the numbers would say there's not a land grab I don't think 19:33the only numbers changed 19:34at a macro level at all the last couple years I've been 19:38were very opportunistic in our strategy right we look for things that augment 19:42what we do 19:43I think you know Julie Department 19:46your car your question on partnering bird we do acquisition is not only about 19:50what that company does 19:51but it's about how does it fit within what IBM already does because we're 19:54trying to 19:55we know world going after rising tide in terms of how we deliver our clients need 19:59I think some companies make the mistake they think that if they have a great 20:02product that's relevant to us 20:04maybe maybe not but it's about how sits in what we're doing in 20:08that's how we look at all of our partnerships really and you know we 20:10partner with 20:11global systems integrators even know we have one with an IBM 20:15we partner with I is to use application developers 20:18the big push this week as I describe a fourth-round a to scientists they were 20:21rolling out 20:22data science education on Big Daddy University because 20:26we think that data scientists will quickly find that the best place to do 20:30that 20:31is on an IBM platform because it's the best tools 20:34and if they can provide better insight to their companies are to their clients 20:37they're gonna be better off so I was so yesterday as the commenting on 20:41answer me ended last week an earlier this week about that Twitter 20:44is like on Twitter's figure out people are confused but whatever space book in 20:48and no idea relation which was just swipe made 20:51and I was icing hate what is a great value so I was on the side 20:55yeah it was a winner Twitter love the company misunderstood certainly I think 20:59in this market with his waves coming in more and more 21:03what a misunderstanding I think when I get your perspective you can share with 21:06the folks out there 21:07what is that next week because it's confusing out there you guys are 21:11insiders IBM I would say like Twitter 21:13is is winning doing very well certainly never were close to you guys we're 21:16work were deeply reporting on IBM's we can see the momentum 21:20and positioning it's all in why what we see is that 21:23is is where the outcomes will end up being for customers but this still out 21:27on a stair it's out this early cuz i do share 21:29as as as to where example so what is the big 21:32misunderstanding that you think is out there 21:36around the market were in and what's the next wave 21:40means always ways coming in you not out for the next wave 21:43usually dressed with your expression goes so what is that big 21:47misunderstanding in this kinda Convergys com 21:49hyper targeted with alex is all new stuff huge opportunities 21:54huge ships an inflection point Bapuji on a set on the Q's 21:57both going on same time ship an inflection point so was misunderstood in 22:02with that 22:02next waves so let me start with the next day where the hell back into 22:06and the misunderstanding so next big wave to me is machine learning 22:10and how do you start to take the data assets that you have 22:15and through machine learning in the application those type algorithms 22:19you start to generate better insights or outcomes in 22:23the reason I D is the next big wave is its it may be one the last competitive 22:27modes out there 22:28you think about it if you have a a corpus a datum 22:31that's unique to you and you can practice machine learning on that and 22:35have that 22:36you know either data that you can sell or defeat in your core business 22:40that's something that nobody else to replicate so becomes incredibly powerful 22:44on so one example share with you and 22:47I want to bring in my book but its action are getting published on that 22:50sent maybe next week but so while is publishing a book I wrote 22:53and willing and able to give us a company by the name of coast are 22:57which I think very few people have heard of um co stars in the commercial real 23:01estate business 23:02they weren't even around a decade ago they have skyrocketed you know 23:06from zero to five hundred million dollars in revenue and it's because they 23:10had data on four million commercial properties out there 23:13who else has that actually nobody has that kinda reach 23:17and so they got a unique data assets they can apply things like machine 23:21learning in statistics to that 23:22and there for anybody who wants to do in in commercial real estate 23:26has to start with them so i point is you're sure to get the point we have 23:29some 23:30businesses where data is the product 23:33it's not an enabler it's the actual product and that's probably what are the 23:37big misunderstandings out there 23:38is that you know data system that serves our existing products or existing 23:42services 23:43we're moving to rover date is the product and that's the moat are posted 23:47a court date is the new development kit and what you're basically saying is that 23:50the competitive advantage 23:51a business user can make innovation observation about data 23:55and not be a scientist and change the game that's what you were saying earlier 23:58similarly because the next big wave misunderstanding what he waits 24:02publisher taken what are people not getting what is wall street 24:05what is potential the ceiling on the front and some the innovation but what 24:09is the general public not getting 24:11we are in shift inflection point with the big 24:14shift and misunderstanding so so I 24:17I went into you know actually agree with with wrought that I think folks 24:22aren't yet arm really appreciating and I guess I would twist in a little bit and 24:27say 24:28the Insight arm instead adjust the data but 24:31but they're not realizing what that is 24:34and what it's going to give us the opportunity for you know 24:38arm I would retire early if I actually could predict 24:42everything that was going to happen but but you know I 24:45could you help but if you think about it you know if you think about 24:49you know mid to late 90's and what we would have all fall 24:55that the internet was down all hours to do 24:59compared to what it actually allowed us to do 25:03is probably like night and day and I think the the time we're in now when you 25:07take 25:08data and you take arm 25:11mobility and you take wild and you take these systems are being gauge mind 25:17and the fact the way people individuals actually want to do things 25:21is is similar but almost like on steroids to what we were doing within 25:25the 25:26the mid nineties or so and so you know 25:29the possibilities or are frankly in lights and 25:32and I think that's part of what people aren't necessarily 25:35realizing is that they have to think about that insight that data that 25:40actually has some value to it in very different way 25:43lot of disruptive enables out and 25:47this lot look Apple fight in which ones will be the biggest 25:50right is hard to me you get paid a lot of money to do that as if you figure it 25:54out 25:54keep a secret yeah majid in Yuma sheila is now out there you this 25:57share benefit VANETs everyone knows another and continue had on the inside 26:03but 26:03but not everybody's use it right I mean I think another example a company like 26:06intuit has done a great job 26:08the start of this offer company they become the data company I think what you 26:12what I've observed in all these companies as you can build a business 26:15model that's 26:16effectively recession-proof because data becomes the IP 26:20in the organization in so I don't I actually 26:24you know I think for us doesn't deliver the world we think this is well 26:26understood 26:27I don't think it's not well understood yet insider my right 26:31and you know when we first started doing on big data 26:34research and working with thousands of clients around the world they were 26:38there were six basic use cases it started of course with the customer the 26:42in customer and the customer 360 and that sort of thing went through a number 26:45of different things around 26:47are optimization ex ever but the additional line is about those new 26:52business models 26:53an you know that clearly in the last 12-18 months has become a lot more what 26:58the topic is 26:59when I'm talking to clients on and I think we will 27:03see that expand even more as we go in the future with a lot of activity in the 27:07crowd check on chat 27:08slash you necks and I'll mention we get priced in time 27:12you guys wanna keep it keep going conversations are so when you getting 27:15that ok here 27:16so we'll move the conversation to 27:19cratchit an SSD next great thought leadership in acting on the stuff for an 27:23hour you guys are awesome great agony cue 27:25so much to talk about what a great we'll certainly see it in a conectar al final 27:29question for you guys is 27:30where you guys see for this week real quick summarize what do you expect to 27:33see a on fall 27:35for big data week here in Silicon Valley the DSP 27:38so I think yes 27:41love the we talked about machine learning is going to be a big topic I 27:45think to be a lot of discussion around the Open Data Platform that mission 27:48before it's a big move 27:49that we made along with another group supporting the Apache Software 27:52Foundation I think that that's a big thing for this week 27:55arm but should be exciting i right gas station on you gotta be in here inside 28:00the cube we live in Silicon Valley with the right back with an ex guess if the 28:03strip break 28:03i'm jennifer is the QB rape