Next concepts that we are going to talk about is the concept of pair of tangents Now from a point external to a parabola from a point external to a parabola You can always catch two tangents to the parabola One is like this another is like this Okay, so let's say this point is h comma k And you can draw two tangents to the parabola. Let's say P t1 and P t2 Okay, then the combined equation of these two tangents is called the pair of tangents Okay, and we had already learned about this in circle as well that the combined equation of The pair of tangents is given by t square is equal to ss1. So nothing changes even in case of a parabola What is t in this case? Let's say if I'm talking about y square is equal to 4ax parabola. What is t in this case? T will be y y1 y1 will be k. This is your x1 y1 Okay, y1 will be k Equal to 2ax plus x1 Okay, what will be s? What will be s s will be y square minus 4ax What will be s1 s1 will be k square minus 4ah So you can write down the combined equation as t square which is this equal to s s1 So that will give you the pair of tangent equation pair of tangents combined equation pair of tangents Combined equation, okay So nothing new here. It is very much similar to the concept which we had learned before as well Okay Now chord of contact chord of contact. What is chord of contact? Chord of contact is nothing but the line connecting the points of contact of these two tangents So this line is called the chord of contact And just like we learned in case of a circle chord of contact equation is still t equal to zero that means yk minus 2ax plus h equal to zero Okay Let's take a question on this concept prove that the area of the triangle The area of the triangle Formed by the tangents drawn from x1 comma y1 to the parabola y square is equal to 4ax and their chord of contact and their chord of contact is y1 square minus 4ax1 to the power of 3 by 2 divided by 2a So please take few minutes to work on it. Very simple problem In case you're done with the problem, please type done on this on the chat box so that I can start the discussion Yeah, so we need to find the area of this triangle pqr that you can see on your screen This point is x1 y1 Now if anybody is trying to attempt this problem, of course, uh method that would come in your mind is Okay, we we can find out the length of the normal drawn from this point Okay Uh, let me call it as m And we can find the area of the triangle by using half into base into height So half into qr into pm Now finding pm is not difficult because you know the equation of this line Right the equation of this line is yy1 is equal to 2ax plus x1 And you know this point p so you can always find out the distance of the point p from the line qr Which is actually your chord of contact But how do I find this is easy? Okay, but how do I find qr? That is the length of the chord of contact How do I find that? See for that you have to go the other way round. Let's say this point is a t1 square comma 2 a t1 And this point is let's say a t2 square comma 2 a t2 Okay Now the meeting point of these two tangents we all know from our previous formula It's actually a t1 t2 comma a t1 plus t2 remember Goa correct That I discussed in the session the other day Right Now According to a given problem a t1 t2 Will be equal to x1 And a t1 t2 will be equal to y1 correct Which implies t1 t2 is x1 by a And t1 plus t2 is equal to y1 by a Okay Now these two in piece of information is very important for me because it will help me to write the Length of this tan length of this chord of contact in terms of x1 and y1 So if you see qr is nothing but Under root of x1 minus x2 square Plus y1 minus y2 square Okay And if you try to simplify it Right by taking your some terms common First of all a could be taken out common So mod a will come out From inside I can take t1 minus t2 whole square also common Okay, and I'll get t1 plus t2 whole square Plus four So that will become mod a t1 minus t2 will come out in fact mod of t1 minus t2 will come out And within the brackets I'll get t1 plus t2 square Plus four Now t1 minus t2 mod is as good as saying t1 plus t2 whole square minus four t1 t2 Yes or no So this term could be written like this Mod t1 minus t2 is nothing but t1 plus t2 whole square minus four t1 t2 So if I decide to use t1 plus t2 as y1 square by a square This is what I will get Correct and here I will get y1 square by a square plus four Okay, we can simplify it And if you simplify it I'll get a mod a mod a out. So you'll have one by mod a Under root of y square minus four a x1 Into y1 square plus four a square Okay, so this will be your qr. What about pm What about pm? So for pm, you will directly use the distance of a point from a line. So you'll say y1 y1 minus 2a x1 plus x1 mod By under root of y1 square four a square Which is going to be y1 square minus four a x1 mod Under root of y1 square plus four a square Okay, now I can use the two formulas that is half qr into pm That will give me half one by mod a under root of y1 square minus four a x1 times y1 square plus four a square into y1 square minus four a x1 mod by under root of y1 square plus four a square So this term and this term will get cancelled So you will get the answer as one by two mod a now mod a is as good as a because a is always positive in a parabola So it's one by two a y1 square minus four a x1 to the power of three by two and that's proved Okay So quite a lengthy problem, but I'm sure you would have understood the concept now moving on to the next concept That is the equation of the chord bisected at a given point equation of a chord bisected at x1 y1 So please note that the equation just like in case of circle becomes t equal to s1 that means If I'm talking about the parabola y square is equal to four a x t will be y1 minus two a x plus x1 Is equal to s1 s1 will be k square minus four a sorry Not k square It will be y1 square minus four a x1 Okay So without wasting much time, let us look into problems which have been asked in this case find the locus of the find the locus of the midpoints of normal chords of the parabola y square is equal to four a x I'll make this question as show that so that you can prove it Show that the locus of the midpoints of the normal chords of the parabola y square is equal to four a x is y to the power four minus two a x minus two a y square Plus eight eight to the power four equal to zero Again, please remember locus questions are very very important because j simply likes locus questions So, please think about it very simple concept any idea guys okay, first of all You have been given that you have to find out the locus of the midpoints of normal chords So if I just ask you what will be the locus let's say the point The midpoint is h comma k. Okay Let's say the midpoint of the chord is h comma k Then what would be the equation of the chord?  This is nothing but s one t equal to s one is the equation of the chord Whose midpoint is given to you? correct Now you are claiming that Now you're claiming that this chord is also the normal This chord is also the normal to the Parabola right that means We can compare this equation with the equation of the normal And we know the equation of the normal is y plus tx is equal to two at plus at cube correct So this is the equation of the normal And both the equations are actually the same equations Both the equations are actually the same equations. Correct. So can I compare their coefficients? So when I compare their coefficient, I can say one by k Let's say this is the one one divided by k Is equal to uh By the way, I have to rearrange and write it in a proper way first Just give me a moment So this I have to write it as y k minus two ax Is equal to k square minus two a h Okay Now we can compare these two So comparing Let me call it one and two So I get one by k is equal to t by minus two a is equal to two at plus at cube By k square minus two a h Remember I have to eliminate t because t is something which I introduce in the problem and that's a parameter So we have to eliminate t which can be easily done through this equation So t is minus two a by k correct And now I can use these two equations Okay, so from these two equations I can say t by minus two a is equal to t times two a plus t square By k square minus two a h t and t gets cancelled Just cross multiply so you get k square minus two a h Let the minus two a be over here that is equal to two a plus at square So this will become k square minus two a h by minus two a is equal to two a plus a times Four a square by k square.  So it becomes k to the power four minus two a h k square And on this side I get minus four a square k square Minus eight eight to the power four collect the terms So it'll become k to the power four Minus two a Uh, we'll have minus two a k square. You can take common. So it'll become h minus two a Plus eight eight to the power four equal to zero Okay, now just generalize this So when you generalize this We get y to the power four minus two a y square x minus two a Plus eight eight to the power four equal to zero And that resembles with the required equation over here as you can see This is what we obtained down over here as well. Okay So let's move on to the next concept now any question so far guys Please feel free to type it in the chat box


Hi, I'm Peter Burris. Welcome to another CUBE conversation from our beautiful studio here in Palo Alto, California. And once again, I'm joined by Eric Herzog. Eric is the CMO and vice president of channels in IBM Storage Group. Eric. Well, thank you. We love coming to see theCUBE. And by the way, I'm a Palo Alto native. Yeah, I've heard that. You know, I don't think we're going to get into that today. Maybe somebody, Tommy, could talk about that. But what I do want to talk about is storage has historically been way down in the food chain of strategy, of business strategy. Now we're talking about digital business. And digital business, at least from our perspective, and I think you would agree, is predicated on the idea that you use data as an asset. In fact, Wikibon says that the difference between business and digital business is digital businesses use data as an asset. Now, since storage is where you put that data and is responsible for availability, throughput, reliability, flexibility and how you do things differently with data, that kind of elevates storage's position as part of a strategic digital business capability, but nobody talks about it. So as a smart guy in the storage community, I'd like to talk to you a little bit about that. First off, you agree with my proposition? Yeah, I would posit that in today's digital business world built around private clouds, storage is, if not the critical foundation, one of the top two critical foundations you have to rely for your digital business. So if you're the CEO or you're the CFO and you know you're gone digital business, if the storage goes down or the storage is slow, your digital business and the value of that data you're driving both internally and for your customers just dramatically shrank. So it's critical, critical, just as when you're building a giant building in downtown San Francisco or downtown New York or downtown Singapore. If you don't have that foundation right, the building literally can fall right down. And in San Francisco, one of the big buildings is actually starting to lean about two or three degrees. There's got a bunch of people pretty freaked out. But let's talk about therefore, what are the strategic digital business capabilities that are associated with storage? That's CXOs have to start thinking about. You mentioned one, we call a true private cloud. The idea that you're still going to need some capacity where the data has to be because you're not going to be able to put everything in the public cloud. So true private cloud is going to be one of them. What's another one? So I think the big thing here is modern data protection.  You've got to be able to give them real, real data sets to work with. Now that doesn't mean you can't track it in case there's a data leak or whatever. But the bottom line is you want those developers A, always be able to get it. B, have it to be self-service because the IT guys are keeping your digital business up and going. They can't be bothered with, hey, can you get me real data set? The quality of the data that those developers produce for you goes way up.  And it gets it faster.  So you want those DevOps guys constantly working and you want to be able to do that. Yet at the same time, the IT guy can focus on what they need to do. And by the way, they can track where all those copies of the real data sets are. So everybody wins and it makes it work well. So in many respects, what you're saying is that availability, which used to be associated with the performance of an individual application, is now associated with digital business strategy because you need to be able to test new business ideas, pursue new business ideas, be fast in bringing things to market. And the whole notion of availability extends beyond just making sure the data is where the application says it needs to be, to now using availability as a metric for ensuring that the data can be where it needs to be within the business so the business can make the appropriate changes and adjustments and extensions to what its strategy is. Well, think of this as you've got a data set. The more you use that data set, not just for the primary storage that gets used by the end users that are coming to your digital business, for everything else, back it up. Okay, great, check box. Okay, interface with common API so the DevOps guys can use it, another check box. Making sure that the test guys can test real data sets, not faux ones. Guess what, faster test time, more accurate test time, boom, better impact for your digital business. So extending the value of the data from just primary storage throughout your entire digital software development process is critical. And in today's world that's what you can do with the modern data protection that for example we have with our IBM solution. So let me build on top of that because I think another capability might be increasingly associated with speed of development. It used to be, again, that storage was very closely aligned with what your server needed. Increasingly we're starting to see the concept of data protection and the concept of data availability actually start to mean something very, very different to developers. Are we now seeing developers and the developer ecosystem start to drive more of what's required in storage? Well you've got to look at it, the developer wants to be able to spin things up quickly on their own. So in the old world you do a ticket, you give it to the VMware guy, the Hyper-V guy, the IT guy, it takes a week or so. You don't want to do that. So with our stuff for example you can check in and check out. It integrates with all their APIs. They can quickly do their work. It's a real data set not using fake data so that makes it better from a reliability perspective and it gets done faster and they know how it really is going to work when you deploy that in your digital business. They can check it in and check it out themselves so it happens way faster. So all that means for you as a digital business guy is better time and faster time to market with more reliable products for your end users. And that's kind of the key. That's kind of what the goal is. So we've got three this far. This notion of true private cloud where we need resources where the data demands, this notion of modern data protection which is to say that the notion of availability is beyond just backup and restore. It's now the multiple ways to use it. New communities that are going to be more closely associated with storage capabilities like the developer world. Are there multi-cloud? Are there other kind of strategic business capabilities at CXOs I have to think about as they envision their digital business strategy and the role that storage is going to play in either constraining it or facilitating it? Well, I think there's a couple of things. First of all, you can look at it in three buckets. Item one is that your storage infrastructure, you still may have some of your older stuff. You still may be using Oracle, not yet using Hadoop and you're using an Oracle data warehouse versus Hadoop big data analytic workload. I hear there's some customers out there that still have Z series installed running things. So you've got to be able to take the thing and cut costs on your traditional infrastructure and your traditional applications, workloads and use cases while you're going to the next generation and modernizing. So you want to be able to handle the older workloads and cut their costs. At the same time, invest more in things like Hadoop and Spark and Mongo, okay? And Cassandra, you want to be able to do both. At the same time as you create your private cloud infrastructure, you want to be able to use new paradigms such as containers. And if you're going to do that, you want a set of storage solutions, both software and array infrastructure that can support that. And that's a critical element is being able to A, modernize and cut costs of your older while you're moving to the new. For all your new stuff, you want to be able to that it's optimized and the DevOps guys can work it and you got all the right APIs. And then for the true private cloud, you're going to containerize model just like the public cloud guys do because you want every advantage for your own digital business that the public clouds and we can do all of that. But it's critical that you do all of that continuum from the newest of the new to the application in the middle, but you still have the old stuff while you're getting the new stuff up and running. So it's critical if I'm the CEO to make sure that my storage does all of that because if I fall down on the old stuff, well, that's a problem. I can't bill, I can't invoice, I can't ship things. If I fall down on the new stuff, guess what? I'm completely uncompetitive, right? And when I fail on the container world, what I'll call the refactoring of my infrastructure, I've totally lost the game because I'm not making it fast. I'm not making resilient. I'm not cutting my cost because everything is cost competitive. And if data is the value, everything's built around that data. That doesn't mean you want your data to be super expensive. Got to figure a way to do it cost effectively, yet still deliver the value in your digital business that the end user wants to see. And it's got to be flexibility across the board. Okay, so we've got some strategic capabilities that CXOs have to think about that storage is going to enable. February 2018, we're looking at say October 2019, next 18 months. What's going to be the one or two biggest changes in the storage world, do you think? Okay, first thing is going to be the automation of storage software across the board, not just for the storage guy, not that all storage companies don't love the storage guy, but increasingly there's a move to DevOps and other functions. So while each company is managing eons and eons and eons of more storage capacity, they're not adding eons and eons of storage admins. So you've got to have the Docker guy, you've got to have the application guy, be able to back up, be able to optimize their workloads, be able to go ahead and spin up a new container without calling the IT guy, because the IT guys are overworked. So that's item one is integration with all the coming APIs, automation, self-service are critical. The more it's automated, the more self-service is, the more you can factor in the non-storage guys into creating a true digital business. So that's item number one. Second thing you've got is there's a new technology known as NVMe. This is a very high-performance storage interface. It's new to the market. All the big storage vendors are working on, including IBM. We did an announcement on February 20th all about NVMe. The value there is more and more applications and workloads because the performance of the system itself, which is already highly resistant, highly available and highly capable of handling any failure mode, is it's super fast, which means you can put more and more applications and workloads on a physical infrastructure, which saves you time and saves you money. So those are two critical things. The rise of this automation paradigm and the self-service paradigm across all of your storage software and integrating it with your application layer, be able to use real datasets as modern data. And then this new high-performance storage interface that will dramatically allow more workloads for every ounce of storage you buy, saving you money, and also making it highly performant to meet your digital business SLAs. I think those are two great ones. I'm going to add one more and I'm sure we're going to be talking more about this. I think over the course of the next year and a half, we're going to see even greater understanding over the relationship between storage and data and new rules, new conventions, new approaches to how to think about that relationship. So that all of this great stuff that's happening within storage actually does become a strategic business capability. Yeah, you could say that storage management software will morph into data management or at least a hybrid of partial managing the storage, but actually also managing the data and things like what is the metadata and how can you use metadata more effectively manage your business? And we're doing a whole bunch of that with IBM and we've already announced several things around that. So that's an actually great observation. And it's not too far from there to say digital asset management. Not in the traditional, not in the marketing sense, but overall how it works. Eric Herzog, CMO, Vice President of Channels, IBM Storage. Once again, thanks for coming on theCUBE and talking to us about some of the things that are going to happen over the next 18 months in the storage world. Great, thank you very much. We always appreciate being with you and thanks again. I'm Peter Burris. Once again, this has been a CUBE conversation from our Palo Alto studios with Eric Herzog of IBM. Until next time.


We all agree that film is a tremendous pedagogical resource that can be used in the classroom across the disciplines. Here at Tulane, we are privileged to have one of the broadest film collections in the region, and in media services at Howard Tilton Memorial Library, we've developed a number of services to support your teaching. The film collections provided by Howard Tilton Memorial Library are both streaming and physical. Our streaming titles, of course, can be viewed wherever there's an internet connection. Recognizing that personal DVD or Blu-ray players are no longer household items, you'll find several viewing stations on the sixth floor of Howard Tilton Memorial Library. We also have portable USB disc readers, as well as Blu-ray players, available to check out from the sixth floor service desk for as long as one week. Many faculty ask about clips. Media services does not have the capacity to create clips for you, but many of our streaming platforms have that functionality built in so you can create and save your own custom clips and easily share them with your class and your Canvas page. Streaming platforms in our portfolio that have clipping include Academic Video Online, DocuSeq, Canopy, and Lumiere. An important service is media reserves. The majority of our streaming titles are only available to us with one or three-year access licenses. This means a film available today may not be available tomorrow. Since most of our platforms do not make the expiration date visible, this can be difficult for planning. To help with this, we redesigned traditional physical media reserves to include streaming titles as well. When you fill out your reserve request form, simply include all the titles you plan to screen in class, regardless of whether we currently have access or not. The media service team has a rigorous workflow in place to verify expiration dates and flag titles for renewal as necessary, as well as to comb through all streaming access options available to us. Finally, all of our films may be used in the classroom setting. A campus screening, however, requires public performance rights, which only a portion of our film has. If you see a film in our collection that you'd like to screen but are unsure of the rights, simply email media-services-at-two-lane.edu and we'll verify the type of screening rights available for that film. If you have any questions or need help finding a film, please reach out to us at media-services-at-two-lane.edu.


Back here live at HP Discover in Frankfurt, Germany. This is siliconangle.com's theCUBE, our flagship program. When we go out to the events and extract the signal from the noise and share that data with you. And I'm excited to be here. I'm John Furrier, the founder of SiliconANGLE. And this is an exciting discussion with autonomy. And Andrew Joyner, who's the general manager of emerging technologies and worldwide marketing for the autonomy portion of within HP. And Brian Weiss, welcome to theCUBE, guys. Thank you, John. Thanks for having us. We have autonomy in theCUBE for the first time. Obviously, I've been blogging publicly about the whole thing, been big proponent of big data. If you follow SiliconANGLE, you know that we love big data. We've been following it since the beginning and we love big data. So you guys, this is your wheelhouse. Obviously, autonomy has pioneered a lot of stuff on the enterprise side, which is very difficult to do. And now with big data exploding with unstructured data and integrating that in with analytics being the killer app of all time right now. You guys now walk into HP now, a good what, year and a half after the acquisition? It has been. You know, what's interesting is this is the first time in HP that all the software assets are underneath one house within HP software. And then within HP software, we have these two really unique software engines. So we have the autonomy engine, which is called IDLE. And we have a Vertica engine. And together, both of those engines were really almost purpose built and designed for big data. You know, if you think about 90% of the information that's inside an enterprise, it's all this human friendly information. It's all the stuff we all consume and love. It's emails and it's blogs and it's tweets and documents. You know, all of that stuff's of a variety. You know, we send it and receive it all day long. So it's of a high velocity. So from day one, we've had all the troubles that many of the organizations had. We've had to designs our systems to handle that. But with Vertica, they're also able to handle the extreme structured stuff. So yesterday for the first time, we talked about to the press and to the community about this bringing together these two worlds, the unstructured, the unstructured. For the first time, we have two unique software assets inside of HP that can handle it. And then what we did is we put in, we had a long list of people from storage, from services to get the alignment. And so it's really been the only HP now. It was a really exciting day for us to talk about we're really geared for big data.  We don't want to go there. Obviously I blogged about it and you go to SiliconANGLE and search on some of my blogs if you want it, if you want to get my opinion on that. But when we were at HP Discover in Vegas, we talked with a lot of folks and the buzz around autonomy, yeah, again, this is pre-storm that we're seeing now, but it's a lot of great buzz. And we talked to people from the laser jet division all the way up through the systems guys and services who had just said, yeah, this is like candy for us because now because big data is so sexy at the market level, HP now can integrate some of that magic into some of their infrastructure and systems products. So there's been a lot of excitement. Now rolling now six months forward, where are we today with you guys within HP? Because yesterday we heard that big data is native within a lot of the different products and services group within HP where we're seeing demos, David Scott did a demo on stage and that was awesome.  And then you get the services guys who were going into customer environments where big data is a mandate with analytics driving it. So it's the confluence of real-time information with large-scale on-demand infrastructure. So it's a perfect storm for that paradigm. So good opportunity for HP. So share with us where you guys are internally and just share some anecdotal. I'd love for Brian to give you the color because traditionally autonomy was just a software paradigm. So we would go to people with big data and then the customer had to figure out how to do it on hardware platforms and how to align services and so forth. And what we've done since the acquisition is we made a lot of progress. You're seeing idle and autonomy power a number of different initiatives. Why don't you share some of the ones you've done. So the exciting one you mentioned is the storage integration. And the problem you come up with a big data is that you have to do all the processing outside of the storage layer and you have to trade off the amount of hardware it takes to keep it fresh as opposed to being able to get real-time information. And it's a real tremendous shame that you can't actually use the hardware itself to do the work, the storage hardware. And so what the storage group is on is taking that processing and they're doing it natively at the storage layer. Which when you think about it is sort of a unique HP proposition, right? We can have that bit of the processing for the data that first comes in as it lands keeping it fresh, that work happens on the store all device. And so I look and now move almost 40,000 times faster as far as its ability to create indexes because the work is happening at the storage. Yeah, I mean it was interesting obviously Silk and Angle and Dave runs we keep on our research side. One of the two areas that we're really number one in is big data. We've been covering that space since the beginning. And an area that we just announced some research on first ever report on what we call software led infrastructure which essentially is converged infrastructure modernized. So if you look at the storage as an example with flash changes the equation on converged infrastructure and the software defined trend is really, really relevant. So you mentioned software assets as a standalone that's interesting. But when you bring in software virtualization at storage networking servers, it's a complete game. So obviously that's important. And we just saw yesterday that VMware spun out spring source, cloud foundry and green plum and some other little kind of software areas where there's a automation around social data. So you can see the jockeying for position on some of these guys trying to kind of retool. So you guys are up and running. So what do you think about that trend? Using that example of the VMware spin out you guys are ahead of the game right now. I mean HP no matter how people slice and dice it actually have in place the full triple threat with software defined with Donna Telly's group you got autonomy a year and a half integrating into HP. Are you guys ahead of the competition and how do you talk about that to the marketplace? I think so because I think there's a couple of things that I think you pick up very well. One thing HP is very hard to argue with is that we can do things at scale. Now we ship a PC and a printer every four seconds we ship a server every eight seconds. So we know scale and obviously just the equation you think of a big data is scale. We do have unique assets though. So we're not just collecting and managing the data. We can actually analyze the data uniquely. I mean autonomy gives you a unique answer. It's not a relational database that gives you the same answer at scale. We give you a unique answer and Vertica can from its analytics as well give you something a unique answer. And what's interesting is when you look at information just overall it falls into two buckets. If you collect the information as a source of risk that scares a lot of people. Do I want more information in my enterprise if it's going to increase my risk? We can allow them to get more information because we have the ability to analyze and interrogate that data. We know the policies to apply against that data that you don't increase your risk. And the second thing is obviously it's an opportunity. Nothing aggravates me more than to see companies throwing away data. Throw away data, you're throwing away a lot of your opportunity. I mean any of the companies today if you look at them that are the shooting stars, Facebook, they're an information company, right? We share information, they monetize it. Google, you search for information, they monetize it. The four looking companies are the ones that are monetizing that information. So if you have the analytics and the ability to understand the information you can monetize it. For HP, what's exciting is that's a new conversation we get to have. We've always been known as an IT company. Now we get to go talk to companies about let me help you make money. So Brian, the VMware is an example, is interesting because one of the things that Dave Vellante and I are looking at right now is the stack. A whole new stack is being created. You can kind of see the moves with VMware kind of telegraphing this now, but where is the data layer? So you think about like the middleware model. The old model was compute and apps and it's the middleware. It's the same wine and a new bottle now, right? You got compute, call the conversion structure, software-related infrastructure and apps being big data, mobility, analytics, all that good stuff. But the middle layer is now data. Data portability, all these issues are being re-architected. So I'd like to get your opinion on what you think about that because you mentioned information. One of the main criteria around analytics is real time. You need low latency. And that is inconsistent with the data warehouse and the old business intelligence models. So I want to get your opinion on what do you see happening in that architecture and what do you guys have now that addresses that, the data layer, how that fits in the stack and to the real time aspect of it. Well, there's two parts to this, right? The first one is, as you mentioned, sort of how you do the analytics and where you do the processing and how you handle the compute resources necessary to do that. And the sort of the holy grail of this is to actually put the analytics as close to the storage as possible, right? So if I put it into a storage device, I want the intelligence at that storage device. I want it almost down to something like bare metal per se. But effectively, if I'm storing it and because I'm storing it, I have a view into it that's analytically intelligent. That's where we want to go, right?  I mean, so what we're going to do in a solid state, obviously I think that'll make a serious impact. And the way in which, for example, Idle works together with the storage stack which we announced yesterday, Store All, is a great example of that. Like a lot of that analytics is happening real time on the way in and so we can speed up the process of keeping the data fresh really by architecting the storage and the analytics at the same time. So let's talk about something that we can relate to which is the Twitter data. So we have a project that was showing a little bit of it where we can get the Twitter data in as such as small low end stuff, better what you guys do, but how do you look at that and how do you store all that massive corpus of information historically and then get all new data? Because one of the paradigms around social data or real time data is storing it and then do data mining takes time, right? So you got to have the ability to, one, do that as well but actually use the new data that's coming in really, really fast and we call that fast data. So I coined the term fast data a couple years ago and that is data that's happening very, very fast, mobile devices or whatever, integrated in with existing data. It's a really hard problem to solve. Can you guys talk about how you address that? Yeah, you know, Twitter is almost ideal for Idle in that we're not keyword based. We're statistically based and one of the challenges of Twitter is how do you find the real conversations about your brand? We did an analysis for McDonald's as an example. The brand team celebrated when they heard their first keyword analysis they said we get a tweet every seven seconds to celebrate. Actually, when you look at the ideas contained in the tweets, 90% of the information was about directions. I'm a mile from McDonald's, meet me at McDonald's, et cetera. The real corpus of the brand was only about 10%. So it's can you naturally understand the information without having to formulate these keywords, figure out who's complaining about cold fries. Once you find that, there's real gold in that, right? Because who's complaining about cold fries can be left to a geolocation. Suddenly you know potentially which franchises are underperforming and you've taken something that was just an information asset out in the cloud to determine which franchises are performing or not underperforming. So let's drill on that. To your point also about speed and volume, right? When you look at an analytics platform, the way that Idle is designed, it's a statistical model, right? Which has an advantage at scale over say language models or other ones. So we can do more volume with less compute power than say a different paradigm for understanding concepts. So we're uniquely positioned to handle that high end. So you're talking about the math in particular. So you can use math to offset raw compute. As opposed to for example a language model where you have to teach it English and you have to say, okay, what's the semantic model? And I got the, the things that follow the verbs are the ones that matter. So we're doing a pure mathematical model which gives us a scalability advantage for stuff. And you're absolutely right. And that stuff gets scaled, right? Well you know, I wish we had more time. I can geek out on this because you know, we love, we design our own stuff. So it's like, we totally understand. But we'll can talk about that later. But the question that's on everyone's mind right now is that in the old data, this is an intelligence market, the ability to do a query was based on a schema. So in the visualization market right now, which is the hottest areas, how do you visualize and get the insights out of the data? It's really, really difficult. So we've been following stuff like Platfora and some companies up in the Hadoop market where you can rapidly ask questions all the time. So rather it's like, it's like the analogy we said, is like imagine doing one Google search a day. That would really not be cool. But most people want to refine their queries as they find out, hey, let's throw away directions. Let's get at the brand as that example. So that ability to do that rapid query, you don't need to do a lot of data science. That's hard to do. So how do you guys address that with the tech? Can you talk about that? Sure. Yeah, absolutely. I mean, there are a couple of things, right? I mean, if you interrogate data long enough, it'll confess, as we like to say. So how do you let the ideas distance themselves? Jeffrey Kasenberg was on stage at DreamWorks. To show you how we get different answers, DreamWorks was doing an analysis about their movie Madagascar. They thought they would see a lot of traditional stuff about families liking the movie or not liking the movie. There was a cluster that stood out and it was children running from the theaters screaming. Not a lot, but there was clusters. When you double clicked, it was Nicholas Cage and Ghost Rider. Why did that show up? Turned out that a movie theater chain had inserted the wrong trailer reel.  So here's the great news. Now they can have an engagement. So they could go to those movie theaters. Typically you produce a movie, you have no engagement. Now they know who is watching. They could reach out to them and help that movie going experience. And it's because the ideas were different that that jumped out for them in using our software. A question on the tech, however. So what's important is that the analytics, the understanding of information and meaning is already done. I mean, this is kind of the point of what Idle does. It understands the information before I ask the question. It's done the clustering. It's done the analysis. And as new data comes in, it's adjusting constantly as to how that happens. So it's more about the data talking to you when you're talking about these types of analytics as opposed to let me ask the question and hope that the compute power can keep up with what it has to do. Yeah, that's actually a good point. And I want to ask the next question on that is, is that you're talking about predictive analytics. And that's an amazing business value. You get the math and the tech behind it. So like the insight around the Madagascar is just kind of a lucky strike. But hey, there's insight there. They kind of bumped into it by accident. But again, that shows that if you use predictive analytics, you get the value. So my question is, Jeff Hammerbacher of Cloudera was on Quora and he quoted, the brightest minds in our business are using big data to serve up banner ads, better banner ads. And that's just a waste. So his point was, big data's not about serving up banner ads or knowing what to do. There's a lot of other values. So final question is, both of you share a perspective of some of the things around big data that are transformative. Is it in the science side? Is it in society? So business value, what big things are happening with big data that people might not know about? I mean, from a tech perspective and some of the innovations that are coming out of it. Glad you started on that. Yeah, you know, first thing I think there's a frontier of noisy information that has tremendous amount of value that we're not mining at all. Video is a great example of this, right? To be able to understand what's happening in video. And that, so those conversations that we're having in that media is becoming something more and more important. And I think, you know, we'll gain efficiencies and insight into that type of information. It's a great example of an unmind sourced fruit. Yeah, and I think what's going to end up happening is we're no longer going to be sitting at our keyboards typing into Google, asking questions and looking at a webpage of answers. I think our mobile devices are going to allow us to find information in the real world. The computers now, the processing power is going to be able to recognize images in the real world and serve up information in a whole new class of ways. And I think that's the frontier.  It was a funny way to find information. So you see personalization as a big thing? I mean, personalization is the synthesis of all the information. You think about a smartphone device. It knows your location, the direction, what you're interested in, your profile. There's such a richness of your information that we can now give you personalized experiences. Okay, so to end the segment, I just want to final, final, final question is just quickly summarize where you guys are within HP. How you, how well integrated are you? Share some color around some of the advancements you guys have. You mentioned Vertica and you guys are now bolted together. HP's got a lot of other software that they're developing. How is this kind of fusing together if you can share without, you know, proprietary information just with the audience who might not be aware of how deep autonomy has penetrated the HP fabric? Terrific, I'll give it a penny in a Brian can as well.  Cloud, security, information, and autonomy as a unique software asset is the heartbeat of that information strategy. 90% of what's in an enterprise is this human friendly format. We continue to create and I would never bet against our need and our desire to consume and create more about human friendly information and that's what is the heart of businesses. And so I think what you will see is you will see continued services alignment from HP. You'll see continued storage innovation where they're embedding us with the storage layers and I think you're going to see us prop up in a wider, much broader, whether we used to sell through a direct sales force, you'll see us essentially rise in a number of different forms throughout each day. I'll give you a couple of direct examples like that. So since you mentioned the last discovery, we'll talk about all the various places where we were looking to be embedded. So right now, autonomy idle is integrated with ArcSight. So what we're doing at the security group is looking at all of the log files and when and if something has gone through as an email, idle will analyze that content of that information and tell me whether that event is a problem or not. So when we used to know you sent an email, now we know that that email was potentially about IP, was problematic, so we're returning some of those security things in the daily, a use case for idle inside the security group. Also printers, I don't know if you saw the announcements on Flow, which uses autonomy technology to automatically categorize information as it goes in the scanner and start off a workflow. Yeah, document management is just a killer area. Document management system comes in through the printing. So we're in printing now, we're in security now, we're embedded within the storage group and of course Vertica and Idle is the core software tech. So you guys, so it's safe to say that big data paradigm analytics included and all that good stuff is integrated throughout HP natively. Absolutely, and it's an exciting area for us. I think it's one of those transformational IT trends and I think we're at the start of it.  Brian and Andrew from Autonomy, talking about the tech and how it's integrated in HP and that's the biggest story here at HP Discover is what's going on with autonomy. They got the real deal, it's being integrated in, HP is embracing it, so the chins are up and they're not afraid to talk about it and we're happy to have them on theCUBE. We'll be right back with our next guests. Thank you. Thanks so much. Ecology and delivery undergoes a tectonic shift. Examples of these shifts are all around us today. Mobility, so.


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