>> Live from San Francisco, it's theCUBE, covering RSA Conference 2019. Brought to you by Forescout. >> Hey, welcome back everybody, Jeff Frick here with theCUBE, we're at the RSA Conference in downtown San Francisco, it's crazy, 40,000 plus people, we'll get the number later today. We're in the Forescout booth for our first time, we're really excited to be here, and, you know, part of the whole Forescout story is the convergence of IT and OT, operations technology, and those things are coming together, which is such a critical piece of smart things, and smart cities, and smart cars. We're excited to have our next guest, Elisa Costante, on. She is the OT technology and innovation lead at Forescout. Elisa, great to see you. >> Great to see you, thank for having me. >> Absolutely. So you've got a PhD in this space, you picked a field that is pretty hot, so as you think back and look at the convergence of OT and IT, what are some of the top-level things that people are thinking about, but what are some of the top-level things that they're just missing? >> Well, when you speak about OT, typically you refer to critical infrastructure and the technology that operates things. So it's cyber-physical systems, right? And when you think of IT, you think about computer and you think about the web, and you're like, okay, when the two things meet? And then you put in the recipe, you put something like an IoT device, like an IP camera, or a sensor for the number of people in a room. Now these whole things are coming together. And they're coming together because they come with a lot of interesting use cases. You can have all the data and information to configure, for instance, your building, to be as smart as possible, and to have. >> They need smart wheels on that cart, my goodness. >> Of course. And you have a clear picture of how much energy you consume and then you can basically have the energy that is cheaper, because it just arrives in the moment that you need it. Now all of these things are IT and OT convergence. And all of these things make our cities and our world smarter today. >> Right, now one of the interesting things I saw in a talk getting ready for this is, you talked about, there's always been a lot of OT systems, they've been around for a while, >> Yeah. >> But they've always been siloed, you know, they haven't been connected to other OT systems and much less being connected to IT systems. >> Yeah >> So they weren't architected for that from the first point of view. So how does that get implemented? Are they re-architecting 'em? Are you guys overlaying a different kind of control plane? How do you take these siloed applications around, say, elevator operation, and then integrate it in with all these other things? >> So what happens is that those systems are legacy systems. That's why. There are like, 60% of the modern buildings, of the buildings today, they have, they are controlled and managed by system that are 20 years old. So what does it mean? That you make an investment and you don't want to change that investment. You are not going to renew all the backbones of your buildings, or of your manufacturing and operation factories. So what do you do on top of these legacy system that have been developed without security in mind, you put the IT systems, to monitor, to control, to have remote access and remote control. And this is where, like, things can go wrong, because if this is not done properly, and by having in mind, for instance, the threat landscape, that's where you will have the controller for your HVAC exposed to the internet, and can pull down all the air conditioning in a hospital, for instance. And that's why WannaCry can come and heat and put down tons and tons of hospitals. >> Right. It's pretty interesting, you know, I think it's a pretty common concept in security for people that you should only have access, you know, to the information you need around a particular project or particular dataset. But you talked about, in some of your other talks that I saw, about a lot of these devices come out of the box with all kinds of capabilities, right? 'Cause they're built for kind of the Nth degree, the maximum use, but there may be a whole bunch of stuff that's turned on out of the box that you probably need to turn off. >> Yeah, that's actually super interesting. If you look at IP cameras, now IP cameras, they should do one thing, record stuff that they see on the screen. But actually they come with a bunch of protocols indeed, like FTPs, Samba protocols, SSDP, that announce the camera on the network, and reveal a lot of information about those camera on the network that if RPCed by an attacker or by someone with not-good intentions, might actually be leveraged to turn the camera against the owner of the camera itself. >> Right, right. And do weird things that the camera should not. And that's really part of what the Forescout solution is, is making sure that the devices are profiled and acting in the way that they're supposed to act. And not doing stuff that they shouldn't be doing. >> Yeah, Forescout is a leader in device visibility. So what we do is we enter into a network, and we give full visibility of all the IP devices that are there, and that's most of the times is a wow effect, like, the asset owner has no ideas that they had a camera that was directly connected to the internet. Or they'd have a thermostat that communicates with the servers. So all of these things, we bring basically light on the dark sides of the network. >> Right. So excited to talk to you 'cause I think the smart cities and smart buildings is such an interesting concept and going to be so important as we get denser populations and smaller areas that connected to transportation. I wonder if you could share some examples that you see out in the field where the ROI on putting these things in, the good part, is way higher than maybe people expect. That because you're combining, you know, a one plus one equals three kind of an opportunity. >> Right, so actually, one example of a very useful and smart use case is, is happening in Amsterdam right now. The Bijlmer Arena, is basically all the walls are made of solar panels, which means it gets the energy and is able to basically self-sustain the arena. The arena is one of the biggest stadiums in the Netherlands. >> Ajax plays there probably? >> Exactly. >> Alright. >> Now what they do if they have collected more energy than they are able to consume, they provide that same energy to the neighbors. Which means that you have basically a small ecosystem that thanks to the collection of data, knowing what neighbor needs how much light and energy in a certain time, you can actually even improve sustainability and going green initiatives. >> I love the innovation that comes out of the Netherlands. We interviewed a company a long time ago, and they were basically doing segmented data centers, where you would have a piece of the data center in your house and they were selling it as free heating. And I'm like, is it free heating, or is it distributed data center? But I mean, the creativity is terrific. So as you look forward, you know, what are you excited about in 2019? What are some of your top initiatives that you're working on? >> So we are working on a lot of IT and OT convergence, and especially on the IoT part. So we are looking at all those tiny devices that you would not expect to be on your network, and what they can do, and how these old systems that have been conceived to be standalone are now starting to communicate, and what kind of threats this communication can bring, and what we can do to actually defend our customers from the threats that can be arised. >> Going to be a good year. Excited to watch the developments unfold. >> Yeah, thanks. >> All right Elisa, thanks for taking a few minutes of your day, I know you said you had early meetings, you're calling Europe, calling all over the world, so thanks for taking a few. >> Thank you for having me. >> All right, she's Elisa, I'm Jeff, you're watching theCUBE. We're at RSA Conference, RSAC is the hashtag, in the Forescout booth. I'm Jeff Frick, thanks for watching. >> Thank you. (upbeat music)

>> Hi, I'm Peter Burris and welcome to another Wikibon Action Item. (electronic music) Once again, we're broadcasting from theCUBE studios in beautiful Palo Alto. Here in the studio with me are George Gilbert and David Floyer. And remote, we have Neil Raden and Jim Kobielus. Welcome everybody. >> David: Thank you. >> So this is kind of an interesting topic that we're going to talk about this week. And it really is how are we going to find new ways to generate derivative use out of many of the applications, especially web-based applications that are have been built over the last 20 years. A basic premise of digital business is that the difference between business and digital business is the data and how you craft data as an asset. Well, as we all know in any universal Turing machine, data is the basis for representing both the things that you're acting upon but also the algorithms, the software itself. Software is data and the basic principles of how we capture software oriented data assets or software assets and then turn them into derivative sources of value and then reapply them to new types of problems is going to become an increasingly important issue as we think about the world of digital business is going to play over the course of the next few years. Now, there are a lot of different domains where this might work but one in particular that's especially as important is in the web application world where we've had a lot of application developers and a lot of tools be a little bit more focused on how we use web based services to manipulate things and get software to do the things we want to do and also it's a source of a lot of the data that's been streaming into big data applications. And so it's a natural place to think about how we're going to be able to create derivative use or derivative value out of crucial software assets. How are we going to capture those assets, turn them into something that has a different role for the business, performs different types of work, and then reapply them. So to start the conversation, Jim Kobielus. Why don't you take us through what some of these tools start to look like. >> Hello, Peter. Yes, so really what we're looking at here, in order to capture these assets, the web applications, we first have to generate those applications and the bulk of that worker course is and remains manual. And in fact, there is a proliferation of web application development frameworks on the market and the range of them continues to grow. Everything from React to Angular to Ember and Node.js and so forth. So one of the core issues that we're seeing out there in the development world is... are there too many of these. Is there any prospect for simplification and consolidation and convergence on web application development framework to make the front-end choices for developers a bit easier and straightforward in terms of the front-end development of JavaScript and HTML as well as the back-end development of the logic to handle the interactions; not only with the front-end on the UI side but also with the infrastructure web services and so forth. Once you've developed the applications, you, a professional programmer, then and only then can we consider the derivative uses you're describing such as incorporation or orchestration of web apps through robotic process automation and so forth. So the issue is how can we simplify or is there a trend toward simplification or will there soon be a trend towards simplification of a front-end manual development. And right now, I'm not seeing a whole lot of action in this direction of a simplification on the front-end development. It's just a fact. >> So we're not seeing a lot of simplification and convergence on the actual frameworks for creating software or creating these types of applications. But we're starting to see some interesting trends for stuff that's already been created. How can we generate derivative use out of it? And also per some of our augmented programming research, new ways of envisioning the role that artificial intelligence machine learning, etc, can play in identifying patterns of utilization so that we are better able to target those types of things that could be used for derivative or could be applied to derivative use. Have I got that right, Jim? >> Yeah, exactly. AI within robotic process automation, anything that could has already been built can be captured through natural language processing, through a computer image recognition, OCR, and so forth. And then trans, in that way, it's an asset that can be repurposed in countless ways and that's the beauty RPA or where it's going. So the issue is then not so much capture of existing assets but how can we speed up and really automate the original development of all that UI logic? I think RPA is part of the solution but not the entire solution, meaning RPA provides visual front-end tools for the rest of us to orchestrate more of the front-end development of the application UI and interaction logic. >> And it's also popping up-- >> That's part of broader low-code-- >> Yeah, it's also popping up at a lot of the interviews that we're doing with CIOs about related types of things but I want to scope this appropriately. So we're not talking about how we're going to take those transaction processing applications, David Floyer, and envelope them and containerize them and segment them and apply a new software. That's not what we're talking about, nor are we talking about the machine to machine world. Robot process automation really is a tool for creating robots out of human time interfaces that can scale the amount of work and recombine it in different ways. But we're not really talking about the two extremes. The hardcore IoT or the hardcore systems of record. Right? >> Absolutely. But one question I have for Jim and yourself is the philosophy for most people developing these days is mobile first. The days of having an HTML layout on a screen have gone. If you aren't mobile first, that's going to be pretty well a disaster for any particular development. So Jim, how does RPA and how does your discussion fit in with mobile and all of the complexity that mobile brings? All of the alternative ways that you can do things with mobile. >> Yeah. Well David, of course, low-code tools, there are many. There are dozens out there. There are many of those that are geared towards primarily supporting of fast automated development of mobile applications to run on a variety of devices and you know, mobile UIs. That's part of the solution as it were but also in the standard web application development world. know there's these frameworks that I've described. Everything from React to Angular to Vue to Ember, everything else, are moving towards a concept, more than concept, it's a framework or paradigm called progressive web apps. And what progressive web apps are all about, that's really the mainstream of web application development now is blurring the distinction between mobile and web and desktop applications because you build applications, JavaScript applications for browsers. The apps look and behave as if they were real-time interactive in memory mobile apps. What that means is that they download fresh content throughout a browsing session progressively. I'm putting to determine air quotes because that's where the progressive web app comes in. And they don't require the end-user to visit an app store or download software. They don't require anything in terms of any special capabilities in terms of synchronizing data from servers to run in memory natively inside of web accessible containers that are local to the browser. They just feel mobile even though they, excuse me, they may be running on a standard desktop with narrowband connectivity and so forth. So they scream and they scream in the context of their standard JavaScript Ajax browser obsession. >> So when we think about this it got, jeez Jim it almost sounds like like client-side Java but I think you're we're talking about something, as you said, that that evolves as the customer uses it and there's a lot of techniques and approaches that we've been using to do some of those things. But George Gilbert, the reason I bring up the notion of client-side Java is because we've seen other initiatives over the years try to do this. Now, partly they failed because, David Floyer, they focused on too much and tried to standardize or presume that everything required a common approach and we know that that's always going to fail. But what are some of the other things that we need to think about as we think about ways of creating derivative use out of software or in digital assets. >> Okay, so. I come at it from two angles. And as Jim pointed out, there's been a Cambrian explosion of creativity and innovation on frankly on client-side development and server-side development. But if you look at how we're going to recombine our application assets, we tried 20 years ago with EAI but that was, and it's sort of like MuleSoft but only was for on-prem apps. And it didn't work because every app was bespoke essentially-- >> Well, it worked for point-to-point classes of applications. >> Yeah, but it required bespoke development for every-- >> Peter: Correct. >> Every instance because the apps were so customized. >> Peter: And the interfaces were so customized. >> Yes. At the same time we were trying to build higher-level application development capabilities on desktop productivity tools with macros and then scripting languages, cross application, and visual development or using applications as visual development building blocks. Now, you put those two things together and you have the ability to work with user interfaces by building on, I'm sorry, to work with applications that have user interfaces and you have the functionality that's in the richer enterprise applications and now we have the technology to say let's program by example on essentially a concrete use case and a concrete workflow. And then you go back in and you progressively generalize it so it can handle more exception conditions and edge conditions. In other words, you start with... it's like you start with the concrete and you get progressively more abstract. >> Peter: You start with the work that the application performs. >> Yeah. >> And not knowledge of the application itself. >> Yes. But the key thing is, as you said, recombining assets because we're sort of marrying the best of EAI world with the best of the visual client-side development world. Where, as Jim points out, machine learning is making it easier for the tools to stay up to date as the user interfaces change across releases. This means that, I wouldn't say this as easy as spreadsheet development, it's just not. >> It's not like building spreadsheet macros but it's more along those lines. >> Yeah, but it's not as low-level as just building raw JavaScript because, and Jim's great example of JavaScript client-side frameworks. Look at our Gmail inbox application that millions of people use. That just downloads a new version whenever they want to drop it and they're just shipping JavaScript over to us. But the the key thing and this is, Peter, your point about digital business. By combining user interfaces, we can bridge applications that were silos then we can automate the work the humans were doing to bridge those silos and then we can reconstitute workflows in much more efficient-- >> Around the digital assets, which is kind of how business ultimately evolves. And that's a crucial element of this whole thing. So let's change direction a little bit because we're talking about, as Jim said, we've been talking about the fact that there are all these frameworks out there. There may be some consolidation on the horizon, we're researching that right now. Although there's not a lot of evidence that it's happening but there clearly is an enormous number of digital assets that are in place inside these web-based applications, whether it be relative to mobile or something else. And we want to find derivative use of or we want to create derivative use out of them and there's some new tools that allow us to do that in a relatively simple straightforward way, like RPA and there are certainly others. But that's not where this ends up. We know that this is increasingly going to be a target for AI, what we've been calling augmented programming and the ability to use machine learning and related types of technologies to be able to reveal, make transparent, gain visibility into, patterns within applications and within the use of data and then have that become a crucial feature of the development process. And increasingly even potentially to start actually creating code automatically based on very clear guidance about what work needs to be performed. Jim, what's happening in that world right now? >> Oh, let's see. So basically, I think what's going to happen over time is that more of the development cycle for web applications will incorporate not just the derivative assets, the AI to be able to decompose existing UI elements and recombine them. Enable flexible and automated recombination in various ways but also will enable greater tuning of the UI in an automated fashion through A/B testing that's in line to the development cycle based on metrics that AI is able to sift through in terms of... different UI designs can be put out into production applications in real time and then really tested with different categories of users and then the best suited or best fit a design based on like reducing user abandonment rates and speeding up access to commonly required capabilities and so forth. The metrics can be rolled in line to the automation process to automatically select the best fit UI design that had been developed through automated means. In other words, this real-world experimentation of the UI has been going on for quite some time in many enterprises and it's often, increasingly it involves data scientists who are managing the predictive models to sort of very much drive the whole promotion process of promoting the best fit design to production status. I think this will accelerate. We'll take more of these in line metrics on UI and then we brought, I believe, into more RPA style environments so the rest of us building out these front ends are automating more of our transactions and many more of the UIs can't take advantage of the fact that we'll let the infrastructure choose the best fit of the designs for us without us having to worry about doing A/B testing and all that stuff. The cloud will handle it. >> So it's a big vision. This notion of it, even eventually through more concrete standard, well understood processes to apply some of these AIML technologies to being able to choose options for the developer and even automate some elements of those options based on policy and rules. Neil Raden, again, we've been looking at similar types of things for years. How's that worked in the past and let's talk a bit about what needs to happen now to make sure that if it's going to work, it's going to work this time. >> Well, it really hasn't worked very well. And the reason it hasn't worked very well is because no one has figured out a representational framework to really capture all the important information about these objects. It's just too hard to find them. Everybody knows that when you develop software, 80% of it is grunt work. It's just junk. You know, it's taking out the trash and it's setting things up and whatever. And the real creative stuff is a very small part of it. So if you could alleviate the developer from having to do all that junk by just picking up pieces of code that have already been written and tested, that would be big. But the idea of this has been overwhelmed by the scale and the complexity. And people have tried to create libraries like JavaBeans and object-oriented programming and that sort of thing. They've tried to create catalogs of these things. They've used relational databases, doesn't work. My feeling and I hate to use the word because it always puts people to sleep is some kind of ontology that's deep enough and rich enough to really do this. >> Oh, hold on Neil, I'm feeling... (laughs) >> Yeah. Well, I mean, what good is it, I mean go to Git, right. You can find a thousand things but you don't know which one is really going to work for you because it's not rich enough, it doesn't have enough information. It needs to have quality metrics. It needs to have reviews by people who have used converging and whatever. So that's that's where I think we run into trouble. >> Yeah, I know. >> As far as robots, yeah? >> Go ahead. >> As far as robots writing code, you're going to have the same problem. >> No, well here's where I think it's different this time and I want to throw it out to you guys and see if it's accurate and we'll get to the action items. Here's where I think it's different. In the past, partly perhaps because it's where developers were most fascinated, we try to create object-oriented database and object oriented representations of data and object oriented, using object oriented models as a way of thinking about it. And object oriented code and object oriented this and and a lot of it was relatively low in the stack. And we try to create everything from scratch and it turned out that whenever we did that, it was almost like CASE from many years ago. You create it in the tool and then you maintain it out of the tool and you lose all organization of how it worked. What we're talking about here, and the reason why I think this is different, I think Neil is absolutely right. It's because we're focusing our attention on the assets within an application that create the actual business value. What does the application do and try to encapsulate those and render those as things that are reusable without necessarily doing an enormous amount of work on the back-end. Now, we have to be worried about the back-end. It's not going to do any good to do a whole bunch of RPA or related types of stuff on the front-end that kicks off an enormous number of transactions that goes after a little server that's 15 years old. That's historically only handled a few transactions a minute. So we have to be very careful about how we do this. But nonetheless, by focusing more attention on what is generating value in the business, namely the actions that the application delivers as opposed to knowledge of the application itself, namely how it does it then I think that we're constraining the problem pretty dramatically subject to the realities of what it means to actually be able to maintain and scale applications that may be asked to do more work. What do you guys think about that? >> Now Peter, let me say one more thing about this, about robots. I think you're all a lot more sanguine about AI and robots doing these kinds of things. I'm not. Let me read to you have three pickup lines that a deep neural network developed after being trained to do pickup lines. You must be a tringle? 'Cause you're the only thing here. Hey baby, you're to be a key? Because I can bear your toot? Now, what kind of code would-- >> Well look, the problems look, we go back 50 years and ELIZA and the whole notion of whatever it was. The interactive psychology. Look, let's be honest about this. Neil, you're making a great point. I don't know that any of us are more or less sanguine and that probably is a good topic for a future action item. What are the practical limits of AI and how that's going to change over time. But let's be relatively simple here. The good news about applying AI inside IT problems is that you're starting with engineered systems, with engineered data forms, and engineered data types, and you're working with engineers, and a lot of that stuff is relatively well structured. Certainly more structured than the outside world and it starts with digital assets. That's why a AI for IT operations management is more likely. That's why AI for application programming is more likely to work as opposed to AI to do pickup lines, which is as you said semantically it's all over the place. There's very, very few people that are going to conform to a set of conventions for... Well, I want to move away from the concept of pickup lines and set conventions for other social interactions that are very, very complex. We don't look at a face and get excited or not in a way that corresponds to an obvious well-understood semantic problem. >> Exactly, the value that these applications deliver is in their engagement with the real world of experience and that's not the, you can't encode the real world of human lived experience in a crisp clear way. It simply has to be proven out in the applications or engagement through people or not through people, with the real world outcome and then some outcomes like the ones that Neil read off there, in terms of those ridiculous pickup lines. Most of those kinds of automated solutions won't make a freaking bit of sense because you need humans with their brains. >> Yeah, you need human engagement. So coming back to this key point, the constraint that we're putting on this right now and the reason why certainly, perhaps I'm a little bit more ebullient than you might be Neil. But I want to be careful about this because I also have some pretty strong feelings about where what the limits of AI are, regardless of what Elon Musk says. That at the end of the day, we're talking about digital objects, not real objects, that are engineered, not, haven't evolved over a few billion years, to deliver certain outputs and data that's been tested and relatively well verified. As opposed to have an unlimited, at least from human experience standpoint, potential set of outcomes. So in that small world and certainly the infrastructure universe is part of that and what we're saying is increasingly the application development universe is going to be part of that as part of the digital business transformation. I think it's fair to say that we're going to start seeing AI machine learning and some of these other things being applied to that realm with some degree of success. But, something to watch for. All right, so let's do action item. David Floyer, why don't we start with you. Action item. >> In addressing this, I think that the keys in terms of business focus is first of all mobiles, you have to design things for mobile. So any use of any particular platform or particular set of tools has to lead to mobile being first. And the mobiles are changing rapidly with the amount of data that's being generated on the mobile itself, around the mobile. So that's the first point I would make from a business perspective. And the second is that from a business perspective, one of the key things is that you can reduce cost. Automation must be a key element of this and therefore designing things that will take out tasks and remove tasks, make things more efficient, is going to be an incredibly important part of this. >> And reduce errors. >> And reduce errors, absolutely. Probably most important is reduce errors. Is to take those out of the of the chain and where you can speed things up by removing human intervention and human tasks and raising what humans are doing to a higher level. >> Other things. George Gilbert, action item. >> Okay, so. Really quickly on David's point that we have many more application forms and expressions that we have to present like mobile first. And going back to using RPA as an example. The UiPath product that we've been working with, the core of its capability is to be able to identify specific UI elements in a very complex presentation, whether it's on a web browser or whether it's on a native app on your desktop or whether it's mobile. I don't know how complete they are on mobile because I'm not sure if they did that first but that core capability to identify in a complex, essentially collection and hierarchy of UI elements, that's what makes it powerful. Now on the AI part, I don't think it's as easy as pointing it at one app and then another and say go make them talk. It's more like helping you on the parts where they might be a little ambiguous, like if pieces move around from release to release, things like that. So my action item is say start prototyping with the RPA tools because that's probably, they're probably robust enough to start integrating your enterprise apps. And the only big new wrinkle that's come out in the last several weeks that is now in everyone's consciousness is the MuleSoft acquisition by Salesforce because that's going back to the EAI model. And we will see more app to app integration at the cloud level that's now possible. >> Neil Raden, action item. >> Well, you know, Mark Twain said, there's only two kinds of people in the world. The kind who think there are only two kinds of people in the world and the ones who know better. I'm going to deviate from that a little and say that there's really two kinds of software developers in the world. They're the true computer scientists who want to write great code. It's elegant, it's maintainable, it adheres to all the rules, it's creative. And then there's an army of people who are just trying to get something done. So the boss comes to you and says we've got to get a new website up apologizing for selling the data of 50 million of our customers and you need to do it in three days. Now, those are the kind of people who need access to things that can be reused. And I think there's a huge market for that, as well as all these other software development robots so to speak. >> Jim Kobielus, action item. >> Yeah, for simplifying web application development, I think that developers need to distinguish between back-end and front-end framework. There's a lot of convergence around the back-end framework. Specifically Node.js. So you can basically decouple the decision in terms of front-end frameworks from that and you need to write upfront. Make sure that you have a back-end that supports many front ends because there are many front ends in the world. Secondly, the front ends themselves seem to be moving towards React and Angular and Vue as being the predominant ones. You'll find more programmers who are familiar with those. And then thirdly, as you move towards consolidation on to fewer frameworks on the front-end, move towards low-code tools that allow you just with the push of a button, you know visual development, being able to deploy the built out UI to a full range of mobile devices and web applications. And to close my action item... I'll second what David said. Move toward a mobile first development approach for web applications with a focus on progressive web applications that can run on mobiles and others. Where they give a mobile experience. With intermittent connectivity, with push notifications, with a real-time in memory fast experience. Move towards a mobile first development paradigm for all of your your browser facing applications and that really is the simplification strategy you can and should pursue right now on the development side because web apps are so important, you need a strategy. >> Yeah, so mobile irrespective of the... irrespective of the underlying biology or what have you of the user. All right, so here's our action item. Our view on digital business is that a digital business uses data differently than a normal business. And a digital business transformation ultimately is about how do we increase our visibility into our data assets and find new ways of creating new types of value so that we can better compete in markets. Now, that includes data but it also includes application elements, which also are data. And we think increasingly enterprises must take a more planful and purposeful approach to identifying new ways of deriving additional streams of value out of application assets, especially web application assets. Now, this is a dream that's been put forward for a number of years and sometimes it's work better than others. But in today's world we see a number of technologies emerging that are likely, at least in this more constrained world, to present a significant new set of avenues for creating new types of digital value. Specifically tools like RPA, remote process automation, that are looking at the outcomes of an application and allow programmers use a by example approach to start identifying what are the UI elements, what those UI elements do, how they could be combined, so that they can be composed into new things and thereby provide a new application approach, a new application integration approach which is not at the data and not at the code but more at the work that a human being would naturally do. These allow for greater scale and greater automation and a number of other benefits. The reality though is that you also have to be very cognizant as you do this, even though you can find these, find these assets, find a new derivative form and apply them very quickly to new potential business opportunities that you have to know what's happening at the back-end as well. Whether it's how you go about creating the assets, with some of the front-end tooling, and being very cognizant of which front ends are going to be better or not better or better able at creating these more reusable assets. Or whether you're talking about still how relatively mundane things like how a database serialized has access to data and will fall over because you've created an automated front-end that's just throwing a lot of transactions at it. The reality is there's always going to be complexity. We're not going to see all the problems being solved but some of the new tools allow us to focus more attention on where the real business value is created by apps, find ways to reuse that, and apply it, and bring it into a digital business transformation approach. All right. Once again. George Gilbert, David Floyer, here in the studio. Neil Raden, Jim Kobielus, remote. You've been watching Wikibon Action Item. Until next time, thanks for joining us. (electronic music)