>>from our studios in the heart of Silicon Valley. Palo ALTO, California It is a cute conversation. >>Hi, and welcome to the Cube studios for another cube conversation where we go in depth with thought leaders driving innovation across the technology industry. I'm your host, Peter Boris. Digital businesses affecting every enterprise of every size, small and large, and the types of solutions that required the types of outcomes that are being pursued are extremely complex and require an enormous amount of work from some of the best and brightest people on the business side as well as the technology side. And that means not just from a large company. It means from an entire ecosystem of potential sources of genius and insight and good hard work. So the consequence for every enterprises, how do they cobble together that collection of experts and capabilities that are gonna help them transform their business more successfully, Maur completely and more certainly than they would otherwise? And that's we're gonna talk about today. Today we're here with Kelly Ireland, who's the founder and C E o. C. B Technologies. Kelly. Welcome to the >>Cube. Thank you, Peter. Happy to be here, >>so let's start by finding a little bit about CV Technologies to also about what you do. >>Um, I have a IittIe background, so I have been in it for 40 years. In 2001 I decided I had a better idea of how to both support clients as well as my employees. So I opened CB Technologies were value added reseller, um, and then say about five years ago, I decided to do some transforming of the company itself. I saw what was going on in the industry, and I thought this was the time for us to get going. Turned out we were a little early, but we wanted to transform from what you would call it the value added reseller two systems integrator. Because that was the only words what they had for. You know what that end result would be? Now I've heard it's the, um, domain expert integrator, which we like a lot better. And what we've done is gone from this value add, which we've all seen over the last couple of decades, into actually engineering solutions, and mostly with consortiums, which will talk about of the O. T. I t. Convergence and what's going to be needed for that to make our customers successful. >>Well, you just described. In many respects, the vision that businesses have had and how it's changed over years were first. The asset was the hardware. Hence the var. Today, the asset really is the date of the application and how you're going to apply that to change the way your business operates the customer experiences, you provide the profitability that you're able to return back to shareholders. So let's dig into this because that notion of data that notion of digital transformation is especially important in a number of different names, perhaps no more important than in the whole industrial and end of things domain. That intersection of I t know Tia's, you said, Tell us a little bit about what you're experiencing with your customers as they try to think about new ways of applying technology technology rich data to their business challenges. >>We'll use the perfect word you said dig, because this is all about layers. It's all about it was technology and software. Now it's about technology, software and integration. In fact, the conversations were having with our clients. Right now we don't even talk about a no Yim's name. Where before you would. But we haven't our head. What? We know what would be best. What we look at now is the first thing you do is go in and sit down with the client. And not only with the client, the you know, the executives or the C I or the C T. O's et cetera, but the employees themselves. Because what we've seen with I I I o t o t i t Convergence, it's You have to take into account what the worker needs and the people that are addressing it that way. Um, this project that we started with Hewlett Packard Enterprise, they started up what we call the refinery of the future. It could be acts of the future. It doesn't really matter. But it was getting at least up to five use cases with a consortium of partner companies that could go address five different things within the refinery. And the reason that I think it's been so successful is that the owner, the CEO Doug Smith and the VP of ops Linda Salinas, immediately wrap their arms around bringing employees. They're a small company there, maybe 50. They brought half of them to HPD Lab to show them what a smart pump laws for their chemical plant text. More chemical in Galina Park in Texas. Starting from that, it was like they put him on a party bus, took them down, put them in the lab, told them, showed them what a smart pump was and all of a sudden the lights turned on for the workers. These are people that have been, you know, manual valves and turning knobs and, you know, looking at computer screens they'd never seen what a smart, censored pump waas all of it sudden on the drive back to the company, ideas started turning. And then HP took it from there, brought in partners, sat everybody in the room, and we started feathering out. Okay, what's needed. But let's start with what the client needs. What do those different business users within the chemical plant need, and then build use cases from that? So we ended up building five use cases. >>Well, so what? Get another five years cases in a second? But you just described something very interesting, and I think it's something that partners have historically been able to do somewhat uniquely on that is that the customer journey is not taken by just an individual within the business. What really happens is someone has an idea. They find someone, often a partner, that can help them develop that idea. And then they go off and they recruit others within their business and a local partner that has good domain expertise at the time. And energy and customer commitment could be an absolutely essential feature of building the consensus within the organization to really accelerate that customer journey. If I got that right? >>Absolutely, absolutely. And what we saw with Refinery of the Future was getting those partnerships HP East started. It created the project kind of through information out to many of their ecosystem partners trying to gain interest because the thing was is this was kind of our bet was a very educated bet, but it's our bet to say, Yeah, we think this makes sense. So, you know, like I said, I think there's about 14 partners that all joined in both on the I t om side the ot oh am side and then both Deloitte and CB Technologies for the S. I and like expert domain expert integration where you really get into How do you tie OT and I t together? >>All right, so we've got this situation where this is not As you said, It's not just in the refining process, manufacturing businesses. It's in a lot of business. But in this particular one, you guys have actually fashioned what you call the refinery of of the future has got five clear use cases. Just give us an example of what those look like and how you've been RCB technology has been participated in the process of putting those together. >>Um, the 1st 1 was pretty wrapped around Predictive Analytics, and that was led by Deloitte and has a whole host of OT and I t integration on it >>again, not limited to process manufacturing at all >>at all, but and a good group, you know, you have national instruments, Intel flow. Serve. Oh, it's ice off Snyder Electric, PTC riel, where they're such a host >>of the >>consortium and I I think what was most important to start this whole thing was H P E. Came in and said, Here's an MOU. Here's a contract. You all will be contract ID to the overall resorts results. Not just your use case. Not just one or two use cases you're in, but all five because they all can integrate in some sense so >>that all can help. Each of you can help the others think. Problems. Truce. That's the 1st 1 about the 2nd 1 >>The 2nd 1 is video is a sensor that was Intel CB Technologies. I think we have as you're in there as well, doing some of the analytics, some P T. C. And what that was all about was taking video. And, you know, taking a use case from Linda and saying, Where where do you need some sort of video analytics Taking that processing it and what we ended up doing with that one was being able to identify, you know, animals or aggressive animals within the train yard. A downed worker transients that shouldn't be there because we can't decipher between you know, someone that's in text marks p p ease versus somebody that's in street clothes. So taking all that analyzing the information, the pictures, training it to understand when it needs to throw and alert >>lot of data required for that. And that's one of the major major drivers of some of the new storage technologies out there. New fabrics that are out there. How did that play? A role? >>As you can imagine, H p E is the under underlying infrastructure across the entire refinery. The future from compute with the, uh, EJ data center into the Reuben network into nimble storage for storing on site. Um, what we're finding, no matter who we talked to in the industry, it is. Most of them still want to keep it on Prem. In some sense, security. They're still all extremely cautious. So they want to keep it on Prem. So having the nimble storage right in the date, having the edge data center having everything in the middle of this chemical plant was absolutely a necessity. And having all of that set up having my team, which was the C B Tech team that actually did all the integration of setting up the wireless network, because guess what? When you're in a different kind of environment, not inside a building, you're out where there's metal pumps. There's restrictions because ah, flash could cause an explosion so intrinsically safe we had to set up all that and determined how? How could we get the best coverage? Especially? We want that video signal to move quite fast over the WiFi. How do we get all that set up? So it takes the most advantage of, you know, the facility and the capabilities of the Aruban network. >>So that's 12345 quickly were >>three worker safety, which hasn't started yet. We're still waiting for one of the manufacturers to get the certification they need. Um, four we have is connected worker, which is on fire, having a work >>of connected worker on fire and worker >>safety. >>Yeah, they don't sound, but just think of all the data and having the worker have it right at his fingertips. And, oh, by the way, hands free. So they're being ableto to take in all this data and transmit data, whether it's by voice or on screen back >>from a worker central perspective, from one that sustains the context of where the worker is, what stress there under what else? They've got to do it said. >>And and what are they trying to complete and how quickly? And that's where right now we have r A y that's in the 90% which is off the chart. But it's and and what's great about being at Text Mark is we actually can prove this. I can have somebody walk with me, a client that wants to look at it. They can go walk the process with me, and they will immediately see that we reduce the time by 90%. >>So I've given your four. What's the 5th 1? >>Acid intelligence, which is all about three D Point Cloud three D visualization. Actually being able to pull up a smart pump. You know it really? Any pump, you scan the facility you converted into three D and then in the program that we're using, you can actually pull up a pump. You can rotate it 360 degrees. It's got a database behind it that has every single bit of asset information connected videos, cad cams, P and I. D s. For the oil and gas industry. Everything's in their e mails could be attached to it, and then you can also put compliance reports. So there you might need to look a corrosion. One of those tests that they do on a you know, annual or every five year basis. That's point and click. You pull it up and it tells you where it sits, and then it also shows you green, yellow, red. Anything in red is immediate, attest that tension yellow is you need to address it greens. Everything's 100% running. >>So the complexity that we're talking about, the kind of specificity of these solutions, even though they can be generalized. And you know, you talked about analytics all the way out to asset optimization Intel intelligence. There are We can generalize and structure, but there's always going to be, it seems to us there's going to be a degree of specificity that's required, and that means we're not gonna talk about package software that does this kind of stuff. We're talking about sitting down with a customer with a team of experts from a lot of different places and working together and applying that to achieve customer outcome. So I got that right >>absolutely, and what we did with the consortium looking at everything. How they first addressed it was right along that line, and if you look at software development, agile following agile process, it's exactly what we're doing in four I I o T o R O T I t Convergence, because if you don't include all of those people, it's never going to be successful. I heard it a conference the other day that said, POC is goto I ot to die, and it's because a lot of people aren't addressing it the right way. We do something called Innovation Delivery as a service, which is basically a four day, 3 to 4 day boot camp. You get all the right people in, in in the room. You pull in everything from them. You boot out the executive team partway through, and you really get in depth with workers and you have them say what they wouldn't say in front of their bosses that this happened with Doug and Linda and Linda said it was mind blowing. She goes. I didn't realize we had so many problems because she came back in the room and there was a 1,000,000 stickies. And then she said, the more she read it and the more you know, we refined it down, she said it was absolutely delivered, you know, the use case that she would have eventually ended up with, but loved having all the insights from, >>well, work. Too often, tech companies failed to recognize that there's a difference between inventing something and innovation. Inventing is that engineering act of taking what you know about physics or social circumstance Secreting hardware software innovation is a set of social acts that get the customer to adopt it, get a marketplace to adopt it, change their behaviors. And partners historically have been absolutely essential to driving that innovation, to getting customers to actually change the way to do things and embed solutions in their operations. And increasingly, because of that deep knowledge with customers are trying to doing, they're participating. Maurine, the actual invention process, especially on the softer side of you said, >>Yeah, yeah, I think what's really interesting in this, especially with Coyote. When I look back a few years, I look at cloud and you know everything was cloud and everybody ran to it and everybody jumped in with both feet, and then they got burned. And what we're seeing with this whole thing with I o t you would think we're showing these are lies, return on. Investments were showing all this greatness that can come out of it and and they're very slow at sticking their toe in. But what we've found is no one arrives should say the majority of corporations anymore don't want to jump in and say, Let's do it two or five or $10 million project. We see your power point. No, let's let's depart Owen with with what we're doing, it's, you know, a really small amount of money to go in and really direct our attention at exactly what their problem is. It's not off the shelf. It's but it's off the shelf with customization. It's like we've already delivered on connected worker for oil and gas. But now we're are so starting to deliver multiple other industries because they actually walk through text mark. We could do tours, that text mark. That was kind of the trade off. All these partners brought technology and, you know, brought their intelligence and spent. We were now on two years of proving all this out. Well, they said, Fine, open the kimono will let your customers walk through and see it >>makes text mark look like a better suppliers. >>Well, it's enhanced their business greatly. I can tell you they're just starting a new process in another week. And it was all based on people going through, you know, a client that went through and went. Wait >>a minute. I >>really like this. There are also being able to recruit technologists within the use in industry, which you would think text marks 50 employees. It's a small little plant. It's very specialized. It's very small. They pulled one of the top. Uh, sorry. Lost not. I'm trying to think of what the name >>they're. They're a small number of employees, but the process manufacturing typically has huge assets. And any way you look at it, we're talking about major investments, major monies that require deep expertise. And my guess is the text Mark is able to use that to bring an even smarter and better >>people smarter and better. People that are looking at it going they're ahead of the curve, for they're so far ahead of the curve that they want to be on board were that they're bringing in millennials on they're connected. Worker Carlos is there trainload lead. And he dropped an intrinsically safe camera and it broke and he tried to glue it together, tried to super glue it together. And then he ran back to Linda and he said I broke the case and this case is like £10. They call it the Brick. They gotta lug it up. They got to climb up the train car, leg it up, take a picture that they have sealed the valves on all the cars before they leave. Well, he had used the real where had, you know, device. And he went into Linda and he said, I know there's a camera in there. There's camera capabilities. Can I use that until we get another case? And she's like, Yeah, go ahead. Well, he went through, started using that toe like lean over, say, Take photo. We engineered that it could go directly back to the audit file so that everybody knew the minute that picture was taken, it went back into the audio file. This is where we found the process was reduced by 90% of time. But he turned around and trained his entire team. He wasn't asked to, but he thought, this is the greatest thing. He went in trainable. And now, about every two weeks, Carlos walks in to my team that sits a text mark and comes up with another use case for connected worker. It's amazing. It's amazing what you know were developed right out of the customer by using their workers and then, you know, proactively coming to us going. Hey, I got another idea. Let's add this where I think at version 7.0, for connected worker. Because of that feedback because of that live feed back in production. >>Great story, Kelly. So, once again, Callie Ireland is a co founder and CEO of CB Technologies. Thanks for being on the tube. >>Thank you for having me >>on once again. I wanna thank all of you for joining us for another cute conversation. I'm Peter burgers. See you next time.

why from Las Vegas it's the cube covering implementing a world 2018 machito by informatica okay welcome back everyone's the cube live here in Las Vegas at the Venetian ballroom is the cubes exclusive coverage of informatica world 2018 I'm John for your host in analyst here with Peter Baris host and analyst here for two days of coverage our next two guests are jitesh guy who's the senior vice president general manager data quality security and governance for informatica and barry green the chief data officer for bank of ireland great to see you attached great to have you on the cube and great to be here so love having two to smart people talking about data GPRS right around the corner and friday you're at the bank of ireland so in the middle of it while you're in you're in this in the territory you're in the heart get any sleep what talk about your role at the bank what are you guys doing I want to get into the GDP RS right on our doorstep it's going to major implications for data as a strategic asset talk about what you do so for me we've created a daily management framework frameworks pretty simple map process get context for data put it into the business data model or sign ownership put data quality over it and then maintain it using a risk model operational risk model now it doesn't matter with GDP our or becbs whatever it is it's about adding value to data understanding day they're using it for them and making sure you've got better customer experience all the good things you know GDP are is important but it's not the only thing you guys are new to managing data and certainly complies your financials bank so it's not a new thing what is how is GDP are being rolled out how is it impacting you guys what are you paying attention to what's the impact so the big thing about GDP are is we're having to understand where our key customer data's sits in the physical systems we're looking at mapping key processes something to see and what it's used for we're assigning ownership to people who own data so we can basically make decisions about it in the future GDP ours a bit like becbs that's going to evolve right you're not going to be GDP are compliant on May 25th you're gonna have to put in place the infrastructure the tooling the governance the management to make sure that as an organization you know you were using data the way it's supposed to be if you want to be a digital organization you have to manage data this is just pushing along they had evolution of data being important to an organization but just as y2k wasn't about making the world safe for mainframes in the year 2000 it forced a separation and understanding of the separation that's required between applications and data so gdpr is another one of those events it's forcing a separation in this case between data and the notion of data assets great so take us through how the thought process of gdpr has catalyzed new thinking within the bank about how we think about data differently as a consequence I think what it's done so we've developed the framework so we can apply it to any problem right I think what it's done is it's raised up data's the risk of data more generally so people talk about data as an asset I've talked about data as a liability right so it's a contingent liability if you think about gdpr it's raise that awareness up that we can't continue to operate and tricked out of the way we have in the past so there's a whole cultural change going on around how we treat data and there's a big understanding training going on about everyone knowing why they use data making sure that they don't use it for the purpose it's not used for and generally it's a big education cultural change very how would you describe the mindset for this new thinking it certainly I agree with you it's at the strategic nature center the center of the center of the value proposition right now on all aspects not just some department what's the mindset that people should be thinking about when they think of data okay should I have access to this data but do I need it for the role I'm undertaking and if it was my data would I be treating it you know how would I shred it how would I want it to be treated even if you're the subject yeah exactly it's almost like you know if I had my data being used for certain thing context is that the way I'd want my data treated there's almost in the old adage you know do unto others as you would have you done to you yeah ethics is important yeah to church talk about the informatics opportunity because you guys really timings pretty awesome for informatica with the catalog you guys have an interesting opportunity right now to come in and do a lot of good things for clients that's that's exactly right we've we've been working very hard with our clients over the last 18 months to help them on this gdpr journey what we you know think of as supporting their privacy and protection and and you mentioned catalog you know our we have our enterprise data catalog powered by Claire our AI machine learning capabilities and metadata and that helps you get an organized view of all your data assets within the enterprise leveraging that same technology we have a security source offering which is effectively a data subject catalog to help our customers understand where exactly is the data subject sensitive data not where the organization's data is but the data subject sensitive data within the organization where their national identifiers information is how where their personal home address email phone etc is and how many occurrences and what systems why so that our customers can take that information and more effectively respond to the data subject if the data subject wants to invoke you know the right to be forgotten or right for data portability etc as well as take that same information and demonstrate to the regulator that they are processing this sensitive data with the appropriate with the appropriate consent from the data subject as well as have the systems I presume to then be able to expose to the subject the reasons why the data may in fact still be part of the asset of the bank correct so I I hadn't heard that before we've had other company cells that they're going to help companies find subject data but you guys are taping us taking a step further and allowing the bank for in this case do we have to look at that data from the subjects perspective exactly right because it's not just with some regulations financial regulations you need to demonstrate the quality and trustworthiness of the data here at to the regulator here it's demonstrating to the data subject themselves the individual themselves how you're processing how you're treating their data how protected or unprotected it is and and how you're using it to market to them how you using to become part of the metadata that's exactly right it's using the same metadata foundation too but focused on the data subject specifically interesting interpret ection aspect of it if I say I want my right to be forgotten and you can hold data for something mean where's the where's the protection aspect for the business and the user is there conflict there how do you guys handle that yes that's interesting there is a conflict so there's a conflict already with an existing regulation so you know um the thing that a lot of people aren't talking about is you can hold data so if someone can't just delete data if you want to hold an account or you know these reasons for using it you got a legitimate use for using it you can still hold it you have to tell a customer why you're using it so there's a lot of context here which they didn't have before so it's giving the customer the power to understand what the data is being used for the context is being used for and so they know it's not gonna be used for sort of spiritless marketing campaigns it's being used for you know the reason that does that extra work for you guys is that automated this is where we start to get into the question next yeah which is a context the context is the metadata and you're going to be able to capture that context explicitly as these data elements have this context in metadata allows you to do that with some degree of certainty and you know relatively low cost I assume it's all about reuse right so a lot of what we've done in the past and on its way at the bank um to me everyone's done in the past is they've understood something and then thrown it away so with Exxon you can record it you know record it then with the metadata you can join the metadata in Exxon so you can do in a high level process understand what data is used at the context is used for who owns that quality all these kind of business relevant things then you put the metadata out and you've got a system view it's very very powerful so the technology is starting to allow us to automate but it's all about gathering it reusing it and making sure you understand it right that's for you know from a from a data subject catalog standpoint you get the technical metadata it tells you across your data landscape where all the sensitive information is for Barry green you marry that up with the business metadata of how is that sensitive information being used in every step of let's say customer onboarding your mission critical business processes within the organization and that's what you demonstrate to a data subject or a regulator if this is how I'm processing it based on this consent now if they invoke the right to be forgotten there's various things you can do there because there's conflicts you can just mask the data using our masking capabilities and then it's true forgotten or you can archive the data and remove it from a particular business process that is marketing or selling to them if that's so yeah choice is it some flexibility correct or or slight maybe slightly differently Mystere forgot that's right you can get work out of that data in an appropriate way so the customer can be forgotten so that this this kind of work now that you cannot apply that data to marketing whatever else it might be for when it comes to understanding better products or building better products whatever else through masking you can apply the data still to that work because it's a legitimate use under the law exactly also think about the fact you've mask key critical data right so the thing about data privacy in general was you know if you can't understand a data subject so if you can hide certain pieces of data and you can't identify them you didn't aggregate it you can it's not personal data anymore so you know there's this some real nuance there's a lot of people aren't talking about these things but these new icers will be surfaced yeah yeah because certainly it's a it's the beginning of a generational shift there gonna be some pain points coming online I mean we're hearing some people complaining here and there you guys are you know used to this some industries are like used to dealing with Brad you know compliance like no big deal some people are fast and loose with their data like wait a minute I said you can't be a digital wanker we can't be a head of digital propositions you don't understand your data you know you and you don't understand it and manage it so this is an opportunity to do this across the enterprise it exposes companies that have not planned for an architected data whether that's investment in data engineering or have staff this is a huge issue and pools and tools that can't support that process I mean if you got a I mean people are looking in their organization going oh man we've really don't have it or they're ready the exciting part is you know organizations have focused on quality and trustworthiness of their data we're now taking that same data and focusing on the privacy and protection and the ethical treatment of it and leveraging the appropriate technologies which happen to be very similar fundamentally for quality and Trust and privacy and protection and and in the absence of a global standard for GDP our we're we're seeing organizations without GDP our as a de facto standard in fact Facebook just announced that they're treating all users data you know that was one of our research predict yes yeah very obvious I mean we'll see how eleven have any teeth or anything but you know Facebook's got their own challenge but it's an opportunity for a clean sheet of paper Friday May 27 I'm sure there's gonna be a ton of class-action lawsuits against Facebook jitesh Barry thanks for coming on great to see you thanks for everything in Ireland we're here on the open and informatica world right and written the solutions expose the cue bringing you all the data right here in the catalog you got the cube dotnet check it out I'm people John free with Peterborough's stay with us for more day to coverage at different Matic world after this short break