>> Narrator: Live from Washington, D.C., it's theCUBE covering Boomi World 19. Brought to you by Boomi. >> Welcome back, everyone, we are here live at Boomi World 2019. It's theCUBE's coverage here for two days. I'm John Furrier, your host, with Lisa Martin who stepped away, she'll be back. Les Rechan, President and CEO of Solace, is back on theCUBE. Cube alumni was with us in 2013. Les, welcome back to theCUBE, good to see you. You know we're on our 10th year of theCUBE, so it's 10 years we've been in business. You're early on with us, thanks for coming back. >> Thank you for having me. >> So you're an entrepreneur, you're on board, you're doing some investing. You see many ways of innovation. We are in one now that's really got a lot of waves coming together, convergence of multiple things happening. You're in the middle of it as the CEO. What's going on, what's your view? What's happened in the marketplace and what're you doing? >> Oh, I think, I agree this is early days. We've got this, everything's transforming, customers are re-imagining their businesses to be innovators, to move the world forward. And along with that, to enable it, we're dealing with a whole new IT infrastructure: hybrid cloud, multicloud, distributed microservices, IoT, real-time, so it's early days of that, and so we're in the business of helping those innovators move the world forward with smart data movements, so we're very excited about it. >> I want to get into your company that you're leading now and some other endeavors you're onto, but I want to get your take on how you see the market and how you talk to customers and friends and people in the industry. What's the biggest story going on in your mind right now? What's the top-line, high-order bit, trend or element or enabler, disruptive enabler. That's really powering the industry right now that's changing it for the better and creating opportunities. What's the big story in your mind? >> Well, time and data are the currency, and when you think about dealing with customers, you're listening to them, you're personalizing your engaging, and this is all about what I would call the event-driven customer journey experience. Business is a series of events. You want to get those events moving and flowing and really, when you think about it, that can be competitively advantaged for your business. >> You know it's interesting we had the folks on from Boomi here. I use the bloodstream as an example, but data movement is how the business we're in. We live in a digital world and it's combining. It's not mutually exclusive with the analog world. And you have, now, the coming together of a digitized society where things are instrumentable. You can actually get the data. And then you got to know what to look for. So, now, the challenge is with data become a big... This is a big, hard problem people try to crack the code on. Is there a formula in your mind to be truly data-driven or data-enabled or data-fed, leveraging the data? Do you see a playbook that companies can adopt to do that? >> Yeah, I think that companies are sitting on top of a lot of data. The key is to liberate it, to get it moving, but within your enterprise and then out to your partners and the customer world, so I think that you really want to just take advantage of it, you want to move it to where it needs to be, you want to augment the intelligence of the people within the enterprise and your customer set, so I talk about an event mesh, we call it. An event mesh enables the intelligent enterprise to deliver value. >> It's a nice concept, it's like connective tissue, or glue layers as a tech term-- >> Les: Digital river, central nervous system, whatever you want to call it. >> Great stuff, talk about the market you're going after. What's the market you're targeting? What's the size of it? What are you going after, what's the territory you guys are trying to take down? >> So, traditionally, we came out of what used to be called messaging-oriented middleware. So we're a messaging system. Now the term would be we're an advanced event broker. This thing used to be a couple-billion-dollar market now when you think about this hybrid multicloud, IoT. This thing has probably exploded by a factor of 10 or more. >> It's interesting RPA seems to be taking hot evaluations these days. Is that the same kind of thing, RPA and automation? They seemed like-- >> I think RPA, when you think about hybrid integration, you've got API management, you've got what Boomi does, the iPaaS, we're the advanced event broker, so we're talking about moving these events around. It could be request/reply, it could be pub/sub, async, synchronous, all these different patterns for all these different use cases that are out there, but that's really what we do as opposed to RPA. >> Got it, what's your business model? What's the business look like? How big is the company? Is it a cloud service? How do you make money? What are some of the details there? >> Well, we're a private company. We're growing very rapidly. We're about 300 people, it's a global enterprise. We're doing great things all over the world. We're enabling Digital India, for example, with companies like Airtel and Reliance, so instead of taking 30 minutes to do a mobile phone recharge, we do it in seconds. In Singapore, we're working with smart transportation, land transport, next-generation payments, 1.4 million connected cars and buses, getting that data flowing to optimize traffic, is another example. Safety-critical data in and out of the airplane which is a huge amount of events. Equities, transactions, we process 85% of the equities, transactions in Canada and the list goes on. We came out of capital markets. Now we're into these other industries 'cause everything's moving to this real-time, real-time sensitive type environment. >> And the intelligence of software. Is that the business model: you make money selling software? What is the--? >> Yeah, that's a great question. We've got multiple deployment models. We've got a hardware appliance, we've got software, we've got cloud. We are for subscriptions or operating expense or capital expense. This thing is a platform, so you've got the broker itself, you've got integration connectors, you've got the governance layers on top monitoring capability, so it's a solution set. We're very flexible and adaptable to the customer's business model in terms of subscriptions or cap packs, whatever you want. >> So you keep it flexible. >> Les: It's very flexible. >> Because, if you're running an IoT, running traffic lights, for instance, or doing some smart cities thing, then it's got to go over to another use case. They're different. >> Yes, we talk about being dynamic, open, and simple. Dynamic in terms of the agility of different types of use cases with one solution, open meaning running everywhere, and simple meaning easy to deploy and manage. >> Yeah, machine learning and data is going to be a nice substrate layer to innovate on, so awesome business model. Let's talk about the technology and the secret sauce. What's going on there? Explain the magic, what's going on with the tech product? >> The secret, this is all we do. Smart data movement is all we do. And we're the only company out there that's really-- >> John: What's smart data movement mean? Define that term. >> Smart data movement would be, I've got to get something from point A to point B. I want it to get there in a guaranteed, persistent way. That's kind of what we do as opposed to taking that payload and transforming it, so we're just moving the data around. We're making sure that it gets there, that you can recover it, et cetera, so that's what we do. >> We heard this on theCUBE this morning: "Apps come and go, but data always remains." And so this has been the theme. What's different with you guys in terms of differentiation? Because I've seen service brokers, they've come and gone. Service brokers are everywhere. It's a key part of a system architecture. You're dealing with solutions that have to think like a system. And systems have consequences. You got to think holistically, so what is your differentiation? What's the role of the broker? Just take us through that value proposition and what's differentiated. >> Yeah, I think the differentiation here is we're a platform. The dynamism and the agility is definitely unique in that we can do WAN optimization really well, we can deal with different use case patterns, so the dynamism and the agility, we can do ultra-low latency, we can do high volume, we can do general purpose across the same platform. The other point of differentiation would be openness, so we're open protocol. We support, whether it's AMQP, whether it's MQTT, we're an open system, and we support openness across all the hyperscalar platforms, across the passes. So dynamic, open, and then simple in terms of it being a single solution set, be it hardware, be it software, be it cloud, and successful. Our customers are very successful. The use cases that we support are compelling. We helped innovators move the world forward, so I'd say it's dynamic, open, simple, and successful. >> Who's the target audience: developers, C-suite? 'Cause you got to code this stuff. Those are two primary target audiences. >> Yeah, I think it's, really, it's both. It's business-driven, IT-enabled, so we tend to work with the architects, the CIO's, the middleware teams on one hand to support this reinvention of your business. On the other hand, when you think about transforming the business and doing something different and innovating, it's got to be business-driven. So here we are at Boomi World. The theme is Accelerated Outcomes, which is key. So it's really driving an outcome, but IT-enabled, so you got to support both sides. >> All right, you got a large growing market, you got a good business model, you got some secret sauce. Now, final segment, so customers, customers and societal benefits because, look, there's a tech for good angle in here, but also, there's a big wave of tech for bad, so all I hear in the news is: tech's evil, this is bad stuff, oh my god. So you got real customers, where's the benefits? Take us through some of the success stories and the opportunities for a tech-for-good component here 'cause I can see the benefits, it's on infrastructure side: deploying new capabilities, compelling, but benefits to society are super important too. >> Yeah, I would say just one example would be Digital India as an example where you're saying you've got hundreds of millions of people who really need to access different capabilities, different services with smartphones. You need to deal with huge volumes. Let's give them that access, let's make it quick, so enabling Digital India is one example of really doing something that helps, helps people live better, reduces their time doing things that they maybe would've taken a long time before. Another example would be Singapore, smart cities. If you can move the traffic flows around better, you've got a population that's increased by a million people in the last several years, that's another example, making payments faster, whatever the case may be. >> So I know you got a hard stop, you got to meet the CEO of Boomi, Chris McNabb, great guy, among theCUBE yesterday, Cube alumni as well. Final question for you is: is there any requirements that need to be in place to work with you guys? 'Cause I would say it's a huge task. Are there dependencies? Are there certain signs that customers need? When does someone know to deploy? I would say, if someone say, hey, I want to modernize my X, what's the tell sign for you guys to know where there's alignment with a project or customer? >> Yeah, I would say that it's a real-time sensitivity. Ideally, it's one where I want scalability. It's one where I want security. I want to be able to get the data to where it needs to be in a guaranteed way, and, at the same time, I want to do it in an affordable way. I want to have one platform for different use cases so that's what I would say around that. >> Les, thanks for taking the time to come on, share your insights in real time here on theCUBE. One final, final question, 'cause I look at the final, final question. You've seen a lot of waves, you've been in a lot of experiences, you've run companies, you're on a lot of boards. A lot of young people coming into the marketplace. I sometimes go on my rant: get off my lawn. Your kids don't know how good you had it. It's a great time to be young and the rescaling going on is an all-time high. What's your advice to the young, upwardly mobile tech, soon-to-be-tech, totally tech-savvy, future employees of the world? Because there's a lot of hard projects to tackle. Tons of jobs: cybersecurity, what you're doing. Do they know how good they have it and what's the advice that you would give people watching here, knowing how robust this environment is? >> Oh, I think it's a great environment and you're right. I think it's all about: people matter most and winning with talents, so the talent supply chain is a big issue. And one is: every day is a learning day. Make it a learn-it-all, keep learning every day 'cause this business is moving very quickly. At the same time, being a good team member, I would say, being compassionate, being empathetic to your teammates, and really using that to your advantage, is huge. It's one thing to have the domain skills, but it's also another thing to have those human skills that really make a difference. >> That's the team sport. It takes a village these days, stack is coming. Les, thanks for coming on. It's theCUBE coverage here in D.C. I'm John Furrier, thanks for watching, be right back. >> Thanks. (upbeat electronic music)

>>Okay. We're back live here at the cube in Las Vegas for IBM. Information on demand. I'm John furrier with Dave Volante a joined the crowd chat on crowd chat.net and we're here with less wretched than general manager of business analytics at IBM. Welcome to the cube. Thanks. I know you've got short time. And for the folks that are going about 10 minutes, we're going to just jump right into it. So obviously business analytics and social business, big data analytics and social business driving the market of the data economy. And under the hood you've got cloud and mobile apps and connected devices. So, so the number one thing that comes up is we need more data scientists and we've got to get the data in the hands of users. So, um, talk a little about your vision there and what's going on here around that rent concept. Yeah, I think it's key here as we talk about imagining the future and leveraging big data analytics, we talk about infusing a culture of analytics everywhere in the organization. >>So the key about that is to really create solutions that are fast, that are easier and that are frankly smarter throughout the organization. So how would, how does visualization play into that last one? If you could talk about that a little bit. Because as a business user, you know, you guys are describing the keynotes today, right? Somebody put up the spreadsheet like, ah, how can you make it easier for people to consume? Yeah, you want to have more rapid insight to action. This is all about whether it's predictive capabilities or we think about, you know, when you look at organizations today, you think about descriptive analytics, what's going on and then you diagnose it, why is it going on? You look at the future with predictive analytics and then even look at prescriptive analytics with things like looking at next best action and then even cognitive capabilities. >>What we really want to do here is make it a lot easier for users to not only visualize and explore, but to then see the patterns in the data to guide them. And what we're trying to do here is really change the whole analytic experience. How they make decisions, how information is presented in a much easier way. Let's talk about the difference in, in verticals. A lot of people have a conversations around business strategy and also the solutions they put out. We're horizontal, we're vertical. Something, a very vertical approach. Even at a technical level with the stack or organization, you guys have a play in all the verticals. Um, and the verticals have different outcome objectives yet. So that means different analytics. How do you guys deal with that? I mean it's an opportunity certainly, but I mean from a technology and then solutions standpoint. >>Yeah, I think a, the key here is we focus on number one, taking advantage of all data, whether it's structured or unstructured, whether it's in motion at rest. And then we want to deliver, as I mentioned previously, all analytic capability from descriptive all the way to cognitive and then all solutions. That's where you get then into the verticals. So telcos are looking at customer churn. Insurance companies are looking at broad banks are looking at risk. Public sector organizations are looking at reducing cycle time and then medical institutions really collaborative care, uh, with, with the patient. So what we try to do here is take that capability that we've got all data, all analytics, all solutions, then apply it, pinpoint it. So for example, predictive maintenance and quality for industrial sector customers. So what you see here is we've announced a solution that converges that capability again, makes it faster, it makes it easier, makes it smarter to deploy. >>I talked with this, uh, EVP CIO stat oil, and she told me that, you know, they had their data in a silo for the exploration side of the business, but when they opened up new data sets that had nothing to do with their business, like ocean data, right? It amazing, amazing transformation and improvements in their business. That's two different datasets. How do you guys enable customers to do that? One, do you, do you do that? And these verticals have to kind of go outside their kind of data competency? Yeah. Okay. Can you talk a little bit about that? So really here when you think about analytics and you think about social, mobile cloud, we're looking at systems of engagement, we're looking at presenting information to people on the frontline that could come from many heterogeneous data sources. So what we want to do is be able to bring that together. We have solutions that actually do that and then bring it together for that user, for that particular problem. >>Let's, what does your business look like? I mean, you're running this to the, the IBM analytics business analytics group. What's in the business analytics group? >>Yeah, it's a pretty big business. Um, I actually came into IBM from Cognos, so that was business intelligence. That was about six years ago. I was the col Cognos. So business intelligence is the first piece. Second piece is performance management capability. So this is financial performance management, sales performance management and disclosure management. And then you've got predictive analytics. So you get into statistics, you get into modeling, you get into, uh, kind of approaching some of the cognitive capabilities. And finally, risk management. This is financial market, credit risk, governance, risk compliance. So it's a pretty big business. We focus on customer related areas, operational areas, finance and risk. And then of course with our big data rather than we focused on this overall big data and analytics opportunity. It's a global business. It's a, something that's very important to IBM. And it's a, it's really, when you think about big data analytics, about 15 cents on every it, the >>dollar being spent. So you're there, the Cognos acquisition, I mean you could, you could argue with it one of two of the major acquisitions that IBM has. That's probably one of the two most important that and PWC, right? I mean it's really transformative. Did you, when you were at Cognos, did you ever imagine, could you even listen to the future as to what has become of this sort of big data meme? I mean it's always been sort of the vision 360 degree view of the customer and all that stuff, but the, just the amount of data, is that something that you guys actually envisioned and you're now seeing through? >>Yeah, no, I think we had, um, you know, it really is gotten to be much bigger than I would have ever dreamed of. You know, and this is the whole theme of this conference, right? It's think big, deliver big, wind big. At the same time we did have a view of where this thing would evolve to, we always talked about this whole all analytic capability and being able to present that to the user, being able to exploit the data that's out there in all the different shapes and forms. But it really has grown pervasively. We talk about, first of all imagining it, you know, you've got the four V's of big data, volume, variety, velocity, veracity, but we talk about having the vision and the value. That's the fifth and sixth really imagining the future, being able to realize it with a big data and analytics architecture and then frankly being able to trust it in terms of security, privacy and risk. >>Yeah, you guys have, Cognos was a nice exit. Was it 5 billion was the, who was the exit when an IBM purchased Cognos was most of that? It was a five, $5 billion firm from an IBM. Yeah. So, so you don't, do you think you undersold? No, no. But you know, the reality is is you, you, you, you never would have been able to see that vision through as an independent company. I mean the resources that you're required, whether it's the services, the hardware piece, the other big data analytics pieces would have been very hard for an independent company. I think to compete with that. We were talking earlier about the little different parts of the big data ecosystem. You know, you got a little doop specialists, you know, you got guys who have tried to, you know, remain independent, still doing okay. But yeah, IBM's got a lot of capabilities there. You've mentioned in your keynote project Neo, what is, what is project Neo? >>Yeah. Neo is our next generation data discovery capability. And again, in the spirit of being faster, easier, smarter, what we're trying to do is make this visualization capability as well as the learning capability available to all knowledge workers, not just modelers. So you don't need to do sophisticated modeling. It'll come back and guide you through in a very natural language kind of way. And it's, we're really trying to change how the whole analytic experience happens. And underneath Neo it takes advantage of some of the other capabilities. We talked today about blue, blue acceleration and then our analytic catalyst capability, which really puts kind of the stats and modeling in a box and brings it to that user. So we're very excited. We're going to be showing that today, uh, in our, in our main tent session. So it should be a know 3:00 PM it's at 3:00 PM yeah. >>At three 30 actually. So that's, so next generation discovery that's on across all datasets. Yes. And with analytics, uh, visualization built in for knowledge workers, you mean like a data scientist or like a worker on the front lines. So the iPhone, what, I mean, like a worker, this would be any knowledge worker, but then we're also with analytics trying to make it more pervasive. We'll embed it in a business process, for example, like a next best action or things like that. So you're going to have analytics going to the masses, embedded in a business process, but then here this is all about really looking at in a descriptive way what different things you want to see in your business in a very self service oriented way. Awesome. Awesome. What do you, what are you hearing from customers? You're out in the field, you run into big business of IBM that has a lot of legacy customers with computing platforms and paradigms that have been old-school. >>I'm going to say old school and a lot of new school rollouts and deployments. What are the top things are customers are asking for and when you want to go out, if you the dial up the top three, you know, floated to the top. What are the top three? I think that the number one thing that clients want here is outcomes. Business outcomes very quickly, right? They also want help on their journeys, right? As they look to evolve their analytic cultures, they look to evolve their platforms. They really want us to be able to go on that journey with them, help them understand their maturity, help them understand where they should be going and really help them prioritize the key actions they can take to drive the outcomes. And then it's really a, once you start, you focused on the priorities, then it's really helping them implement those. >>So we really look to, you know, our partner ecosystem as well as our services organization to help them drive those outcomes quicker. So a lot of activity you'd call the market robust at this point, very robust against 15 cents on every it dollars. It's a huge opportunity. It's a very exciting, a certain political business. Your Tim is 15 cents at every it dollar. The big data analytics component of it spent. Yeah, I mean served with service catalog, self-service with instrumentation of essentially value chains. I mean everything is now instrumented for the first time in history of business. I mean you think about it. Yeah. From oil exploration to hiring. So really appreciate your insight. A final question is what, what do you, what should people walk away with who aren't on site here, who are watching a, about what's happening here at IOD? There's so much happening. >>You know, we're talking, I think there's a lot of announcements. First of all, taking advantage of all data, whether it's insights stream. So we've got all data announcements, all analytic announcements, new solution announcements. But as we've looked out and we talked to many of our clients over the last couple of months, what do they need help with to be successful here? Because this is really all about outperforming. It's about continuously transforming in your business. They, they really want help imagining the future. So let's infuse that analytic culture everywhere in the business. Let's really, um, realize the value here. So evolve our platform and architecture and then really do it in a trusting way to drive the outcomes less. Thanks so much for your time. I know you're really busy. You've got a lot of, uh, business to do, customers to talk to a and speeches to give. Appreciate your time taking on the cube business outcomes fastest. What people want the most, help on this journey and collaborative way and implement it, scale it up. So, uh, that's, that's the future of business, social, social, business, business analytics and data. And onto the hood, the engine of innovation, cloud and mobile, social. This, the cube. We write back with our next guest after the short break, >>the cube.