>> Announcer: From the Cube Studios in Palo Alto in Boston, connecting with thought leaders all around the world, this is The Cube Conversation. >> Everyone welcome to this special live stream here in The Cube Studios. I'm John Furrier, your host. We've got a great panel discussion here for one hour, sponsored by Lumina PR, not sponsored but organized by Lumina PR. An authentic conversation around professionals in the news media, and communication professionals, how they can work together. As we know, pitching stories to national media takes place in the backdrop in today's market, which is on full display. The Coronavirus, racial unrest in our country and a lot of new tech challenges from companies, their role in society with their technology and of course, an election all make for important stories to be developed and reported. And we got a great panel here and the purpose is to bridge the two worlds. People trying to get news out for their companies in a way that's relevant and important for audiences. I've got a great panelists here, Gerard Baker Editor at Large with the Wall Street Journal, Eric Savitz, Associate Editor with Barron's and Brenna Goth who's a Southwest Staff Correspondent with Bloomberg Publications. Thanks for joining me today, guys, appreciate it. >> Thank you. >> So we're going to break this down, we got about an hour, we're going to probably do about 40 minutes. I'd love to get your thoughts in this power panel. And you guys are on the front lines decades of experience, seeing these waves of media evolve. And now more than ever, you can't believe what's happening. You're seeing the funding of journalism really challenging at an all time high. You have stories that are super important to audiences and society really changing and we need this more than ever to have more important stories to be told. So this is really a challenge. And so I want to get your thoughts on this first segment. The challenge is around collecting the data, doing the analysis, getting the stories out, prioritizing stories in this time. So I'd love to get your thoughts. We'll start with you, Brenna, what's your thoughts on this as you're out there in Arizona. Coronavirus on the worst is one of the states there. What are your challenges? >> I would say for me, one of the challenges of the past couple months is just the the sheer influx of different types of stories we've had and the amount of news coming out. So I think one of the challenging things is a lot of times we'll get into a bit of a routine covering one story. So early on maybe the Coronavirus, and then something else will come up. So I personally have been covering some of the Coronavirus news here in Arizona and in the Southwest, as well as some of the protests we've seen with the Black Lives Matter movement. And prioritizing that is pretty difficult. And so one thing that I I've been doing is I've noticed that a lot of my routine projects or things I've been working on earlier in the year are off the table, and I'll get back to them when I have time. But for now, I feel like I'm a little bit more on breaking news almost every day in a way that I wasn't before. >> Gerard, I want to get your thoughts on this. Wall Street Journal has been since I could remember when the web hit the scene early on very digital savvy. Reporting, it's obviously, awesome as well. As you have people in sheltering in place, both journalists and the people themselves and the companies, there's an important part of the digital component. How do you see that as an opportunity and a challenge at the same time because you want to get data out there, you want to be collecting and reporting those stories? How do you see that opportunity, given the challenge that people can't meet face to face? >> First of all, thank you very much for having me. I think as we've all discovered in all fields of endeavor in the last three months, it's been quite a revelation, how much we can do without using without access to the traditional office environment. I think one of the things that Coronavirus, this crisis will have done we all agree I think is that it will have fundamentally changed the way people work. There'll be a lot more people quite a bit more working from home. They'll be a lot more remote working. Generally, there'll be a lot less travel. So on the one hand, it's been eye opening. actually how relatively easy, I use that word carefully. But how we've managed, and I think it's true of all news organizations, how we've managed surprisingly well, I think, without actually being at work. At the Wall Street Journal, we have a big office, obviously in midtown Manhattan, as well as dozens of bureaus around the world. Nobody has really been in that office since the middle of March. And yet we've put out a complete Wall Street Journal product, everything from the print edition, obviously, through every aspect of digital media, the website, all of the apps, video, everything, audio, podcasts. We've been able to do pretty well everything that we could do when we were all working in the office. So I think that will be an important lesson and that will clearly induce some change, some long term changes, I think about the way we work. That said, I'd point to two particular challenges that I think we have not properly overcome. Or if you like that we have, the two impediments, that the crisis has produced for us. One is, as you said, the absence of face to face activity, the hive process, which I think is really important. I think that a lot of the best ideas, a lot of the best, the best stories are developed through conversations between people in an office which don't necessarily we can't necessarily replicate through the online experience through this kind of event or through the Zoom meetings that we've all been doing. I think that has inhibited to some extent, some of the more creative activity that we could have done. I think the second larger problem which we all must face with this is that being essentially locked up in our homes for more than three months, which most of us has been I think accentuates a problem that is already that has been a problem in journalism for a long time, which is that journalists tend to cluster in the major metropolitan areas. I think, a couple of years ago, I read a study which said, I think that more than three quarters of journalists work for major news organizations, print, digital TV, radio, whatever, live and work in one of four major metropolises in the US. That's the New York area, the Washington DC area, the San Francisco area and the LA area. And that tends to create a very narrow worldview, unfortunately, because not enough people either come from those areas, but from outside those areas or spend enough time talking to people from outside those areas. And I think the Coronavirus has accentuated that. And I think in terms of coverage, I'm here in New York. I've been in New York continuously for three and a half months now which is quite unusual, I usually travel a lot. And so my reporting, I write columns now, mainly, but obviously I talk to people too. But the reporting, the editing that we're doing here is inevitably influenced by the experience that we've had in New York, which has obviously been, frankly, devastating. New York has been devastated by Coronavirus in a way that no where else in the country has. And I think to some extent, that does, perhaps have undue influence on the coverage. We're all locked up. We're all mindful of our own health. We're all mindful of people that we know who've gone to hospital or have been very, very sick or where we are, we are heavily influenced by our own immediate environment. And I think that has been a problem if we had been, imagine if the journalists in the country, instead of being clustered in New York and LA and San Francisco had been sort of spread over Texas and Missouri and Florida, things like that. I think you'd have a very different overall accounting of this story over the last three months. So I think it's just, it's accentuated that phenomenon in journalism, which I think we're mindful of, and which we all need to do a better job of addressing. >> It's really interesting. And I want to come back to that point around, who you're collaborating with to get this, now we have virtual ground truth, I guess, how you collaborate. But decision making around stories is, you need an open mind. And if you have this, I guess, I'll call it groupthink or clustering is interesting, now we have digital and we have virtual, it opens up the aperture but we still have the groupthink. But I want to get Eric's take first on his work environment, 'cause I know you've lived on both sides of New York and San Francisco area, as well as you've worked out in the field for agencies, as well on the other side, on the storytelling side. How has this current news environment, journalism environment impacted your view and challenges and your opportunities that you're going after the news? >> Well, so there's there's a few elements here. So one, Barron's Of course, covers the world, looks at the world through a financial lens. We cover the stock market every day. The stock market is not the center of story, but it is an important element of what's been unfolding over the last few months and the markets have been incredibly volatile, we change the way that we approach the markets. Because everything, the big stories are macro stories, huge swings in stock prices, huge swings in the price of oil, dramatic moves in almost every financial security that you can imagine. And so there's a little bit of a struggle for us as we try and shift our daily coverage to be a little more focused on the macro stories as we're still trying to tell what's happening with individual stocks and companies, but these bigger stories have changed our approach. So even if you look at say the covers of our magazine over the last few months, typically, we would do a cover on a company or an investor, that sort of thing. And now they're all big, thematic stories, because the world has changed. And world is changing how it looks at the financial markets. I think one thing that that Gerard touched on is the inability to really leave your house. I'm sitting in my little home office here, where I've been working since March, and my inability to get out and talk to people in person to have some, some interface with the companies and people that I cover, makes it tougher. You get story ideas from those interactions. I think Gerard said some of it comes from your interactions with your colleagues. But some of that also just comes from your ability to interact with sources and that is really tougher to do. It's more formalistic if you do it online. It's just not the same to be on a Zoom call as to be sitting in a Starbucks with somebody and talking about what's going on. I think the other elements of this is that there's, we have a lot of attempts, trying new things trying to reach our readers. We'll do video sessions, we'll do all sorts of other things. And it's one more layer on top of everything else is that there's a lot of demands on the time for the people who are working in journalism right now. I would say one other thing I'll touch on, John, which is, you mentioned, I did use, I worked for public communications for a while, and I do feel their pain because the ability to do any normal PR pitching for new products, new services, the kinds of things that PR people do every day is really tough. It's just really hard to get anybody's attention for those things right now. And the world is focused on these very large problems. >> Well, we'll unpack the PR comms opportunities in the next section. But I want to to just come back to this topic teased out from Gerard and Brenna when you guys were getting out as well. This virtual ground truth, ultimately, at the end of the day, you got to get the stories, you got to report them, they got to be distributed. Obviously, the Wall Street Journal is operating well, by the way, I love the Q&A video chats and what they got going on over there. So the format's are evolving and doing a good job, people are running their business. But as journalists and reporters out there, you got to get the truth and the ground truth comes from interaction. So as you have an aperture with digital, there's also groupthink on, say, Twitter and these channels. So getting in touch with the audience to have those stories. How are you collecting the data? How are you reporting? Has anything changed or shifted that you can point to because ultimately, it's virtual. You still got to get the ground truth, you still got to get the stories. Any thoughts on this point? >> I think in a way what we're seeing is in writ large actually is a problem again, another problem that I think digital journalism or the digital product digital content, if you like, actually presents for us today, which is that it's often said, I think rightly, that one of the, as successful as a lot of digital journalism has been and thank you for what you said about the Wall Street Journal. And we have done a tremendous job and by the way, one of the things that's been a striking feature of this crisis has been the rapid growth in subscriptions that we've had at the Journal. I know other news organizations have too. But we've benefited particularly from a hunger for the quality news. And we've put on an enormous number subscriptions in the last three months. So we've been very fortunate in that respect. But one of the challenges that people always say, one of the one of the drawbacks that people always draw attention to about digital content is that there's a lack of, for want of a better words, serendipity about the experience. When you used to read a newspaper, print newspapers, when may be some of us are old enough to remember, we'd get a newspaper, we'd open it up, we'd look at the front page, we look inside, we'd look at what other sections they were. And we would find things, very large number of things that we weren't particularly, we weren't looking for, we weren't expecting to, we're looking for a story about such. With the digital experience, as we know, that's a much it's a much less serendipitous experience. So you tend to a lot of search, you're looking, you find things that you tend to be looking for, and you find fewer things that, you follow particular people on social media that you have a particular interest in, you follow particular topics and have RSS feeds or whatever else you're doing. And you follow things that, you tend to find things that you were looking for. You don't find many things you weren't. What I think that the virus, the being locked up at home, again, has had a similar effect. That we, again, some of the best stories that I think anybody comes across in life, but news organizations are able to do are those stories that you know that you come across when you might have been looking for something else. You might have been working on a story about a particular company with a particular view to doing one thing and you came across somebody else. And he or she may have told you something actually really quite different and quite interesting and it took you in a different direction. That is easier to do when you're talking to people face to face, when you're actually there, when you're calling, when you're tasked with looking at a topic in the realm. When you are again, sitting at home with your phone on your computer, you tend to be more narrowly so you tend to sort of operate in lanes. And I think that we haven't had the breadth probably of journalism that I think you would get. So that's a very important you talk about data. The data that we have is obviously, we've got access broadly to the same data that we would have, the same electronically delivered data that we would have if we'd been sitting in our office. The data that I think in some ways is more interesting is the non electronically delivered data that is again, the casual conversation, the observation that you might get from being in a particular place or being with someone. The stimuli that arise from being physically in a place that you just aren't getting. And I think that is an important driver of a lot of stories. And we're missing that. >> Well, Gerard, I just want to ask real quick before I go to Brenna on her her take on this. You mentioned the serendipity and taking the stories in certain directions from the interactions. But also there's trust involved. As you build that relationship, there's trust between the parties, and that takes you down that road. How do you develop trust as you are online now? Is there a methodology or technique? Because you want to get the stories out fast, it's a speed game. But there's also the development side of it where a trust equation needs to build. What's your thoughts on that piece? Because that's where the real deeper stories come from. >> So I wasn't sure if you're asking me or Gerard. >> Gerard if he wants can answer that is the trust piece. >> I'll let the others speak to that too. Yeah, it is probably harder to... Again, most probably most people, most stories, most investigative stories, most scoops, most exclusives tend to come from people you already trust, right? So you've developed a trust with them, and they've developed a trust with you. Perhaps more importantly, they know you're going to treat the story fairly and properly. And that tends to develop over time. And I don't think that's been particularly impaired by this process. You don't need to have a physical proximity with someone in order to be able to develop that trust. My sources, I generally speak to them on the phone 99% of the time anyway, and you can still do that from home. So I don't think that's quite... Obviously, again, there are many more benefits from being able to actually physically interact with someone. But I think the level of, trust takes a long time to develop, let's be honest, too, as well. And I think you develop that trust both by developing good sources. and again, as I said, with the sources understanding that you're going to do the story well. >> Brenna, speed game is out there, you got to get stories fast. How do you balance speed and getting the stories and doing some digging into it? What's your thoughts on all this? >> I would say, every week is looking different for me these days. A lot of times there are government announcements coming out, or there are numbers coming out or something that really does require a really quick story. And so what I've been trying to do is get those stories out as quick as possible with maybe sources I already have, or really just the facts on the ground I can get quickly. And then I think in these days, too, there is a ton of room for following up on things. And some news event will come out but it sparks another idea. And that's the time to that when I'm hearing from PR people or I'm hearing from people who care about the issue, right after that first event is really useful for me to hear who else is thinking about these things and maybe ways I can go beyond the first story for something that more in depth and adds more context and provides more value to our readers. >> Awesome. Well, guys, great commentary and insight there on the current situation. The next section is with the role of PR, because it's changing. I've heard the term earned media is a term that's been kicked around. Now we're all virtual, and we're all connected. The media is all virtual. It's all earned at this point. And that's not just a journalistic thing, there's storytelling. There's new voices emerging. You got these newsletter services, audiences are moving very quickly around trying to figure out what's real. So comms folks are trying to get out there and do their job and tell a story. And sometimes that story doesn't meet the cadence of say, news and/or reporting. So let's talk about that. Eric, you brought this up. You have been on both sides. You said you feel for the folks out there who are trying to do their job. How is the job changing? And what can they do now? >> The news cycle is so ferocious at the moment that it's very difficult to insert your weigh in on something that doesn't touch on the virus or the economy or social unrest or the volatility of the financial markets. So I think there's certain kinds of things that are probably best saved for another moment in time, If you're trying to launch new products or trying to announce new services, or those things are just tougher to do right now. I think that the most interesting questions right now are, If I'm a comms person, how can I make myself and my clients a resource to media who are trying to tell stories about these things, do it in a timely way, not overreach, not try insert myself into a story that really isn't a good fit? Now, every time one of these things happen, we got inboxes full of pitches for things that are only tangentially relevant and are probably not really that helpful, either to the reporter generally or to the client of the firm that is trying to pitch an idea. But I will say on the on this at the same time that I rely on my connections to people in corporate comms every single day to make connections with companies that I cover and need to talk to. And it's a moment when almost more than ever, I need immediacy of response, accurate information access to the right people at the companies who I'm trying to cover. But it does mean you need to be I think sharper or a little more pointed a little more your thinking about why am I pitching this person this story? Because the there's no time to waste. We are working 24 hours a day is what it feels like. You don't want to be wasting people's time. >> Well, you guys you guys represent big brands in media which is phenomenal. And anyone would love to have their company mentioned obviously, in a good way, that's their goal. But the word media relations means you relate to the media. If there's no media to relate to, the roles change, and there's not enough seats at the table, so to speak. So getting a clip on in the clip book that gets sent to management, look, "We're on Bloomberg." "Great, check." But is at it? So people, this is a department that needs to do more. Is there things that they can do, that isn't just chasing, getting on your franchises stories? Because it obviously would be great if we were all on Barron's Wall Street Journal, and Bloomberg, but they can't always get that. They still got to do more. They got to develop the relationships. >> John, one thing I would be conscious of here is that many of our publications, it's certainly true for journalists, true for us at Barron's and it's certainly true for Bloomberg. We're all multimedia publishers. We're doing lots of things. Barron's has television show on Fox. We have a video series. We have podcasts and newsletters, and daily live audio chats and all sorts of other stuff in addition to the magazine and the website. And so part of that is trying to figure out not just the right publication, but maybe there's an opportunity to do a very particular, maybe you'd be great fit for this thing, but not that thing. And having a real understanding of what are the moving parts. And then the other part, which is always the hardest part, in a way, is truly understanding not just I want to pitch to Bloomberg, but who do I want to pitch at Bloomberg. So I might have a great story for the Wall Street Journal and maybe Gerard would care but maybe it's really somebody you heard on the street who cares or somebody who's covering a particular company. So you have to navigate that, I think effectively. And even, more so now, because we're not sitting in a newsroom. I can't go yell over to somebody who's a few desks away and suggest they take a look at something. >> Do you think that the comm-- (talk over each other) Do you think the comms teams are savvy and literate in multimedia? Are they still stuck in the print ways or the group swing is they're used to what they're doing and haven't evolved? Is that something that you're seeing here? >> I think it varies. Some people will really get it. I think one of the things that that this comes back to in a sense is it's relationship driven. To Gerard's point, it's not so much about trusting people that I don't know, it's about I've been at this a long time, I know what people I know, who I trust, and they know the things I'm interested in and so that relationship is really important. It's a lot harder to try that with somebody new. And the other thing is, I think relevant here is something that we touched on earlier, which is the idiosyncratic element. The ability for me to go out and see new things is tougher. In the technology business, you could spend half your time just going to events, You could go to the conferences and trade shows and dinners and lunches and coffees all day long. And you would get a lot of good story ideas that way. And now you can't do any of that. >> There's no digital hallway. There are out there. It's called Twitter, I guess or-- >> Well, you're doing it from sitting in this very I'm still doing it from sitting in the same chair, having conversations, in some ways like that. But it's not nearly the same. >> Gerard, Brenna, what do you guys think about the comms opportunity, challenges, either whether it's directly or indirectly, things that they could do differently? Share your thoughts. Gerard, we'll start with you? >> Well, I would echo Eric's point as far as knowing who you're pitching to. And I would say that in, at least for the people I'm working with, some of our beats have changed because there are new issues to cover. Someone's taking more of a role covering virus coverage, someone's taking more of a role covering protests. And so I think knowing instead of casting a really wide net, I'm normally happy to try to direct pitches in the right direction. But I do have less time to do that now. So I think if someone can come to me and say, "I know you've been covering this, "this is how my content fits in with that." It'd grab my attention more and makes it easier for me. So I would say that that is one thing that as beats are shifting and people are taking on a little bit of new roles in our coverage, that that's something PR and marketing teams could definitely keep an eye on. >> I agree with all of that. And all everything everybody said. I'd say two very quick things. One, exactly as everybody said, really know who you are pitching to. It's partly just, it's going to be much more effective if you're pitching to the right person, the right story. But when I say that also make the extra effort to familiarize yourself with the work that that reporter or that editor has done. You cannot, I'm sorry to say, overestimate the vanity of reporters or editors or anybody. And so if you're pitching a story to a particular reporter, in a field, make sure you're familiar with what that person may have done and say to her, "I really thought you did a great job "on the reporting that you did on this." Or, "I read your really interesting piece about that," or "I listened to your podcast." It's a relatively easy thing to do that yields extraordinarily well. A, because it appeals to anybody's fantasy and we all have a little bit of that. But, B, it also suggests to the reporter or the editor or the person involved the PR person communications person pitching them, really knows this, has really done their work and has really actually takes this seriously. And instead of just calling, the number of emails I get, and I'm sure it's the same for the others too, or occasional calls out of the blue or LinkedIn messages. >> I love your work. I love your work. >> (voice cuts out) was technology. Well, I have a technology story for you. It's absolutely valueless. So that's the first thing, I would really emphasize that. The second thing I'd say is, especially on the specific relation to this crisis, this Coronavirus issue is it's a tricky balance to get right. On the one hand, make sure that what you're doing what you're pitching is not completely irrelevant right now. The last three months has not been a very good time to pitch a story about going out with a bunch of people to a crowded restaurant or whatever or something like that to do something. Clearly, we know that. At the same time, don't go to the other extreme and try and make every little thing you have seen every story you may have every product or service or idea that you're pitching don't make it the thing that suddenly is really important because of Coronavirus. I've seen too many of those too. People trying too hard to say, "In this time of crisis, "in this challenging time, what people really want to hear "about is "I don't know, "some new diaper "baby's diaper product that I'm developing or whatever." That's trying too hard. So there is something in the middle, which is, don't pitch the obviously irrelevant story that is just not going to get any attention through this process. >> So you're saying don't-- >> And at the same time, don't go too far in the other direction. And essentially, underestimate the reporter's intelligence 'cause that reporter can tell you, "I can see that you're trying too hard." >> So no shotgun approach, obviously, "Hey, I love your work." Okay, yeah. And then be sensitive to what you're working on not try to force an angle on you, if you're doing a story. Eric, I want to get your thoughts on the evolution of some of the prominent journalists that I've known and/or communication professionals that are taking roles in the big companies to be storytellers, or editors of large companies. I interviewed Andy Cunningham last year, who used to be With Cunningham Communications, and formerly of Apple, better in the tech space and NPR. She said, "Companies have to own their own story "and tell it and put it out there." I've seen journalists say on Facebook, "I'm working on a story of x." And then crowdsource a little inbound. Thoughts on this new role of corporations telling their own story, going direct to the consumers. >> I think to a certain extent, that's valuable. And in some ways, it's a little overrated. There are a lot of companies creating content on their websites, or they're creating their own podcasts or they're creating their own newsletter and those kinds of things. I'm not quite sure how much of that, what the consumption level is for some of those things. I think, to me, the more valuable element of telling your story is less about the form and function and it's more about being able to really tell people, explain to them why what they do matters and to whom it matters, understanding the audience that's going to want to hear your story. There are, to your point, there are quite a few journalists who have migrated to either corporate communications or being in house storytellers of one kind or another for large businesses. And there's certainly a need to figure out the right way to tell your story. I think in a funny way, this is a tougher moment for those things. Because the world is being driven by external events, by these huge global forces are what we're all focused on right now. And it makes it a lot tougher to try and steer your own story at this particular moment in time. And I think you do see it Gerard was talking about don't try and... You want to know what other people are doing. You do want to be aware of what others are writing about. But there's this tendency to want to say, "I saw you wrote a story about Peloton "and we too have a exercise story that you can, "something that's similar." >> (chuckles) A story similar to it. We have a dance video or something. People are trying to glam on to things and taking a few steps too far. But in terms of your original question, it's just tougher at the moment to control your story in that particular fashion, I think. >> Well, this brings up a good point. I want to get to Gerard's take on this because the Wall Street Journal obviously has been around for many, many decades. and it's institution in journalism. In the old days, if you weren't relevant enough to make the news, if you weren't the most important story that people cared about, the editors make that choice and you're on the front page or in a story editorially. And companies would say, "No, but I should be in there." And you'd say, "That's what advertising is for." And that's the way it seemed to work in the past. If you weren't relevant in the spirit of the decision making of important story or it needs to be communicated to the audience, there's ads for that. You can get a full page ad in the old days. Now with the new world, what's an ad, what's a story? You now have multiple omni-channels out there. So traditionally, you want to get the best, most important story that's about relevance. So companies might not have a relevant story and they're telling a boring story. There's no there, there, or they miss the story. How do you see this? 'Cause this is the blend, this is the gray area that I see. It's certainly a good story, depending on who you're talking to, the 10 people who like it. >> I think there's no question. We're in the news business, topicality matters. You're going to have a much better chance of getting your story, getting your product or service, whatever covered by the Wall Street Journal, Barron's or anywhere else for that matter, if it seems somehow news related, whether it's the virus or the unrest that we've been seeing, or it's to do with the economy. Clearly, you can have an effect. Newspapers, news organizations of all the three news organizations we represent don't just, are not just obviously completely obsessed with what happened this morning and what's going on right now. We are all digging into deeper stories, especially in the business field. Part of what we all do is actually try to get beyond the daily headlines. And so what's happening with the fortunes of a particular company. Obviously, they may be impacted by they're going to be impacted by the lockdown and Coronavirus. But they actually were doing some interesting things that they were developing over the long term, and we would like to look into that too. So again, there is a balance there. And I'm not going to pretend that if you have a really topical story about some new medical device or some new technology for dealing with this new world that we're all operating in, you're probably going to get more attention than you would if you don't have that. But I wouldn't also underestimate, the other thing is, as well as topicality, everybody's looking at the same time to be different, and every journalist wants to do something original and exclusive. And so they are looking for a good story that may be completely unrelated. In fact, I would also underestimate, I wouldn't underestimate either the desire of readers and viewers and listeners to actually have some deeper reported stories on subjects that are not directly in the news right now. So again, it's about striking the balance right. But I wouldn't say that, that there is not at all, I wouldn't say there is not a strong role for interesting stories that may not have anything to do what's going on with the news right now. >> Brenna, you want to add on your thoughts, you're in the front lines as well, Bloomberg, everyone wants to be on Bloomberg. There's Bloomberg radio. You guys got tons of media too, there's tons of stuff to do. How do they navigate? And how do you view the interactions with comms folks? >> It looks we're having a little bit of challenge with... Eric, your thoughts on comm professionals. The questions in the chats are everything's so fast paced, do you think it's less likely for reporters to respond to PR comms people who don't have interacted with you before? Or with people you haven't met before? >> It's an internal problem. I've seen data that talks about the ratio of comms people to reporters, and it's, I don't know, six or seven to one or something like that, and there are days when it feels like it's 70 to one. And so it is challenging to break through. And I think it's particularly challenging now because some of the tools you might have had, you might have said, "Can we grab coffee one day or something like that," trying to find ways to get in front of that person when you don't need them. It's a relationship business. I know this is a frustrating answer, but I think it's the right answer which is those relationships between media and comms people are most successful when they've been established over time. And so you're not getting... The spray and pray strategy doesn't really work. It's about, "Eric, I have a story that's perfect for you. "And here's why I think you you should talk to this guy." And if they really know me, there's a reasonable chance that I'll not only listen to them, but I'll at least take the call. You need to have that high degree of targeting. It is really hard to break through and people try everything. They try, the insincere version of the, "I read your story, it was great. "but here's another great story." Which maybe they read your story, maybe they didn't at least it was an attempt. Or, "if you like this company, you'll love that one." People try all these tricks to try and get get to you. I think the highest level of highest probability of success comes from the more information you have about not just what I covered yesterday, but what do I cover over time? What kinds of stories am I writing? What kinds of stories does the publication write? And also to keep the pitching tight, I was big believer when I was doing comms, you should be able to pitch stories in two sentences. And you'll know from that whether there's going to be connection or not, don't send me five or more pitches. Time is of the essence, keep it short and as targeted as possible. >> That's a good answer to Paul Bernardo's question in the chat, which is how do you do the pitch. Brenna, you're back. Can you hear us? No. Okay. We'll get back to her when she gets logged back in. Gerard, your thoughts on how to reach you. I've never met you before, if I'm a CEO or I'm a comms person, a company never heard of, how do I get your attention? If I can't have a coffee with you with COVID, how do I connect with you virtually? (talk over each other) >> Exactly as Eric said, it is about targeting, it's really about making sure you are. And again, it's, I hate to say this, but it's not that hard. If you are the comms person for a large or medium sized company or even a small company, and you've got a particular pitch you want to make, you're probably dealing in a particular field, a particular sector, business sector or whatever. Let's say it says not technology for change, let's say it's fast moving consumer goods or something like that. Bloomberg, Brenna is in an enormous organization with a huge number of journalist you deal and a great deal of specialism and quality with all kinds of sectors. The Wall Street Journal is a very large organization, we have 13, 1400 reporters, 13 to 1400 hundred journalist and staff, I should say. Barron's is a very large organization with especially a particularly strong field coverage, especially in certain sectors of business and finance. It's not that hard to find out A, who is the right person, actually the right person in those organizations who's been dealing with the story that you're trying to sell. Secondly, it's absolutely not hard to find out what they have written or broadcast or produced on in that general field in the course of the last, and again, as Eric says, going back not just over the last week or two, but over the last year or two, you can get a sense of their specialism and understand them. It's really not that hard. It's the work of an hour to go back and see who the right person is and to find out what they've done. And then to tailor the pitch that you're making to that person. And again, I say that partly, it's not purely about the vanity of the reporter, it's that the reporter will just be much more favorably inclined to deal with someone who clearly knows, frankly, not just what they're pitching, but what the journalist is doing and what he or she, in his or her daily activity is actually doing. Target it as narrowly as you can. And again, I would just echo what Eric and I think what Brenna was also saying earlier too that I'm really genuinely surprised at how many very broad pitches, again, I'm not directly in a relative role now. But I was the editor in chief of the Journal for almost six years. And even in that position, the number of extraordinarily broad pitches I get from people who clearly didn't really know who I was, who didn't know what I did, and in some cases, didn't even really know what Wall Street Journal was. If you can find that, if you actually believe that. It's not hard. It's not that hard to do that. And you will have so much more success, if you are identifying the organization, the people, the types of stories that they're interested in, it really is not that difficult to do. >> Okay, I really appreciate, first of all, great insight there. I want to get some questions from the crowd so if you're going to chat, there was a little bit of a chat hiccup in there. So it should be fixed. We're going to go to the chat for some questions for this distinguished panel. Talk about the new coffee. There's a good question here. Have you noticed news fatigue, or reader seeking out news other than COVID? If so, what news stories have you been seeing trending? In other words, are people sick and tired of COVID? Or is it still on the front pages? Is that relevant? And if not COVID, what stories are important, do you think? >> Well, I could take a brief stab at that. I think it's not just COVID per se, for us, the volatility of the stock market, the uncertainties in the current economic environment, the impact on on joblessness, these massive shifts of perceptions on urban lifestyles. There's a million elements of this that go beyond the core, what's happening with the virus story. I do think as a whole, all those things, and then you combine that with the social unrest and Black Lives Matter. And then on top of that, the pending election in the fall. There's just not a lot of room left for other stuff. And I think I would look at it a little bit differently. It's not finding stories that don't talk on those things, it's finding ways for coverage of other things whether it's entertainment. Obviously, there's a huge impact on the entertainment business. There's a huge impact on sports. There's obviously a huge impact on travel and retail and restaurants and even things like religious life and schooling. I have the done parents of a college, was about to be a college sophomore, prays every day that she can go back to school in the fall. There are lots of elements to this. And it's pretty hard to imagine I would say to Gerard's point earlier, people are looking for good stories, they're always looking for good stories on any, but trying to find topics that don't touch on any of these big trends, there's not a lot of reasons to look for those. >> I agree. Let me just give you an example. I think Eric's exactly right. It's hard to break through. I'll just give you an example, when you asked that question, I just went straight to my Wall Street Journal app on my phone. And of course, like every organization, you can look at stories by sections and by interest and by topic and by popularity. And what are the three most popular stories right now on the Wall Street Journal app? I can tell you the first one is how exactly do you catch COVID-19? I think that's been around since for about a month. The second story is cases accelerate across the United States. And the third story is New York, New Jersey and Connecticut, tell travelers from areas with virus rates to self isolate. So look, I think anecdotally, there is a sense of COVID fatigue. Well, we're all slightly tired of it. And certainly, we were probably all getting tired, or rather distressed by those terrible cases and when we've seen them really accelerate back in March and April and these awful stories of people getting sick and dying. I was COVID fatigued. But I just have to say all of the evidence we have from our data, in terms of as I said earlier, the interest in the story, the demand for what we're doing, the growth in subscriptions that we've had, and just as I said, little things like that, that I can point you at any one time, I can guarantee you that our among our top 10 most read stories, at least half of them will be COVID-19. >> I think it's safe to say general interest in that outcome of progression of that is super critical. And I think this brings up the tech angle, which we can get into a minute. But just stick with some of these questions I just want to just keep these questions flowing while we have a couple more minutes left here. In these very challenging times for journalism, do byline articles have more power to grab the editors attention in the pitching process? >> Well, I think I assume what the questioner is asking when he said byline articles is contributed. >> Yes. >> Contributed content. Barron's doesn't run a lot of contributing content that way in a very limited way. When I worked at Forbes, we used to run tons of it. I'm not a big believer that that's necessarily a great way to generate a lot of attention. You might get published in some publication, if you can get yourself onto the op ed page of The Wall Street Journal or The New York Times, more power to you. But I think in most cases-- >> It's the exception not the rule Exception not the rule so to speak, on the big one. >> Yeah. >> Well, this brings up the whole point about certainly on SiliconANGLE, our property, where I'm co founder and chief, we basically debate over and get so many pitches, "hey, I want to write for you, here's a contributed article." And it's essentially an advertisement. Come on, really, it's not really relevant. In some case we (talk over each other) analysts come in and and done that. But this brings up the question, we're seeing these newsletters like sub stack and these services really are funding direct journalism. So it's an interesting. if you're good enough to write Gerard, what's your take on this, you've seen this, you have a bit of experience in this. >> I think, fundamental problem here is that is people like the idea of doing by lines or contributed content, but often don't have enough to say. You can't just do, turn your marketing brochure into a piece of an 800 word with the content that that's going to be compelling or really attract any attention. I think there's a place for it, if you truly have something important to say, and if you really have something new to say, and it's not thinly disguised marketing material. Yeah, you can find a way to do that. I'm not sure I would over-rotate on that as an approach. >> No, I just briefly, again, I completely agree. At the Journal we just don't ever publish those pieces. As Eric says, you're always, everyone is always welcome to try and pitch to the op ed pages of the Journal. They're not generally going to I don't answer for them, I don't make those decisions. But I've never seen a marketing pitch run as an op ed effectively. I just think you have to know again, who you're aiming at. I'm sure it's true for Bloomberg, Barron's and the Journal, most other major news organizations are not really going to consider that. There might be organizations, there might be magazines, digital and print magazines. There might be certain trade publications that would consider that. Again, at the Journal and I'm sure most of the large news organizations, we have very strict rules about what we can publish. And how and who can get published. And it's essentially journal editorials, that journal news staff who can publish stories we don't really take byline, outside contribution. >> Given that your time is so valuable, guys, what's the biggest, best practice to get your attention? Eric, you mentioned keeping things tight and crisp. Are there certain techniques to get your attention? >> Well I'll mention just a couple of quick things. Email is better than most other channels, despite the volume. Patience is required as a result because of the volume. People do try and crawl over the transom, hit you up on LinkedIn, DM you on Twitter, there's a lot of things that people try and do. I think a very tightly crafted, highly personalized email with the right subject line is probably still the most effective way, unless it's somebody you actually, there are people who know me who know they have the right to pick up the phone and call me if they really think they have... That's a relationship that's built over time. The one thing on this I would add which I think came up a little bit before thinking about it is, you have to engage in retail PR, not not wholesale PR. The idea that you're going to spam a list of 100 people and think that that's really going to be a successful approach, it's not unless you're just making an announcement, and if you're issuing your earnings release, or you've announced a large acquisition or those things, fine, then I need to get the information. But simply sending around a very wide list is not a good strategy, in most cases, I would say probably for anyone. >> We got Brenna back, can you hear me? She's back, okay. >> I can hear you, I'm back. >> Well, let's go back to you, we missed you. Thanks for coming back in. We had a glitch on our end but appreciate it, bandwidth internet is for... Virtual is always a challenge to do live, but thank you. The trend we're just going through is how do I pitch to you? What's the best practice? How do I get your attention? Do bylines lines work? Actually, Bloomberg doesn't do that very often either as well as like the Journal. but your thoughts on folks out there who are really trying to figure out how to do a good job, how to get your attention, how to augment your role and responsibilities. What's your thoughts? >> I would say, going back to what we said a little bit before about really knowing who you're pitching to. If you know something that I've written recently that you can reference, that gets my attention. But I would also encourage people to try to think about different ways that they can be part of a story if they are looking to be mentioned in one of our articles. And what I mean by that is, maybe you are launching new products or you have a new initiative, but think about other ways that your companies relate to what's going on right now. So for instance, one thing that I'm really interested in is just the the changing nature of work in the office place itself. So maybe you know of something that's going on at a company, unlimited vacation for the first time or sabbaticals are being offered to working parents who have nowhere to send their children, or something that's unique about the current moment that we're living in. And I think that those make really good interviews. So it might not be us featuring your product or featuring exactly what your company does, but it still makes you part of the conversation. And I think it's still, it's probably valuable to the company as well to get that mention, and people may be looking into what you guys do. So I would say that something else we are really interested in right now is really looking at who we're quoting and the diversity of our sources. So that's something else I would put a plug in for PR people to be keeping an eye on, is if you're always putting up your same CEO who is maybe of a certain demographic, but you have other people in your company who you can give the opportunity to talk with the media. I'm really interested in making sure I'm using a diverse list of sources and I'm not just always calling the same person. So if you can identify people who maybe even aren't experienced with it, but they're willing to give it a try, I think that now's a really good moment to be able to get new voices in there. >> Rather than the speed dial person you go to for that vertical or that story, building out those sources. >> Exactly. >> Great, that's great insight, Everyone, great insights. And thank you for your time on this awesome panel. Love to do it again. This has been super informative. I love some of the engagement out there. And again, I think we can do more of these and get the word out. I'd like to end the panel on an uplifting note for young aspiring journalists coming out of school. Honestly, journalism programs are evolving. The landscape is changing. We're seeing a sea change. As younger generation comes out of college and master's programs in journalism, we need to tell the most important stories. Could you each take a minute to give your advice to folks either going in and coming out of school, what to be prepared for, how they can make an impact? Brenna, we'll start with you, Gerard and Eric. >> That's a big question. I would say one thing that has been been encouraging about everything going on right now as I have seen an increased hunger for information and an increased hunger for accurate information. So I do think it can obviously be disheartening to look at the furloughs and the layoffs and everything that is going on around the country. But at the same time, I think we have been able to see really big impacts from the people that are doing reporting on protests and police brutality and on responses to the virus. And so I think for young journalists, definitely take a look at the people who are doing work that you think is making a difference. And be inspired by that to keep pushing even though the market might be a little bit difficult for a while. >> I'd say two things. One, again, echoing what Brenna said, identify people that you follow or you admire or you think are making a real contribution in the field and maybe directly interact with them. I think all of us, whoever we are, always like to hear from young journalists and budding journalists. And again, similar advice to giving to the advice that we were giving about PR pitches. If you know what that person has been doing, and then contact them and follow them. And I know I've been contacted by a number of young journalists like that. The other thing I'd say is and this is more of a plea than a piece of advice. But I do think it will work in the long run, be prepared to go against the grain. I fear that too much journalism today is of the same piece. There is not a lot of intellectual diversity in what we're seeing There's a tendency to follow the herd. Goes back a little bit to what I was saying right at the opening about the fact that too many journalists, quite frankly, are clustered in the major metropolitan areas in this country and around the world. Have something distinctive and a bit different to say. I'm not suggesting you offer some crazy theory or a set of observations about the world but be prepared to... To me, the reason I went into journalism was because I was always a bit skeptical about whenever I saw something in any media, which especially one which seemed to have a huge amount of support and was repeated in all places, I always asked myself, "Is that really true? "Is that actually right? "Maybe there's an alternative to that." And that's going to make you stand out as a journalist, that's going to give you a distinctiveness. It's quite hard to do in some respects right now, because standing out from the crowd can get you into trouble. And I'm not suggesting that people should do that. Have a record of original storytelling, of reporting, of doing things perhaps that not, because look, candidly, there are probably right now in this country, 100,00 budding putative journalists who would like to go out and write about, report on Black Lives Matter and the reports on the problems of racial inequality in this country and the protests and all of that kind of stuff. The problem there is there are already 100,000 of those people who want to do that in addition to probably the 100,000 journalists who are already doing it. Find something else, find something different. have something distinctive to offer so that when attention moves on from these big stories, whether it's COVID or race or politics or the election or Donald Trump or whatever. Have something else to offer that is quite distinctive and where you have actually managed to carve out for yourself a real record as having an independent voice. >> Brenna and Gerard, great insight. Eric, take us home close us out. >> Sure. I'd say a couple things. So one is as a new, as a young journalist, I think first of all, having a variety of tools in your toolkit is super valuable. So be able to write long and write short, be able to do audio, blogs, podcast, video. If you can shoot photos and the more skills that you have, a following on social media. You want to have all of the tools in your toolkit because it is challenging to get a job and so you want to be able to be flexible enough to fill all those roles. And the truth is that a modern journalist is finding the need to do all of that. When I first started at Barron's many, many years ago, we did one thing, we did a weekly magazine. You'd have two weeks to write a story. It was very comfortable. And that's just not the way the world works anymore. So that's one element. And the other thing, I think Gerard is right. You really want to have a certain expertise if possible that makes you stand out. And the contradiction is, but you also want to have the flexibility to do lots of different stories. You want to get (voice cuts out) hold. But if you have some expertise, that is hard to find, that's really valuable. When Barron's hires we're always looking for people who have, can write well but also really understand the financial markets. And it can be challenging for us sometimes to find those people. And so I think there's, you need to go short and long. It's a barbell strategy. Have expertise, but also be flexible in both your approach and the things you're willing to cover. >> Great insight. Folks, thanks for the great commentary, great chats for the folks watching, really appreciate your valuable time. Be original, go against the grain, be skeptical, and just do a good job. I think there's a lot of opportunity. And I think the world's changing. Thanks for your time. And I hope the comms folks enjoyed the conversation. Thank you for joining us, everyone. Appreciate it. >> Thanks for having us. >> Thank you. >> I'm John Furrier here in the Cube for this Cube Talk was one hour power panel. Awesome conversation. Stay in chat if you want to ask more questions. We'll come back and look at those chats later. But thank you for watching. Have a nice day. (instrumental music)

>> from New York City. It's the cue covering automation anywhere. Imagine, brought to you by automation anywhere you >> were in midtown Manhattan, at the automation anywhere. Imagine Crawford's twenty nineteen really psyched to be here. Fifteen hundred people talking about our P A. But really, the Rp story is much more than just robotic process. Automation is really a new way to work, which we hear about all over the place and really reimagining what this technology can do. We're excited to have our next guest. She's Shelly Kramer, an analyst and partner for feature research. Shelley, great to see you. >> Great to see you, too. And you got it. >> I got a right. >> You got it. >> Well, you're a very busy lady. Got all kinds of stuff going on, which is what we like. So first off, just kind of Have you been here before? General impressions of the show. >> This is my first, Uh, this is my first, uh, automation anywhere event. And so it's exciting. I write a lot about our PPA and about the future of work and work force transformation. So it's great to be >> here. Yeah. And you just wrote not a super uplifting article linked in about, you know, employee dissatisfaction and some of the issues with employee retention. We talked before. We turn the cameras on about things like calling him human resource is, you know, and human capital there, they're people. And I thought my here really touched on it. Well, in the keynote today that this is not a rip and replace technology for people. This is a tool to help us do our jobs better, just like our laptops and our mobile phones and our application. So are you excited about the opportunity? See, it is this transformative. >> I do see this transformative. And I think that before you talk about what we talked about, the technology that we have to talk about people and Simpson and I'm pulling this out of my memory banks. So on average, about eighty two percent of employees within any organization are disengaged. OK, eighty two percent. >> So the ping pong tables and the tables are not doing it. >> And so when you think about it and engaged workforce are people who wake up in the morning or whatever it is, they go to work and who are excited about what they're doing excited about their company. They're working for love, the culture that they're working within. I love all those things that they're doing. And so when you realize that eighty two percent of people are disengaged, that's problematic. Right then, you're talking about the toughest talent acquisition markets that we've had in a really long time. So we're all fighting for top talent, not just top tech talent but any kind of talent. And so focusing on how we can make the workforce better and create better cultures and put systems and processes in place that can make people do their jobs more efficiently, more productively and actually like them. That's to me. That's the beginning of where we get to this technology piece and what our P a Khun Dio How? Aye aye plays a role in there and how you can. How employees can partner you think of technology as a partner, as opposed to worrying about technology replacing them. So I think it's an exciting time in the workforce, and when you think about it that way, it makes a lot of sense. >> Do you think the difference in kind of the expectations that people have when they Goto work to be engaged as a function of the millennials who are looking for something that's more mission lead. Is it a function of just the competition? It's so robust that before people could get away with having, you know, maybe a less compelling work experience. What do you think is driving? The changer hasn't changed, and maybe now we're just paying more attention to it. >> You know, I think it's changed in a little bit. I think that you and I are old enough that when we were coming of age and we were working our way up the corporate ladder, you know, you kind of sold a little bit of your soul to the company store. No matter. I mean, I gripped in advertising, right, and, you know, I work crazy hours, and I loved it. But I never questioned that there were dues that I had to pay, and that's what you think. And I think that people don't necessarily expect the world on a platter. But I think especially the more skilled you are, whether it's a knowledge of tack or whatever it is in today's market, I think that ueno and again it could be someone my age. It could be someone that's twenty five. It could be someone that's forty. I can find something else. So minute, this isn't doing it for me, right? I can go find something else right now. That said, there are also people who are punching a clock. You know what I'm saying? And I don't mean ship workers. Necessarily. As much as I need to pay the mortgage, I need to get my kid's bed. You know, I don't love this job. Maybe it's a path to something. One of my daughters works for an insurance company. She has a very non glamorous job. She doesn't love it, but she knows she has to do it for X amount of time before she can be considered for this different promotion. And she is watching the clock on literally. I'm getting to that milestone and asking for her promotion. And if that doesn't happen, she'LL leave. So so I think that when you can, people don't feel like they need to be stuck, right? So I think that way. As a CZ leaders and his executives in the workforce, I think you always have to be mindful about what the work environment that you're creating is and focus on. How do we keep how do we get people? And how do we build the value props that we used when we entice them to say yes to our offer? How do we get them to stay? >> S o many things there, But But, you know, what things you just mentioned is is I don't think they accept it like we did. Maybe when we're coming up, which is, you know, you hire somebody and you hire them for the act tributes that they're bringing in the organization than it used to be. Then you give him the employee rulebook and you basically squash, you know, kind of all the individual creativity and ingenuity and enthusiasm, which is why you hired him in the first place. And we don't see that as much anymore. But at the same token, you know, not everyone's worried about robots taken their job at the same time. There's so many unfulfilled Rex out there. And as you said, it's the most competitive labor market out there. How our employers supposed to kind of square that circle because they need to bring the automation they want to keep the people happy. It's a hyper competitive market, and they need mission. But, you know, we gotta pay the bills and get the products out. >> I think that So I think that we can never forget that people that work for our companies need to pay the bills too. Right? So when you can give them something that they could be excited about, Tio dio that helps. Right? But it just kind of like I'm thinking back Teo, uh, presentation and I can't remember his name. But the V p of product did a presentation about today on a loan mortgage loan application. Okay, that has to be like one of the most boring things, right? If you're in that mortgage loan processing, do this. Do this. Do this villain this spreadsheet love about, By the way, I hate creating spreadsheets. I just want to look at a finished one. But anyway, it was so cool to just look at this, and I shot a video of it, shared it on Twitter. If you want to see what I'm talking about, but which is so cool that you can do this and do this and do this and you know you create this process. And in no time the technology has done all the work and all the calculations, and you've got a recommendation approved, not approved. And so if you're in the mortgage loan business, way to think about that leased, the way that I think to think about it is, doesn't mean that your job is going to go away. It's just like my daughter doing that not very exciting job that she's doing. If automation could fuel some of the mundane, repeatable, banal tasks so that she could focus on the other part of the equation where it's more interesting and more exciting, I think then that's really the value equation there. But I think as I think, what businesses have todo is be transparent and very honest with their employees and tell them, you know, this is our This is why we're doing this. This is what our means, and this is how it's going to add value. It we're not doing this to necessarily replace humans. This is so that we can make this work better, efficient more, you know. And I think that you know, I'll step back and say for a personal example. We went through a process last year where we evaluated all of our business processes, and we looked at how much time our employees were spending sweet track time doing certain tasks. And then we were realizing, you know, the value there. We were actually paying too much in terms of the time, investment or tasks that didn't make sense to. Then we set out integrating automation into our processes, and it was it was a big project, right? And people were kind of worried, you know, and they were kind of worried about it. But one of the things that way told them early on with, like, This is not so that we don't have work for you. This is so that we can make what it is you're doing more efficient and you could do things you like better, >> right? Right. >> And so and that has happened and way didn't lose any of our team. And a lot of those task that they were doing are now automated. They're doing stuff that they like more. So I think that I think that's really the challenge for businesses. Two is the messaging right and then involving your teams in the process, appointment of any kind of >> technology. I think it's just the soul crushing. You know, expression is so it's so valid for for these types of activities. And I think again may hear had a great stat. Four percent of US jobs required a medium level of creativity, which you know people want to get out from under that. But if we can define it as a tool and is a thinking like personal digital assistants, my body will. That used to be just my palm three was my p d. A. Right wow how no. One No one was threatened by the Palm taking the job away. So I think you know, you're right. If we can put it in the context of it's just another tool that's just gonna help you get your job done. That's a very different way to frame the problem versus kind of just ripping replace narrative, which we hear kind of over and over again. >> Well, and I think it also goes beyond Jeff. It's goes beyond, and I think that employees at every level have to understand this. It goes beyond just helping you get your job done. It really is about, you know, cos that survived today and tomorrow are the companies who transformed. And, you know, we talk a lot about digital transformation. And you know, I'm out there on the front lines all day, every day, and I can promise you there are many, many companies who are far from really understanding and embracing this and understanding what it takes from a technology standpoint and the value, that data ad and how to use that data and and the impact that that has on customer experience and all that sort of thing. So So I think it's really is about much more than this will make your jobs suck less >> right, right, Right. >> I think it's about this is how our company stay successful. This is how you helped make your job in the role you play within our organization, what you want it to be, right? And I think that you could probably telling, you know, I've been marketing because I'm always thinking about you know how I know how you spend something and I don't mean in a spin like a PR way, but I think we all have to step back and think about it in terms of the whole equation. And there are a whole lot of companies that don't exist anymore, right? You know whether you're talking about the financial services sector and you know and every business everywhere is being disrupted. I told this story. I was I was talking with me here earlier this morning and I was telling him a story about how my husband, I just bought a new car and we expected to get a loan for that car from our community. It's not a community from our our local bank local. Our local bank has been recently purchased by a bigger bank in the last couple of years, but we run all of our corporate money. I mean, everything that we've ever done is here in this way. You know your spell. ITA loan application. No problem. Give us an interest rate. No problem. But they made every part. My husband I vote travel a lot for business, and they're every part of the process required us to be somewhere together to have an official closing. To do this, to do that and it was just like way could never purchased this car because they were making it so difficult for us. So we enter death talking with the car dealer who said I'm not God. We can fix you up, financed it through their banking partner, which is a huge national bank approved in five minutes. Loan documents in five minutes. Hey, come on out. You sign this tomorrow? He consigned this when he gets, you know. And when I talked to my bank after the transaction, they said, Here's the deal. I wanted to do business with you. But when you make it difficult for a customer to give you their money, they're not gonna hesitate to give somebody else there money, Right? So So I think the banking industry is one example of the these processes that air so cumbersome that in some ways can be automated, but it just it doesn't make sense. And customers today you and I are impatient people as our people younger than we are way. No, there has to be a better way. An analogy could give us a better >> win it right, And, you know, they could use different data sets. And I mean, I've bought himself recently, and you just push the button on the phone and it takes a minute. The wheel spins and then your approved right and you're done if you're done, and it's it's a completely different experience. But the part about the digital transformation I want to follow because it came up today where a lot of times people are the integration point between these systems very similar to the example you just used and you can't digitally transform. If all these automated systems ultimately have the bottleneck through some person to take this piece Veda and stick it over there, right? So it's it's absolutely critical to get those people out of the way, right? So as you look forward twenty nineteen, what are some of the big trends beyond our P A and kind of personal digital assistants not called palm, uh, that you're seeing and that you're excited about? >> Well, I think that, you know, it's hard not to be excited about our p A. Just simply because of, you know, it's predicted to be a one point nine billion this year and to almost double by twenty twenty one. I mean, it makes sense that companies like automation anywhere doubling down on that right. It also makes sense that gigantic companies like IBM and Jo Lloyd and you know why. I mean, you >> know, hearing for >> all here, right? There's a reason for that, right? Because IBM customers want this and Microsoft's customers want this. So So I think that in general I think that technology is fueling our world. Our personal lives are business world, and I think that probably one of the biggest things that I pay attention to to that we pay attention to is that technology alone isn't the answer. It's the partnership of human beings and their skill sets and capabilities and data and automation and artificial intelligence and all those things. So I think that I think that it's an incredibly exciting time. It's kind of like, you know, you you go back to the video that we saw this morning in the bit about the Internet, and I don't know if you remember this. I don't know, probably. I don't know how much older I am than you, but, you know, I remember that Internet machine and wow, this is like I could send an email, you know? And then when you think about right how and those comments, You know that Matt Lauer and Katie Couric we're making it like that weren't down comments we didn't didn't know, right? Know the impact Internet could have would have, you know. And so I think the same is true of this kind of technology today. This this next generation of technology. So there's not just one thing I'm interested. I'm interested in Element. >> Gotta keep learning right because way have a hard time with were very linear and everything is growing exponentially. So you got a got to be willing. Teo learned the next thing because it's right around the corner, >> and I think that's so key. That's that's a great rap. I think that people who are happiest today are people who actually love change and who love learning. And I would say I would posit that most that those air not inherently things that people trades that people possess. I'm lucky because I do. You see what I'm saying? I think it's >> an interesting question, whether that's inherent. If there's just people that liked the learning, our curious all the time, and that and then they got to stick in the muds and Candice stick in the muds, change your attitude and become learners again. >> Maybe they won't. I mean, you know, I think that they're I do think that there are are people who are wired to like change and two are curious and who loved learning. And I think there are a whole bunch of people who are not. And I would I truly believe that for success in today's world and moving forward for young people and not so young people, you better get there if that's not your deal, because I don't think that I did it. And I have stumbled across conversations of people having like, you know, that's not gonna happen, you know? So I don't have to worry about it because I'm gonna be outta here by then. Or and you know what? There are a whole bunch of people that have that mindset, and that's a okay, but especially for young people making their way, >> they okay mindset. But it's not the fact that that's the problem. It's it's happening now. I mean, the future is here, and it's happening at a faster pace. Well, Shelley, we could go on and on and on, but we're going to leave it there. And I appreciate you taking a few minutes out of your day. >> Absolutely. My pleasure. >> All right. She Shelly, I'm Jeff. You're watching the Cube. Where? Automation anywhere. Imagine in Midtown Manhattan. Thanks for watching. See you next time.

>> From New York City, it's theCUBE! Covering Automation Anywhere Imagine, brought to you by Automation Anywhere. >> Hey welcome back everybody, Jeff Frick here with theCUBE. We're in Midtown Manhattan at the Automation Anywhere Imagine 2019. We we're here last year, it was about 1,500 people. And really, Automation Anywhere is really hot in the RPA space, Robotic Process Automation, but it's really a lot more than that, it's not just automating some processes, it's really about new ways to work, personal digital assistants, and really changing the game. We're excited to have our next guest, first time on theCUBE. He's Prince Kohli, the CTO of Automation Anywhere. Prince, great to see you. >> Thank you, Jeff, good to be here. >> Yeah, so you weren't here last year, so I'm curious to get your general impressions of the event and kind of the scene here with the Automation Anywhere ecosystem. >> Of course, I wasn't here last year, I heard a lot about it, but the sense of excitement, the sense of growth, and the sense of opportunity that is there in everyone. The number of customers who were here and were excited to be here, partners who were here and were really happy to be here, and of course, the team, my own team. It just, just the sense of excitement, and the fact that we are on a hockey stick, in terms of growth, is just palpable. >> Right, so I'm curious to get your take, you've been in the Valley for a long time, and really the RPA theme is about digital workers. In fact, they get roles, they get names, they talk about 'em on stage like they're people. And the idea is that we all have our own assistant, which has been talked about forever but maybe you kind of had an offshore person you could help dial in your laundry, nothing like what we're talking about today. So, as you look back at the evolution as to how we got here, what's your take on the role of a personal digital assistant? >> That's a great question. The way, in my view, the way it evolved was that it is similar to cloud computing. I think the idea that these things could happen. I mean, you know, Star Trek had it, right? >> Right. >> So I think those things have, as an idea, have existed, but usually it was in fantasy. But what has happened in the last five or ten years, is that computing, the need for automation across applications, the need for work to be less mundane, the need for creativity in our human jobs, those have become really important. And therefore the definition of work is evolving. What can be automated therefore must be automated. And it is not automation within an application, it is automation across applications, across processes, across whichever applications, from whichever vendors there may be, without changing the application itself. And that, with the tenurial of AI and acceptance of AI, I think has allowed people to start accepting the notion of a digital worker. >> It's pretty interesting, one of the topics of the keynote was that the people were the integration point between (laughs) a lot of these systems, super inefficient. And what I think is interesting on the AI front and the automation, the place I see it's just a little bit every day, is on Google, or an app that most people are familiar with, whether it's Google Maps, and suddenly it's got restaurants on it, and suddenly it's got reviews on it, and suddenly it's got Street View or whether it's now on the email where suddenly it's guessing my response, it's auto filling even before I start to complete my email. And it really shows that it's this ongoing continuous innovation empowered by AI and a boatload of data that lets these applications do, as you said, things that before would be considered magical. >> Absolutely, and if you look at the digital worker paradigm, right? It's not, if you look at a great example of a digital worker, for example an AP clerk, an account payables clerk. Think of an invoicing function, an invoice comes in, someone has to read it, interpret it, the (coughs), excuse me, the format of invoices are very different across vendors. Reading, interpreting, tying it to a PO, making sure the PO is correct, making sure the PO is valid, was issued at the right time, the item is not late, someone has signed up, there are so many things one has to do. And a person has to do all that today. But it is really very boring work. There is, you just follow a set of steps, there is not judgment involved, really. What an AP digital worker allows you to do (coughs) is to be able to read the document, interpret it, take all the steps that are necessary, and then be able to do that job 24 hours a day, and allow the offloading of this mundane, boring work, right, from a human. So they can be more creative, they can actually make the process better, as opposed to just following a set of simple rules. >> Right, finishing one of the earlier conversations too, and then defining that process so that you can automate it, you're going to unwind inefficiency, you're going to unwind biases, you're going to unwind a whole bunch of stuff to get it to the automated process. So there's all kinds of secondary benefits beyond simply freeing up your time to do more creative work. >> That is correct, and I think, as you said, there are biases, there are also things that must work together in enterprise and today don't. And you know, the vendors, the application vendors are not going to do that, it is not in their own interest. So someone has to, and we are the fabric that brings it together. >> Right, and just people as an integration point, I thought that was classic, that's like the worst place you want to be. And then the other concept that I think doesn't come out enough is a lot of people can be thinking about RPA as a rip and replace for the people. It's not rip and replace at all, it's really augment, just like you augment with your laptop, your phone, other software applications that you're working with every day. >> It's a great point, we have never seen any customer, even talking about ripping and replacing people. What they're trying to do is give people the tools and the augmentation necessary for them to make their own life better. And that improves the moral of the employees, that improves the company's productivity, of course, right, and probably the best output, the best of vidimation that, it improves their customer satisfaction. Because customers are able to create cards faster, are able to get responses faster, claims get adjusted faster, all these things work very well. >> Right, it's interesting, when you sit back and look at the whole technology stack, some really fundamental changes in microprocesser power, networking speed, storage, now the cloud that puts all this access together, and then you add the AL, and the machine learning on top of it, it's really kind of this crazy perfect storm of technologies that are coming together, that are enabling this, which we really couldn't do before, all those pieces weren't there. So if look forward, as CTO, what are some of the things you're excited about, how do you see this evolving, over the next little time, and mid time, I never go longtime, longtime is forever in the future we don't even guess. >> Longtime, I can predict one thing for sure about long time, that whatever we say today will be wrong, in the long-term. Short and medium-term I think we probably will be right. I think short and medium-term, what I see happening, is that AI becoming a part of pretty much every layer of every product, for us for example, as an intelligent RPA platform, AI is embedded in the interaction with the application, interaction with the screen, interaction with the person, interaction with the document, so whichever way we interact with the outside world, as well as how we get better ourselves, AI is embedded in that. And then we use many third-party AI's as our own part to add AI enabled skills, for example understanding if a insurance claim should be denied or not, a credit card should be issued or not. So all these things become part of how AI helps us in day-to-day. So I think that will be the biggest change, I think people, the example that you brought up, right, Google email. I don't think that people predicted that with the first use of AI, in Google, but it is very useful, I use it all the time, because it happens to get better all the time, it knows all my phrases, it knows how I respond, I think that'll happen again and again. >> Right, right, it's just like spell-check, the great unwashed AI that we've all been using for years, and years, and years. Alright Prince, so, the final word is really, I think that's important, is, you're talking about the intelligence. It's not just a process that we apply software to, but this ongoing iterative intelligence applied, whether it's machine learning, or AI, to make it better, and better, and better. It's not just going to be static. >> Not at all, not at all. I think it understands what it needs to be doing, and it then provides ideas on how it could be doing better, and then it integrates those ideas back. Everything gets better over time, and everything that a human finds repetitive, high volume, boring, will eventually get farmed off, to an augmentation, additional worker, additional system. >> And oh, by the way, the number of open rec's is still not going to go down, right? >> Because, you know, if you remember the ATM world, as an ATM started coming in people started worrying tellers will go away and the number of jobs will go down. Actually banks are doing really well, right, and they started hiring more people. The nature of the job changes, the value that humans provide go higher and higher, but that's what happens, eventually. >> Alright Prince, congratulations for you for jumping on a rocket ship, I'm sure it's going to be (laughs) a really fun ride, and having us here at the show. >> Excellent, thank you Jeff, thank you so much. >> Alright, he's Prince, I'm Jeff, your watching theCube, we're on Automation Anywhere Imagine 2019 in midtown Manhattan, thanks for watching, we'll see you next time. (energetic music)

>> From New York City, it's theCUBE. Covering Automation Anywhere Imagine. Brought to you by Automation Anywhere. >> We're in midtown Manhattan at Automation Anywhere Imagine 2019. It's about 1,500 people talking about RPA which is part of the story but it's really a much broader story than RPA. It's about the ecosystem, it's about new ways to work, and really, RPA is an enabler but that's not the story in and of itself. It's really about helping people do their jobs better like a whole bunch of other tools that've come out over the years to help us out. We're excited to have a return guest who was here with us last year. He's Ankur Kothari, co-founder, another co-founder and chief revenue officer of Automation Anywhere. Great to see you again. >> Always good to see you, Jeff. >> So, it's been a year since last we spoke in June. >> We've been way less on ground, a lot on the flight. >> Yeah. >> Yeah. >> And, you brought in a bunch of money. You got a lot of resources really to support you now. So, how has that kind of changed? You know, you guys have grown a lot. You've put $500 million in the bank. How's that changing what you're working on now? >> Well, we are deploying that capital in three major ways. One is global expansion. We have now grown into, we have offices now in more than 30, 35 countries, 30 plus countries. So we are getting closer to all our customers worldwide in all top 30 economies and major business hubs where we are now we have opened offices, so, that's one. We are using this capital to build our ecosystem with our partners and all the developers. And, obviously we have invested a lot in our product. Taking the product stack more and more broader which allows us to automate any process that can be automated. >> Yeah, I mean, it's a great resource that you have at your disposal now. And Mihir talked about a lot of kind of higher level topics which I found really good in the keynote, really reframing RPA and personal digital assistance, if you will, around it's just another tool to help people get their job better. And he had some ridiculously sad stats about how much time that people are being asked to do robotic tasks which they really shouldn't be doing those tasks. >> Yes. >> There's much higher value stuff. It's not really rip-and-replace, it's really augment and help people do better. >> Augmenting, yes, yes, absolutely, generally most of these journeys start with this goal of productivity and rightly so. There's nothing wrong with that but as you scale in this journey and you start working, as you onboard more digital workers, digital colleagues as we like to call it, you find that the conversation in your organization changes from productivity to progress because that's what any technological transformation is about. It's not just about productivity, it's truly about progressing your team, your company, your industry, your customers forward. >> Right. >> So, that's what you face. And the second big prize on that front is it allows you to make work human. The moment you start automating every process that can be automated, we start using computers what they were designed for, to process things and not just to be used as a system of records. >> Right. >> So, we can do what we are good at. Solving complex problems using our creativity and empathy. >> Right, one of the things I thought was really interesting was the launch of the community addition, which is free. Free for small businesses, free for developers. I can't remember if there's an academic component-- >> Yes. >> Or not, but, you know, you're the guy who's puttin' money in the cash register. I'm sure there were some interesting conversations about having a free community edition. I wonder if you can share some insight 'cause, you know, that's taking money out of the bank, but obviously there's a much larger strategic goal. >> There's a strategic goal. The problem that we are falling in love with is that what would it take for us to accelerate the journey of every company to become a digital enterprise? How do we share in this new bot economy? And, in order to do that, we have to have every person participate in this whole phenomenon. An idea as big as this can not be one company or a few individuals' ideas. So, we have opened up that whole thing for everyone to participate. The community edition allows students, developers, small businesses, everyone to download. They go to our Automation Anywhere University and they can get freely trained and certified. And they can work with a bot. And they can build a bot and form their own opinion. >> Right. >> And have their own point of view. And the belief behind that is that a good idea can come from anywhere or anyone. And those ideas, once they use our product, they can monetize it in our marketplace which is the Bot Store. >> Right. >> So, that it allows everyone to form an opinion, and contribute to this new bot economy. >> It's pretty interesting. One of the topics Mihir touched on in the keynote was that we often think of, you know, kind of applying new technology to today's world, but we often miss, you know, as he said, that now is not the station, it's the train, and it's moving. And by opening it up to developers now, as you said, you're expanding the width, the breadth, and the potential applications of your technology to problems that you guys have never even thought about before. >> Exactly, that's the real thing. We are automating processes that we are doing now but generally it's about automating what we have not even seen. >> Right. >> These processes were designed for people to do. How would a process look when bots are performing there? I live in Silicon Valley and pretty much a computer science guy working on cutting edge. If you asked me 10 years ago would I let any of my family member live in a stranger's house? I would say, no way. Airbnb is one of the largest hotel chains in the world right now. >> Right, right. >> What that tells you is that human brain mind thinks linearly unless you give them something that allows humans to think exponentially. >> Right >> And that's the whole idea of beauty of technology. It allows us to think exponentially, and once our brain stretch there, then it's not possible to go back. >> Well, the other thing I think is really smart on your play is the competition for developers' attention, right? The developers these days have a lot of power and they can choose of a myriad of technologies in which to apply themselves. So, by having this community edition and opening it up is one part, but the other piece that I think is interesting is the whole bot economy. And I think you opened up the store last time we were here last year. >> Yes. >> Now you're putting money behind it so people can sell. In fact, we had a customer on earlier who's developing some stuff but they can augment that investment by actually selling those bots into this store. >> On the Bot Store, yeah. >> So, I wonder if you can talk a little bit more about how that is evolving? Is it kind of matching your vision? Has it accelerated past your vision? >> It is accelerating much faster than what we imagined first. When we one year ago we launched our marketplace, that is Bot Store. We opened up our University for everyone to get freely trained online. Then we started our community online, which is eight people. And with this community edition, everyone is now participating in it. What that is doing is we believe that more, the one thing that all developers want, is to contribute. Their work to be used by others. >> Right. >> And then, in a Bot Store, it allows them to even monetize it. It allows them to productize it so that personal satisfaction of solving a problem is what the developers get. And such new, creative ideas we are getting once we did that. Yesterday we had Bot Games and more than 250 to 300 developers participated in different games. And they were building these bots on fly, and they were competing. And we believe that when we bring all these people together and we give them a problem, genius comes out. >> Right. >> And it has been true. >> (laughs) So the ecosystem is huge and that's part of why you have your own show. And we go to a lot of shows. We were at Google Cloud a couple weeks ago. So, there's really two components of the ecosystem, traditional ecosystem. You've got the devs we talked about. There's the system integrators and you've got them all here in force. And they don't come out unless they really see a big opportunity. >> Yes. >> And the other part is the ISVs, right? To add all these different components. So, how is that evolving? Where do you see it going over the next year or two? >> It's interesting, you saw today that there was IBM, Microsoft, and Oracle all went on stage with software partnerships, you know Workday. So, we are forming large partnerships with software and how our product works with theirs, and the digital workers are part of that whole equation. And all our service providers and SIs and advisories that've been on this journey with us for the last five to six years and they are ramping up their entire practices to get their customers to become a digital enterprise. So, you see these two different worlds coming together and all the three worlds are working together for the customer to become a digital enterprise. >> Right. >> And, that's the best part. The digital native companies like Amazon, Airbnb, they have got this right. But what about the companies who have been there for 50 years, 100 years? How do they become digital? >> Right. >> And that's a more interesting problem. If you look at the software, and all the service partners and we are working together to solve that problem. So, it's a very interesting mix, an interesting time. And add to that this whole bot economy of developers bringing all these new digital workers. We are seeing the consumption of bot, growing in an exponential way. We are growing multi-force in few months. It's been a great, great ride. >> Right, well, I want to close on that in the last question 'cause you are one of the co-founders. I think there was four founders, if I'm correct. >> Yes. >> And you guys did it a very different way. You basically funded it the best way to fund a company, which is with revenue. >> Yes. >> And customer funded and you didn't go out and get outside money and now you've got this huge round which is actually an A round. >> Yes, it's a... >> So, how does that change the game? I mean, it puts you in a very good spot 'cause you don't have to take that money 'cause you were operating fine. But how does it, from a co-founder point of view, change the trajectory of your journey? >> There is obviously a value that that kind of capital brings because you can grow asymmetrically as well. >> Right, right. >> But the real value, for me, is the five investors who are such tier A, top-tier investors, who are the right partners we have got on this journey. If you think about Goldman Sachs, and NEA, and SoftBank, and General Atlantic which is one of larger growth-- >> Pretty good roster. >> Right. So you get that expertise and you get those partnerships that allows you to think exponentially and grow very fast. So, that's the real value for me in addition to the capital. >> Well, Ankur, thanks for sharing your journey with us. It's really been fun to watch and we're just at another inflection point I think. >> Always great to see you, and again next year. We ought to do this every year. >> All right, very good. >> Bigger and bigger. >> Absolutely, thanks again. >> Thanks a lot. >> He's Ankur, I'm Jeff, you're watching theCUBE. We're at Automation Anywhere in midtown Manhattan. Thanks for watching, we'll see you next time. (upbeat electronic music)

(energetic music) >> From New York City, it's The Cube! Covering Automation Anywhere Imagine, brought to you by Automation Anywhere. >> Hey welcome back, Jeff Rick here with The Cube, we're in midtown Manhattan at Automation Anywhere Imagine 2019, we were here last year for the first time, we're really excited to be back. Since we were here, I think they raised like 550 million dollars, the RPA space is going bananas, and it's a really exciting place to be, both for the company and also for us at Cube, so we're excited to be back, and we got a return visit from last year, she's Neeti Metha, she's the co-founder, we always love to get co-founders, SVP brand strategy and culture, welcome back. >> Good to see you again, Jeff. >> Absolutely. So, first off, congratulations, I mean what a move you guys have made in only one short year. >> Thank you. The space is really taking off, and we are very excited to see the growth. >> So, excited to talk about the technology all day long but you're getting involved in some of the little higher-level discussions which are really really important, we see it in AI, and these are the conversations, I think, are much more important and that's about ethics, and how are these tools being used, what do people need to think about when they're using their tools, we don't just want to qualify bad behavior or bad bias' or bad ways of doing things in the past, that doesn't help so, what are you thinking about, how are you helping customers, what are some of the things they should be thinking about in this space? >> So, two things, one is, I think, society unfortunately has had a lot of unconscious bias in a lot of different ways, you know, it may not be intentional, it may be something that is inherent in the way we behave as a society or a community, or a race, religion, as a gender, it doesn't matter, and somehow, when we do AI and machine learning and we are training these bots, when we feed all this data to them, there are two things that AI helps us with. One is, we get to see it outside-in, so we are looking at it as how the data is looked upon by the machine, and these bias' become a little bit more obvious to us than otherwise, and then two, we can actually take that as a learning point and fix those biases so that we are not always targeting the most populous religion or the most populous race, or the most populous gender at that point, but we are looking at it absolutely gender-neutral, or race-neutral or religion-neutral and so forth, so AI really helps in those two things, one is it allows you to see it and identify it, and two, it allows you to rectify it as you're training these bots to make certain decisions using the analysis and the data that they have at their disposal. >> I'm curious how the outside-in exposes it 'cause for a lot of people, they don't see it, right, that's why the Terma Conch is bias so, is it in the documentation that you maybe never really had to write it down, what are some of the things that suddenly surfaced that, Oh, I didn't really realize we were doing that." >> So two things, one, again, in that sense, the data that we had, there was a lot of data, so having AI and machine learning actually helps us digitize that data and that means that we have a lot more data that can be analyzed, first of all, which was not possible before, and second, we can actually look at that data and cut in and dice it in any way we want to to kind of see these biases a little bit more. When you couldn't have digitized data, then how are you going to have one human brain, for example, look at all the data that was not digitized and analyze it without the digitization, and then actually find analyses around that or find biases around that? So it really does help to digitize that data and, for example, Automation Anywhere's IQ bot helps you digitize dark data or hidden data, and covert it to digitized data and then you can analyze it and do things with that data that you could never before. >> Okay, great. So, one of the things that came up in your great keynote this morning, lot of stuff, I could go on for probably 2 hours, but one of them is really re-thinking this concept of what a bot is, is it digital assistant, or even a digital employee? And thinking of it, not as something that's going to replace what I do per se, but it's just another tool in my toolbox, just like I have a laptop, I have a mobile phone, I have sales force, I have all these other systems, and really thinking of it more that way to offload some of this mundane, soul-crushing work that unfortunately takes up way too much of all of our time. Very different approach than, "This is a substitute for what I do now." >> Technology is always a human enabler, and this is extremely important. So the RPA and the digital workforce is something that we believe that every human who is working could leverage and enable themselves to get to that new level of creativity, that innovation, get rid of the repetitive and mundane and do things that you never could before or you could never get to because of a time perspective. And so, it's extremely important for people to utilize this to actually help themselves, their careers, their own teams, their divisions, their organizations and their societies to get to the next level. >> Right, and open up this productivity gate because, the other thing I think is really funny is, all this conversation about robots taking jobs and yet companies have thousands and thousands of open recs, they can't hire enough people, even with the technology and I'm always drawn to this great invite, we did a Google cloud a couple of years ago, where, when they were starting to scale, they realized they could not do it with people, they just couldn't hire fast enough and had to start incorporating software defined automation, or else they could never take advantage of that. We're seeing that here and that's really part of the whole story and why RPA is so exciting right now, is 'cause you're an enabler for productivity force multiplier. >> That's right and a lot of businesses have certain things that are inherent in their industries, for example, there might be a seasonality requirement, or there might be a requirement where they suddenly have a surge of customers and so forth, and in order to stock that many claims or accounts that they're opening or whatever their process is doing, in order to get that many humans onboard them, train them, at least give them a breathing space to get onboard and actually be responsive to that organization, you can help them by having bots to bridge that gap and allow them to be successful. >> Right. Another interesting stab in here, I got great notes, again it was a terrific keynote, he talked about only 4% of US jobs require a medium level of creativity and I was struck, I remember being in grade school and we watched a movie about people in an auto-manufacturing plant, just the worst kind of monotony they were doing, and this one guy used to load cars on a train and every once in a while he would just drop one on purpose or run the forklift through it just to kind of break up his day. >> Right. >> So, again, the purpose is not to replace, but to really enable people to start to use their brains and be more creative. >> It is to unleash the human potential, and that is what automation will do for it. >> Now, you guys have recently came out with some new research, or if you can give us some of the highlights on some of your new research? >> Absolutely. So, last year, we worked with the Goldsmith's University of London to see if automation, and we believe so, but we wanted to see and validate that automation actually did make work more human. So, did people actually free themselves of their repetitive and mundane and then become more creative and innovative and solve problems that they wanted to and they couldn't before? And the answer was overwhelmingly yes. So this year, we went the next step in that research, and we did a second research, a second wave of research, where we said, "What do organizations, what are the challenges organizations will face if they want to implement this automation and unleash that human potential?" and you should read the research, it's on our website, but it was very very interesting, 72% of people didn't believe that AI or machine learning or automation would be taking over their jobs, yet only 38% of them were exposed or had the opportunity to work with this. So the potential is enormous, technology has to be an organizational change, that's another thing that came out of the research, and corporations should work towards it, but I think this research was very insightful, please do look at it, I think it will be very useful to you. >> So one of the announcements too, that came out today was about the community addition, and I think that's a really interesting play, right, 'cause your introducing a freemium, so people, myself, individuals, educations, businesses, have access to your whole suite for free. I'm sure there was some interesting conversations internally to really make that leap, but it really supports your theme of the democratization of the automation which we hear over and over around data and a lot of pieces of the stack, and so obviously the bigger picture, the bigger opportunity far outweighs a couple of bucks of revenue from this small company or that small company. I wonder if you can kind of share some of the thought behind that? >> Absolutely. This was always part of the strategy, but it was part of the strategy to do it at the right time, when the technology was mature and robust enough one, but when we could actually allow and give that opportunity to every human who wanted to get rid of their repetitive and mundane, give them the opportunity to be better at what they do, to create more and innovate more, and so we are very excited about it, we've had such a great response from the market on it and the idea from the beginning, and I think we are very committed to it, and Automation Anywhere is to create opportunity for automation for everyone. >> That's great. So, last question Neeti, what are you working on in 2019, I mean I don't expect you to raise another half a billion dollars, great year from last time, what are some of your priorities though as we look at the balance of 2019? >> I think this industry is under tremendous growth, I think we are seeing a lot of results, for the customers and for employees, and so we are very very excited, I think it's a great time for the industry, it will create a lot more innovation, we'll have a lot more new things coming out this year, a lot more engagement from all over the world, and it's a super exciting time to be in this industry. >> Great. Well thanks for taking a few minutes out of your busy day and for having us back here at the show. >> Absolutely, my pleasure, Jeff. >> She's Neeti, I'm Jeff, you're watching The Cube, where Automation Anywhere Imagine 2019 in midtown Manhattan. Thanks for watching, see you next time. (energetic music)

>> From New York City, it's theCUBE! Covering Automation Anywhere, Imagine. Brought to you by Automation Anywhere. >> Welcome back everybody, Jeff Frick here with theCUBE, we're in Midown Manhattan at Automation Anywhere Imagine 2019. We were here last year, it's about 1,500 people who are excited to be back, the RPA space is really, really hot as evidenced by tons of investment coming into it and we're excited to have the CEO, fresh of the keynote but here Shukla the CEO and co-founder of Automation Anywhere. Great to see you and great job on the keynote. >> Thank you, great to see you too. >> Yeah, so I wanted to jump into some of the top level themes that you outlined that I think are so important and one of them was this whole concept of democratization of automation. We hear about it in Big Data, we hear about it at citizen developers and you guys are taking it really into the automation space and you had three things that were really important. One, it has to work for anyone. It's got to be available anywhere, which implies on anything. And it has to be available to any company, regardless of size. It sounds like you've really baked those concepts into a lot of the announcements that you've had today and where you're taking the company. So I wonder if you can dive a little bit deeper as to why those are guiding principles. >> Absolutely. I think what guides us there is that we believe that the power of technology lies when it impacts the lives of millions of people and makes them better. So you if you start with that premise, how do you make that possible. Now when you look at any technology that has affected, made millions of lives better, they had these three characteristics in common. Take an example of a personal computer or internet. It was available to anyone, for any kinds of people, any profile of people. It was available anywhere in any device and it was available for any sized company. So we have seen this play out a few times in our lifetime so, we have learned from that, that if our mission is to make power of RPA and AI reach millions of people and make their lives better, if that's the mission then we have to make this possible for anyone, for anywhere and for any sized company. >> And a big piece of that was the announcement of the community version which is free. So I'm sure there were some interesting discussions about moving to a freemium model and actually giving the software free for people that qualify. I wonder if you can talk about those discussions and clearly there's a bigger picture that you're focused on, versus just the revenue for one or two small customers. >> Right, so our community edition is free for small businesses, student and individual developers. And the reason why we did this is for two reasons. One is, we believe the students are our future and they will take this technology forward and we need more and more people with digital skills. So it seemed like the right place to invest and enable them with the next set of technologies. The reason to make it available free for developers is, we believe that today about 95% of processes that we automate are the processes that we do manually today. But that is changing very fast. In three to five years, 30% of things that we will automate will be the things that are not part of our lives today. It is things that we don't know yet, right? >> Right, right. >> And that happens every time. The way we use phones and everything, nobody could've predicted this. So we know that will happen like it happened in internet and other evolution. It will happen in our space as well. And developers are an amazing asset, they are the ones who will discover, find these new ways that none of us know about and they will create this new future in front of our eyes. So it makes sense to empower developers and especially developers are very picky, they want the best software available. They won't settle for anything less and because we have the complete intelligent digital workforce platform that includes the best RPA, artificial intelligence and analytics, (coughs) we thought they would love the power of this combined platform that is not available anywhere else. And true to the cause, as soon as we announced it we had an amazing success. The requests are pouring in from 120 countries worldwide and the adoption has been phenomenal. >> And you mentioned that on stage on the keynote that there's some examples out there where people are not doing automating of processes that they already did but are really starting to get creative in the uses of this tool and I think we see it over and over as you said, people miss the hype recurve, it's hard to see the future and it's hard to apply what we're doing today to what we're going to be doing in the future, because we really don't know. >> That's right. I think sometimes I describe this way to people, that when the new technology comes, people think that new technology is the train and the world is the stations. So the station remains where it is and the tain moves on, right? That's not how real world is. The real world is, the world is a train itself, that's moving forward and technology is one of the, you can say it's the first-- >> The locomotive. >> First locomotive or one of the pieces in it. But the whole world is moving as well. So we often, many of us get this wrong that, we make a mistake to think that, how will this new technology fill in a stationary world where that's not the case, the world is moving. >> The other thing you brought up I thought was pretty interesting is that, this is not to displace workers, it's to enable workers to do better and I couldn't help but think of, just like my PC helps me do my job better, the internet helps me do my job better, my phone and my ERP system all help me do my job better. So, of course, why wouldn't I want a powered AI assistant to help me do my job better. >> That's absolutely true. Look, I have a very extraordinary privilege of seeing this transformation through the eyes of thousands of people who use our platform every day, and I've visited about, of the 2,800 plus customers we have, I have visited hundreds of them and talked to thousands of people on the ground who use this technology. And there is not a single one of them who would go back. And I invariably ask that, after a few discussions I would say "Would you ever consider going back?", and the answer is universal across any country, any verticle. People do not want to go back to, why would you, why would you do a robotic job? And so, it is more clear than ever before that this transformation is certainly not about us, certainly not about bots. It is about empowering people so that they're more productive unlike any other time in human history. Taking it a step further, as you said, compared to where PCs brought us. >> You said, again I could go on your keynote all day long, another great thing you brought up which was just crushing, I think you said that 4% of people have jobs that need some degree of creativity. That is horrible! >> Is it not? Is it not? >> That is horrible. And again to personalize it, you talked about your kids and this world that they're going to be coming into, why would we want to put them into a robotic job? >> Right. So the data shows that only 4% of US jobs require medium creativity. And as a parent that is, I'm troubled by it because we, like all parents, we tell our children they can do anything. What do we mean by they can do anything? If they get one of those 4% jobs, that's still a medium level of creativity so probably we hope they get 4.1% of those jobs that require full human capacity, yeah? >> Right, right. >> That's not anything they can do. They don't have as many opportunities that they should have. And I think we need to create a better world with more opportunities for our children. I'll settle at 40% but 4% isn't acceptable. >> So a little bit about the business, cause the deeper stuff I think is more interesting, but the business is doing well, again. Since we last met you had this huge A round, I think someone said "The largest A round ever.". You put over half a billion dollars into the bank. A, what is that show in terms of validation from the marketplace, for the opportunities you guys are addressing? And then B, with great resources comes great responsibility, you know? So what are you doing next as you look into 2019, what are some of your top priorities? >> So we have been very fortunate to get the, as you mentioned about 550,000,000 in our series A round and it is, if not the largest, one of the largest series A round ever. I think it shows, first of all it's a validation of our market leadership and the growth of the category both. We continue to invest heavily in three areas. First is our RND investment continues to grow, especially in AI and making RPA accessible to millions. So those investments continue. We are significantly investing in the global expansion across, now we have offices in about 30, 35 countries worldwide. And the third is, we will carefully look at acquiring maybe new technologies and new acquisitions to make our digital labor platform more complete and offer customers more similar solutions. >> Right. So last question before I let you go, I know they got you flying back to back to back all day. It's really about the ecosystem. The Partner Ecosystem, you've got obviously a bunch of system integrators here which validates that they see a huge opportunity, but talk about how you're developing an ecosystem to extend the reach beyond just the people that work at Automation Anywhere. >> So we have two important pillars to our ecosystem. We have our site system integrators. We bought 700 plus partners who provide invaluable experience in various domains all over the world. Many of them provide the bots and the bot store that are domain specific, process specific, ready to tax and audit and finance and accounting and supply chain and oil and gas and telcos, across all industries. So they bridge the gap between technology and the customer specific, domain specific process. That's one very important pillar. The second important pillar is the software companies. So we have a great deal of partnerships with many of them, for example we have a continued partnership with IBM, with their digital business automation group. We recently announced partnership with Workrave that is very important to us. It has an enormous potential of how when you combine best in class, HR and cloud finance with best in class intelligent digital workforce. The possibilities of value creation is enormous. We today announced our partnership with Oracle and we extended our partnership with Microsoft on multiple fronts, and there are many more as well. So the two key pillars to our creating an ecosystem. Again, all of this is, almost everything that we do comes down to a single mission statement which is, how do we take the power of RPA and AI to millions of people and make their life better? >> Great, great mission. So again, thanks for having us. Congratulations on a great event and we look forward to watching the next year unfold. >> Thank you, I look forward to it (laughter) >> Alright he's been here, I'm Jeff, you're watching theCube. We're at Automation Anywhere Imagine 2019 in Midtown Manhattan, thanks for watching. We'll see you next time.

>> From New York City, it's the cube, covering automation anywhere, Imagine brought to you by automation anywhere. >> Hey welcome back everybody Jeff Rick here with theCUBE. We're in midtown Manhattan at the automation anywhere, imagine 2019 event we were here last year, it's grown quite a bit and we're excited to be back. Our very first guest of today is Kashif Maboob, he is the VP Product Marketing and Global Head of our PA at automation anywhere. Great to see you. >> Nice to be here. >> Yeah so a year ago, in June I looked up the date and since June you guys have had a very exciting year, you raised like a half a billion dollars the RPA space is blowing up and this conferences I think outgrowing the venue so it's been quite a years. >> It certainly has been quite a year, yes we did have the largest Series A for a enterprise software company ever we are still on the Series A which is quite significant in our industry at the moment, the growth has been phenomenal, last year when you and I met here we had nine offices we have 35 offices today we have... we are looking at exiting 2019 with about 3,000 employees the numbers just speak for themselves. RPA that category itself has been at a growth space that I certainly have never seen before. >> So here had a great keynote a little bit earlier and he touched on a couple of really key topics and he did this last year too when he talked about, truly transformational technology shifts. And he talked about mobile before and personal computing and some of these things and he had three kind of things, it has to work for everyone it must be available anywhere and it must work for any size company and you guys are making real concrete moves into that area and one thing he talked about, is this concept of community edition. So i wonder if you can give us a little bit more flavor what is community edition, why is it important automation anywhere? >> Absolutely the concept, the vision that we are driving towards, is automation for all. For all types of users, by that we mean business user, IT user, developer. You don't have to be somebody who is proficient at coding you don't have to be somebody who is doing just one part of the business. Anybody in the business should be able to pick up the software and start using it. So with that concept in mind, we then thought about all types of businesses. Because until not too long ago RPA was a realm for the largest of the large companies. So last year fourteen fifteen hundred of our enterprises that number has grown to about 2,800 now. Still some of the largest companies in the world. Now taking it further is also talking about the various channels through which we deliver our software. so not just on premises which is most of RPA today but going forward enabling cloud delivery models. So with all that combined what is the fastest way to get people started on it and that is to remove all barriers to remove all friction and that's where community Edition comes in. It's a free product, it is the entire digital workforce platform. So not just RPA but RPA with AI and with analytics all combined, with a mobile app ready system. So when you when you sign up or download, whichever way you want to call it. You are actually signing up into a very robust, very comprehensive the most complete digital workforce platform that enables business users, students, educators, but perhaps most importantly developers to start developing their own bots, their own software robots. A community edition is just one piece of a larger ecosystem strategy that we have, that includes the community edition. So download the software or sign up into it and start building, but where do you learn how to build bots? well, we have Automation Anywhere University. We have about 175,000 students signed up already. We're fast becoming the world's largest University as well and then... So you have free courses available, you can get certifications as a trainer as a developer, as a business user. Once you have that training you can start developing bonds. Let's say you have questions that you want answered or you feel like the expert who should be sharing his or her knowledge for that we have the A people community, it's again RPA's largest community in the world, seventy-five thousand plus users already so that's piece number three and last but not the least, you've downloaded the Community Edition, you've become proficient in building boards, you're sharing knowledge and your expertise what's the next step? The next step is to build bots that the rest of the world can use so we are we have bought stores that we launched last year >> right >> so you can actually upload your bots and you will start monetizing the bots so it isn't a virtuous cycle, it's an ecosystem of free software, free education, free community, in a marketplace that lets you share your knowledge your expertise with the world. So that's our vision that's what we are very much into it and more than a vision it's in practice today. >> Right it's an interesting play right because we always hear about the democratization of data, and the citizen developer, so you guys are really talking about the democratization of automation and I'm sure there were some interesting conversations we're going to have the CFO on later, about you know taking some revenue off the table to enable kind of this community outreach to go out and offer really a full stacks almost like a freemium, classic kind of freemium play, to let people and as you said developers, schools, small businesses get involved in this. What if you could talk about kind of the strategic reason that you're giving up some short-term revenue for obviously a much potential bigger gain down the road. >> So a great point , if you look at the vision, the vision is to automate any process that can be automated right. Is to automate any process any organization that should be automated so what does that mean? That means an enormous workforce that is RPA ready. RPA educated that has knowledge of RPA and not just RPA but any automation per se because AI is included in here. >> Right >> So the only way we can reach that goal, of having millions and millions of users using not just our product, but any RPA product is to educate them to get products in their hands and so we can't think short term in that way. Our our vision is multi-decade vision. And its enormous vision as you as you heard also you mentioned so it's automation for all. For any business size and through any delivery channel >> Right >> And that's where the strategy is that's why we launched Community Edition and you will see a lot more coming down the pipeline as well >> Right So the next big theme is cloud right, we were both at the Google cloud show, last week there you got an announcement here about Oracle cloud and then here talked about, your guys own cloud so I wonder if you can talk a little bit about kind of the cloud strategy and then some of these different options that you guys are enabling for a cloud enabled version of automation anywhere. >> Absolutely so that's a big step just like freeing up our software, through community edition, we need to open a channel through which anybody can have software available so so you don't have just the option of on-premise software, but cloud ready web ready software so for that we announced today, the intelligent automation cloud. The the focus is simplicity, security and scalability. Those three things are critical for any business should be simple enough for anybody to use the software without having to download and install and maintain and so they're big huge cost IT costs for maintaining and price of it >> Right >> So removing that cost, that's what we mean by a zero footprint software it's simple but simple does not mean it's weak or its anything like that. Simple mean is powerful, easy enough to use, intuitive enough to use for a business user >> Right >> Who is who's expertise lives in the process, not necessarily in the coding and scripting environment >> Right >> On the other hand giving the the developers a very robust and IDE you know development environment so that all users, the business user the developer and the IT manager they all get the capability. Security is built-in. We cannot have robust security if you're dealing with world's largest financial organization nine out of ten largest banks, are already in business with us so security is paramount. Audit compliance is paramount >> Right >> Audit ease is paramount and last but not the least is the scalability. So cloud provides us and our customers infinite scale. So simplicity, security, scalability, delivered through cloud and an intelligent cloud not just a cloud that is basic, but cloud where AI is built in >> Right >> Where cognitive capabilities are built in so that's that's a vision that's the goal >> Right but it's and even more of that it's just choice right depending on what the customer needs what their particular application is, within a within a single customer or a single entity pick a large bank, they may have some implementations behind the firewall, on prem they might have some, on your cloud they might have some on some of these big public clouds. You're really offering now the choice it's not necessarily a locked in delivery strategy. >> So we are certified with the five largest cloud platforms available today. Whether it's Google, Oracle, Amazon Web Services, Azure, you will see Microsoft talking here today you will hear from IBM executives here today. Very close partnerships with these organizations >> Right >> So not only that we are technology partners, but we are certified with their cloud platforms which makes which gives our customers the peace of mind. >> Right >> That if we are certified, say with AWS Amazon Web Services, the security that's built into Amazon Web Services, the scalability that comes out of it, the 99.99% uptime and all of those amazing things that amazon has invested in >> Great >> Over the years and now available to our customers as well >> Right >> So that's that's an important factor. >> A lot going on since we last that down a year ago but let's let's look at forward again and I think I asked you last year, you know what are we going to be talking about 2019? So what's coming next? I mean you guys have a huge war chest, you're in a very hot space, you have a lot of momentum Like how you said you doubled your offices in a year, hiring like mad, so what's next? what are you what are you working on in the near term, and the mid term? >> So we started with Community Edition a month ago so in a month we have about 12,000 signups and downloads which is very significant for our enterprise business. It's from throughout the world but in a month's time we are coming out with one of our most the biggest releases if you will ever and that's where we introduce the cloud, that's where we introduce for the business user, a completely web-based interface, which is what we call bot sketch, that gives you the ability, to drag and drop and build your process and in the backend we will develop the bot the software robot for you so it's sort of a bridge between a business user, and she might be on the accounting side or billing side but she's the expert in knowing her own process but she's not a scriptor, she's not a coder she's not a developer, her area of expertise is is the process itself >> Right >> It could be a logistics process , it could be an HR process and she can sketch out their process just like building a workflow and once she finishes her work and she's complete with her workflow or her process end to end, the the development side can take over and the code is already written for them at that point the developer can bring in their own Python code, can run it on Linux, in IT is the third user of course and they can see the entire environment so we are launching an environment that is ready for business that's robust enough for for the developer and secure and gives peace of mind to the IT so that's a major release it of course comes with our built-in security, cloud management and all of that so >> Right >> That's what we are rolling up to and Community Edition is there and you will see more and more talk about digital worker, you earlier you saw me here and it described the digital worker, bot store is there, it's the first-ever automation marketplace so there are lots of firsts >> Right >> And there are lots of the biggest and the largest so we are running out of you know superlatives to use here. I'm in marketing of course, so I have to be careful what I what I come up with >> That's right there's people playing bingo probably so we have to careful that they don't fill up their card. I just want to give you the last take you know when we talk a year ago you talked about three things, about RPA by itself, no kind of cognitive automation and in incorporating you know machine learning and artificial intelligence and then smart analytics and as you're talking and I'm listening, you know I don't even necessarily need to build the body, I mean you just kind of built around the bot but now I can I can get somebody else's bot, now you're talking about actually building the bot for me so you you're leveraging a lot of these, core technologies to power the compute and cloud to actually help me build the bot, taking me one step further where I just need to know my process to be able to start to implement my own digital assistants and and add automation to my world. >> Absolutely so the story is not the bot, the story is always the customer, looking at the customers pain point and what can we do to solve that pain point. How can we make the process more efficient, better faster cheaper right so the bot is a vehicle for us to really enable our customers, to really simplify their lives so that as Mahir mentioned, we as humans can do more cognitive more intelligent work >> Right >> That's the vision >> Right >> and everything that we are announcing today, everything that we have done in the past 15 years that we've been business and our vision is all about you know a fanatical customer focus, we have a large partner base as well we work with largest advisories over 700 partners so if you look at the overall picture it's again building an ecosystem for our customers where they are not tied to one thing >> Right >> We are not we are trying to open it up it's an open platform, we work with best-of-breed, at the same time we provide our customers readiness with AI and security right out of the box as well if they already have a Best of Breed system installed, we will work with that, if they would like to work with our systems, we will work they have capability there so it's a it's a very open approach, it's a very flexible approach because there's no way we you cannot tie down your customer and expect them to stay with you. We want to enable them to automate their process in the most efficient way possible. >> Yeah well congratulations, it's quite a ride and I think the real fun stuffs just getting started. >> Yes absolutely thank you. >> All right thanks again. >> All right, he's Kashif I'm Jeff you're watching the cube were on a mission anywhere, imagine 2019 in midtown Manhattan. Thanks for watching, see you next time (upbeat music)

>> Live from Midtown Manhattan, it's theCUBE. Covering BigData New York City 2017. Brought to you by SiliconANGLE Media and its ecosystem sponsors. (calm electronic music) >> Basil Faruqui, who's the Solutions Marketing Manger at BMC, welcome to theCUBE. >> Thank you, good to be back on theCUBE. >> So first of all, heard you guys had a tough time in Houston, so hope everything's gettin' better, and best wishes to everyone down in-- >> We're definitely in recovery mode now. >> Yeah and so hopefully that can get straightened out quick. What's going on with BMC? Give us a quick update in context to BigData NYC. What's happening, what is BMC doing in the big data space now, the AI space now, the IOT space now, the cloud space? >> So like you said that, you know, the data link space, the IOT space, the AI space, there are four components of this entire picture that literally haven't changed since the beginning of computing. If you look at those four components of a data pipeline it's ingestion, storage, processing, and analytics. What keeps changing around it, is the infrastructure, the types of data, the volume of data, and the applications that surround it. And the rate of change has picked up immensely over the last few years with Hadoop coming in to the picture, public cloud providers pushing it. It's obviously creating a number of challenges, but one of the biggest challenges that we are seeing in the market, and we're helping costumers address, is a challenge of automating this and, obviously, the benefit of automation is in scalability as well and reliability. So when you look at this rather simple data pipeline, which is now becoming more and more complex, how do you automate all of this from a single point of control? How do you continue to absorb new technologies, and not re-architect our automation strategy every time, whether it's it Hadoop, whether it's bringing in machine learning from a cloud provider? And that is the issue we've been solving for customers-- >> Alright let me jump into it. So, first of all, you mention some things that never change, ingestion, storage, and what's the third one? >> Ingestion, storage, processing and eventually analytics. >> And analytics. >> Okay so that's cool, totally buy that. Now if your move and say, hey okay, if you believe that standard, but now in the modern era that we live in, which is complex, you want breath of data, but also you want the specialization when you get down to machine limits highly bounded, that's where the automation is right now. We see the trend essentially making that automation more broader as it goes into the customer environments. >> Correct >> How do you architect that? If I'm a CXO, or I'm a CDO, what's in it for me? How do I architect this? 'Cause that's really the number one thing, as I know what the building blocks are, but they've changed in their dynamics to the market place. >> So the way I look at it, is that what defines success and failure, and particularly in big data projects, is your ability to scale. If you start a pilot, and you spend three months on it, and you deliver some results, but if you cannot roll it out worldwide, nationwide, whatever it is, essentially the project has failed. The analogy I often given is Walmart has been testing the pick-up tower, I don't know if you've seen. So this is basically a giant ATM for you to go pick up an order that you placed online. They're testing this at about a hundred stores today. Now if that's a success, and Walmart wants to roll this out nation wide, how much time do you think their IT department's going to have? Is this a five year project, a ten year project? No, and the management's going to want this done six months, ten months. So essentially, this is where automation becomes extremely crucial because it is now allowing you to deliver speed to market and without automation, you are not going to be able to get to an operational stage in a repeatable and reliable manner. >> But you're describing a very complex automation scenario. How can you automate in a hurry without sacrificing the details of what needs to be? In other words, there would seem to call for repurposing or reusing prior automation scripts and rules, so forth. How can the Walmart's of the world do that fast, but also do it well? >> Yeah so we do it, we go about it in two ways. One is that out of the box we provide a lot of pre-built integrations to some of the most commonly used systems in an enterprise. All the way from the Mainframes, Oracles, SAPs, Hadoop, Tableaus of the world, they're all available out of the box for you to quickly reuse these objects and build an automated data pipeline. The other challenge we saw, and particularly when we entered the big data space four years ago was that the automation was something that was considered close to the project becoming operational. Okay, and that's where a lot of rework happened because developers had been writing their own scripts using point solutions, so we said alright, it's time to shift automation left, and allow companies to build automations and artifact very early in the developmental life cycle. About a month ago, we released what we call Control-M Workbench, its essentially a community edition of Control-M, targeted towards developers so that instead of writing their own scripts, they can use Control-M in a completely offline manner, without having to connect to an enterprise system. As they build, and test, and iterate, they're using Control-M to do that. So as the application progresses through the development life cycle, and all of that work can then translate easily into an enterprise edition of Control-M. >> Just want to quickly define what shift left means for the folks that might not know software methodologies, they don't think >> Yeah, so. of left political, left or right. >> So, we're not shifting Control-M-- >> Alt-left, alt-right, I mean, this is software development, so quickly take a minute and explain what shift left means, and the importance of it. >> Correct, so if you think of software development as a straight line continuum, you've got, you will start with building some code, you will do some testing, then unit testing, then user acceptance testing. As it moves along this chain, there was a point right before production where all of the automation used to happen. Developers would come in and deliver the application to Ops and Ops would say, well hang on a second, all this Crontab, and these other point solutions we've been using for automation, that's not what we use in production, and we need you to now go right in-- >> So test early and often. >> Test early and often. So the challenge was the developers, the tools they used were not the tools that were being used on the production end of the site. And there was good reason for it, because developers don't need something really heavy and with all the bells and whistles early in the development lifecycle. Now Control-M Workbench is a very light version, which is targeted at developers and focuses on the needs that they have when they're building and developing it. So as the application progresses-- >> How much are you seeing waterfall-- >> But how much can they, go ahead. >> How much are you seeing waterfall, and then people shifting left becoming more prominent now? What percentage of your customers have moved to Agile, and shifting left percentage wise? >> So we survey our customers on a regular basis, and the last survey showed that eighty percent of the customers have either implemented a more continuous integration delivery type of framework, or are in the process of doing it, And that's the other-- >> And getting close to a 100 as possible, pretty much. >> Yeah, exactly. The tipping point is reached. >> And what is driving. >> What is driving all is the need from the business. The days of the five year implementation timelines are gone. This is something that you need to deliver every week, two weeks, and iteration. >> Iteration, yeah, yeah. And we have also innovated in that space, and the approach we call jobs as code, where you can build entire complex data pipelines in code format, so that you can enable the automation in a continuous integration and delivery framework. >> I have one quick question, Jim, and I'll let you take the floor and get a word in soon, but I have one final question on this BMC methodology thing. You guys have a history, obviously BMC goes way back. Remember Max Watson CEO, and Bob Beach, back in '97 we used to chat with him, dominated that landscape. But we're kind of going back to a systems mindset. The question for you is, how do you view the issue of this holy grail, the promised land of AI and machine learning, where end-to-end visibility is really the goal, right? At the same time, you want bounded experiences at root level so automation can kick in to enable more activity. So there's a trade-off between going for the end-to-end visibility out of the gate, but also having bounded visibility and data to automate. How do you guys look at that market? Because customers want the end-to-end promise, but they don't want to try to get there too fast. There's a diseconomies of scale potentially. How do you talk about that? >> Correct. >> And that's exactly the approach we've taken with Control-M Workbench, the Community Edition, because earlier on you don't need capabilities like SLA management and forecasting and automated promotion between environments. Developers want to be able to quickly build and test and show value, okay, and they don't need something that is with all the bells and whistles. We're allowing you to handle that piece, in that manner, through Control-M Workbench. As things progress and the application progresses, the needs change as well. Well now I'm closer to delivering this to the business, I need to be able to manage this within an SLA, I need to be able to manage this end-to-end and connect this to other systems of record, and streaming data, and clickstream data, all of that. So that, we believe that it doesn't have to be a trade off, that you don't have to compromise speed and quality for end-to-end visibility and enterprise grade automation. >> You mentioned trade offs, so the Control-M Workbench, the developer can use it offline, so what amount of testing can they possibly do on a complex data pipeline automation when the tool's offline? I mean it seems like the more development they do offline, the greater the risk that it simply won't work when they go into production. Give us a sense for how they mitigate, the mitigation risk in using Control-M Workbench. >> Sure, so we spend a lot of time observing how developers work, right? And very early in the development stage, all they're doing is working off of their Mac or their laptop, and they're not really connected to any. And that is where they end up writing a lot of scripts, because whatever code business logic they've written, the way they're going to make it run is by writing scripts. And that, essentially, becomes the problem, because then you have scripts managing more scripts, and as the application progresses, you have this complex web of scripts and Crontabs and maybe some opensource solutions, trying to simply make all of this run. And by doing this on an offline manner, that doesn't mean that they're losing all of the other Control-M capabilities. Simply, as the application progresses, whatever automation that the builtin Control-M can seamlessly now flow into the next stage. So when you are ready to take an application into production, there's essentially no rework required from an automation perspective. All of that, that was built, can now be translated into the enterprise-grade Control M, and that's where operations can then go in and add the other artifacts, such as SLA management and forecasting and other things that are important from an operational perspective. >> I'd like to get both your perspectives, 'cause, so you're like an analyst here, so Jim, I want you guys to comment. My question to both of you would be, lookin' at this time in history, obviously in the BMC side we mention some of the history, you guys are transforming on a new journey in extending that capability of this world. Jim, you're covering state-of-the-art AI machine learning. What's your take of this space now? Strata Data, which is now Hadoop World, which is Cloud Air went public, Hortonworks is now public, kind of the big, the Hadoop guys kind of grew up, but the world has changed around them, it's not just about Hadoop anymore. So I'd like to get your thoughts on this kind of perspective, that we're seeing a much broader picture in big data in NYC, versus the Strata Hadoop show, which seems to be losing steam, but I mean in terms of the focus. The bigger focus is much broader, horizontally scalable. And your thoughts on the ecosystem right now? >> Let the Basil answer fist, unless Basil wants me to go first. >> I think that the reason the focus is changing, is because of where the projects are in their lifecycle. Now what we're seeing is most companies are grappling with, how do I take this to the next level? How do I scale? How do I go from just proving out one or two use cases to making the entire organization data driven, and really inject data driven decision making in all facets of decision making? So that is, I believe what's driving the change that we're seeing, that now you've gone from Strata Hadoop to being Strata Data, and focus on that element. And, like I said earlier, the difference between success and failure is your ability to scale and operationalize. Take machine learning for an example. >> Good, that's where there's no, it's not a hype market, it's show me the meat on the bone, show me scale, I got operational concerns of security and what not. >> And machine learning, that's one of the hottest topics. A recent survey I read, which pulled a number of data scientists, it revealed that they spent about less than 3% of their time in training the data models, and about 80% of their time in data manipulation, data transformation and enrichment. That is obviously not the best use of a data scientist's time, and that is exactly one of the problems we're solving for our customers around the world. >> That needs to be automated to the hilt. To help them >> Correct. to be more productive, to deliver faster results. >> Ecosystem perspective, Jim, what's your thoughts? >> Yeah, everything that Basil said, and I'll just point out that many of the core uses cases for AI are automation of the data pipeline. It's driving machine learning driven predictions, classifications, abstractions and so forth, into the data pipeline, into the application pipeline to drive results in a way that is contextually and environmentally aware of what's goin' on. The history, historical data, what's goin' on in terms of current streaming data, to drive optimal outcomes, using predictive models and so forth, in line to applications. So really, fundamentally then, what's goin' on is that automation is an artifact that needs to be driven into your application architecture as a repurposable resource for a variety of-- >> Do customers even know what to automate? I mean, that's the question, what do I-- >> You're automating human judgment. You're automating effort, like the judgments that a working data engineer makes to prepare data for modeling and whatever. More and more that can be automated, 'cause those are pattern structured activities that have been mastered by smart people over many years. >> I mean we just had a customer on with a Glass'Gim CSK, with that scale, and his attitude is, we see the results from the users, then we double down and pay for it and automate it. So the automation question, it's an option question, it's a rhetorical question, but it just begs the question, which is who's writing the algorithms as machines get smarter and start throwing off their own real-time data? What are you looking at? How do you determine? You're going to need machine learning for machine learning? Are you going to need AI for AI? Who writes the algorithms >> It's actually, that's. for the algorithm? >> Automated machine learning is a hot, hot not only research focus, but we're seeing it more and more solution providers, like Microsoft and Google and others, are goin' deep down, doubling down in investments in exactly that area. That's a productivity play for data scientists. >> I think the data markets going to change radically in my opinion. I see you're startin' to some things with blockchain and some other things that are interesting. Data sovereignty, data governance are huge issues. Basil, just give your final thoughts for this segment as we wrap this up. Final thoughts on data and BMC, what should people know about BMC right now? Because people might have a historical view of BMC. What's the latest, what should they know? What's the new Instagram picture of BMC? What should they know about you guys? >> So I think what I would say people should know about BMC is that all the work that we've done over the last 25 years, in virtually every platform that came before Hadoop, we have now innovated to take this into things like big data and cloud platforms. So when you are choosing Control-M as a platform for automation, you are choosing a very, very mature solution, an example of which is Navistar. Their CIO's actually speaking at the Keno tomorrow. They've had Control-M for 15, 20 years, and they've automated virtually every business function through Control-M. And when they started their predictive maintenance project, where they're ingesting data from about 300,000 vehicles today to figure out when this vehicle might break, and to predict maintenance on it. When they started their journey, they said that they always knew that they were going to use Control-M for it, because that was the enterprise standard, and they knew that they could simply now extend that capability into this area. And when they started about three, four years ago, they were ingesting data from about 100,000 vehicles. That has now scaled to over 325,000 vehicles, and they have no had to re-architect their strategy as they grow and scale. So I would say that is one of the key messages that we are taking to market, is that we are bringing innovation that spans over 25 years, and evolving it-- >> Modernizing it, basically. >> Modernizing it, and bringing it to newer platforms. >> Well congratulations, I wouldn't call that a pivot, I'd call it an extensibility issue, kind of modernizing kind of the core things. >> Absolutely. >> Thanks for coming and sharing the BMC perspective inside theCUBE here, on BigData NYC, this is the theCUBE, I'm John Furrier. Jim Kobielus here in New York city. More live coverage, for three days we'll be here, today, tomorrow and Thursday, and BigData NYC, more coverage after this short break. (calm electronic music) (vibrant electronic music)

>> From Times Square, in the heart of New York City, it's theCUBE. Covering Imagine 2018. Brought to you by Automation Anywhere. >> Welcome back everybody, Jeff Frick here with theCUBE, we are at Automation Anywhere in midtown Manhattan, 2018, excited to have our next guest, he's Kevin Kroen, he's partner of financial services, intelligent automation leader at PWC, Kevin, great to see you. >> Thank you. >> So financial services seems to be a theme, we're here in Manhattan, why is financial services an early adopter or maybe a frequent adopter or an advanced adopter of the RPA technology? >> Sure, so I think as we see our financial services clients and their agendas, there's been a huge focus on productivity and simplifying their overall operating model over the past couple of years. Banks in particular have gone through several years of having to focus their spending on non discretionary manners like regulatory compliance and risk management. And what that's generated is a need, as they started looking towards the next generation to really start thinking about what they're gonna look like in a post regulatory environment. And automation has quickly risen to the top of the agenda. >> What they're gonna look like in a post regulatory environment. >> Yes. >> Why a post regulate? >> Well I mean if you look through, you know what banks have had to deal with in term of Dodd-Frank, in terms of CCAR, you know, the regulation from federal reserve, these are things that took a lot of spending both on implementing operational processes and on implementing technology. A lot of that work is starting to you know, the banks are putting that behind themselves and so as they look forward and look at how they're going to gain more profitability in the future, the challenge becomes, there's not necessarily a new set of product innovation coming in, and so you have to really look at the expense line. >> Right. >> And so because of that automation has risen to the top of that agenda and so this continues to be one of the top areas of interest that we're getting from our clients. >> Right, so when you say post regulatory, you mean like a new regulation that they have to respond to, not that they're suddenly not gonna be regulated. >> There's not a lot of new regulations coming in right now, especially- >> That pesky one last week, GDRP. >> Yeah but in the US we're in an environment right now, there was just, you know, the revisions to the Dodd-Frank bill that were passed a lot of regulatory rules were actually being loosened so you don't necessarily have an increase in dollars that are going to be going into that. >> Right right, so it just always fascinates me, right, I thought ERP was supposed to wring out all the efficiency in our systems but that was not the case, not even by a long shot and now we continue to find these new avenues for more efficiency and clearly this is a big one that we've stumbled upon. >> Yeah, you know I think it's interesting, when you look at big technology investment over the last decade or two, you could argue a lot of efforts been focused at what I call the kind of core infrastructure and core plumbing so you know, how do I consolidate data into a single location? How do I make sure that data reconciles into different parts of my organization but that like kind of last mile of what someone does as part of their day to day business process was never really addressed, you know or is only addressed in pieces, and so I think as you start looking at the productivity term and how you actually start getting efficiency, we have very few clients that are saying, I want to take on that next big ERP type of limitation or I'm ready to spend 300 million dollars on a new project, they're looking to try to get the most value out of what they already have and they're actually looking to look at that last mile and how can they actually gain some benefit off it so the RPA technologies I think we're one of the catalysts of just being the perfect technology in the right place at the right time from a current business environment, a current technology spend perspective. >> Yeah it's pretty interesting Mihir was talking about, you know one of the big benefits is that you can take advantage of your existing infrastructure, you know, it's not a big giant rip and replace project but it's, again, it's this marginal incremental automation that you just get little benefit, little benefit, little benefit, end of the day, turns into a big benefit. >> Yeah, and I think that's, you know, it's quick, it's fast, it's, you know it can be implemented in an agile manner and you know, our clients are continuously telling us over and over again, they're willing to invest, but they wanna invest where they're gonna see a tangible payback immediately. >> Right. >> And I think when you start to talk the concept of digital transformation, it can mean a lot of different things to a lot of different people but there are big picture changes that could be made, those may be longer term trends but they're more immediate things and more immediate benefits that could be gained and I think that's really the sweet spot of where RPA and Automation Anywhere fall into. >> I was just looking up Jeff Immelt in his key note said this is the easy fountain money of any digital transformation project, I think that was the quote, that you'll ever do. That's a pretty nice endorsement. >> Yeah and it's, as we go out, we talk to CFOs, COOs, CIOs, you know, it's, the value proposition is really attractive because, you know, there have been, there's a track record of failed, technology projects failed big transformation projects and, you know, no one wants to necessarily risk their career on creating the next big failure and so I think using technology like RPA almost as an entry point or kind of like a gateway drug into the digital world, see the benefits, start to understand what are some of the business problems and historical kind of, you know, things you're trying to untangle in your infrastructure, attack that and then, you know, start to layer on additional things on top of that, once you get good with RPA and then you can start figuring out, okay, that's they gateway to artificial intelligence, okay how do I start to apply AI across my organization? As you get beyond AI, okay, how do I get into, more advanced state infrastructure and you can start thinking about this world where you can, you know, rather than do the big, five year project where you're gonna try to solve world hunger, it gives you a chance to kind of incrementally go digital over time and I think that's definitely the direction we see a lot of our clients wanting to go in. >> Right, Kevin I want to get your feedback on another topic that came up again in the keynote, was just security, you know it was like the last thing that was mentioned, you know, like A B C D E F G and security, financial services, obviously security is number one, it's baked into everything that everyone's trying to do now, it's no longer this big moat and wall, but it's got to be everywhere so I'm just curious, from the customer adoption point of view, where does security come up in the conversation, has it been a big deal, is it just assumed, is there a lot of good stuff that you can demonstrate to clients, how does security fit within this whole RPA world? >> You know with security and I would just say the broader kind of risk management pieces to the operator infrastructure are one of the first questions we get asked and a highly regulated environment like financial services, you know, the technology is easy and powerful with RPA but you also have to take a step back and say okay, I can program a bot to go do anything in my infrastructure, and that could mean running a reconciliation or it could mean going to our wire system and trying to send money out the door. And so there's a lot of concern around, not only understanding the technical aspects to you know, how the tools work with different types of security technologies, but more looking at your approach to entitlements and your approach to how you actually manage who has access to code bots, deployed bots in production, the overtime, understand what happens, you know we did a presentation to a board of directors a couple months ago on kind of automation more broadly and you know this is, you know, senior level executives the first question we got was, you know, okay, how do I prevent the 22 year old kid that just came off of campus from building a bot that no one knows about, setting it loose in our infrastructure and it going rogue, right? And so I mean this group was pretty savvy, they caught onto it very quickly and you know, the CIO of this client was sitting next to me and she kind of didn't have an immediate answer to that and I think that was kind of the a-ha moment, this is something we really need to put some thought into around you know, who are we gonna let build bots, what policies are gonna be set around how bots get deployed into our production environment, how are we gonna monitor what happens? You know how are we gonna get our auditors, our operational risk folks, our regulators, how are we gonna get all our different stakeholder groups comfortable that we have a well controlled, well functioning bot infrastructure that exists? >> Right, cause the bots actually act like people, they're entitled as like a role right, within the organization? >> We have clients that have literally had to set bots up as new employees, like they get onboarded, they have a, you go to the corporate directory and you can see a picture of R2D2, right like and it's the way they get around how they get a bot intel to a system but it's still, it's not a human right, so you still have to have a policy for how you actually will get code that uses that bot entitlement to function right and so that has to be done in a well disciplined, well controlled manner. >> Right, because to give them the ability to provide information to help a person make a decision is very different then basically enabling them to make that decision and take proactive action. >> Exactly. >> Yeah, it's funny we talked to Dr. Robert Gates at a show a little while ago and he said the only place in the US military where a machine can actually shoot a gun is on the Korean border, but every place else they can make suggestions but ultimately it's gotta be a person that makes the decision to push the button. >> And we're seeing, you know, trying to equate that to financial services, you see a similar pattern where there are certain areas where people are very comfortable playing this technology, you know you get into accounting and reporting and you know more back office type processes, you got other areas that people are a little less comfortable, you know anything that touches kind of wire systems or touches things that, you know, going out the door, touches kind of core trading processes, things like that there's a different risk profile associated with it. I think the other challenge is too is RPA is getting the gateway drug into this going back to my previous point, as you start to layer additional technologies into this, you might have less transparency over understanding clearly what's happening, especially as artificial intelligence takes a much broader role in this and so there's gonna be a lot of scrutiny I think over the next couple years put into like how do I understand the models that are created by artificial intelligence technologies and those decisions that are being made because you, if your regulator says, okay, why did you make this decision, you have to be able to explain it as the supervisor of that intelligent bot, you can't just say, oh it's cause what the machine told me to do, as so, that'll be one of the interesting challenges that's ahead of us. >> Yeah it's good, I mean it's part of the whole scale of conversation, I had interesting conversation with a guy, talking about really opening up those AI boxes so that you have an auditable process, right, you can actually point to why it made the decision even if you're not the one that made it in real time and it's doing it really really quickly so. >> Exactly. >> Really important piece. >> Yeah and as PWC, it's one of our challenges, as a consultant I'm helping clients implement this, my colleagues in our audit practice are now grappling with that same question because we're increasingly being asked to audit that type of infrastructure and have to prove that something did what it was suppose to have done. >> Right, right, alright Kevin, well nothing but opportunities for you ahead and thanks for taking a few minutes to stop by. >> Okay, thank you for having me. >> Alright, he's Kevin, I'm Jeff, you're watching theCUBE from Automation Anywhere, Imagine 2018 in Manhattan, thanks for watching. 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>> From Times Square in the heart of New York City, it's theCUBE, covering Imagine 2018. Brought to you by Automation Anywhere. >> Hey welcome back everybody. Jeff Frick here with theCUBE. We're in downtown Manhattan, actually midtown Manhattan, at Automation Anywhere Imagine 2018, 1100 people talkin' about bots, talkin' about Robotics Process Automation, or RPA. And we're excited to have the guy that counts the money at the end of the day; it's important part of any business. He's a co-founder, Ankur Kothari, Chief Revenue Officer and Co-Founder, Automation Anywhere. Ankur, great to see you. >> Great to be here, Jeff, thanks for having me. >> So, first off, as a co-founder, I think you're the third or fourth co-founder we've had on today. A little bit of reflection since you guys started this like 14 years ago. >> Yeah. Here we are, there's 1100 people, the room is packed. They had the overflow, they're actually all over us out here with the overflow for the keynote. Take a minute and kinda tell us how you feel about how this thing has evolved over time. >> It feels like a great party to be part of. Always, you're always happy. >> Right. >> One of the traits that you'll find a lot of co-founders is that they are always happy, never satisfied. They're always looking for the next big one. >> Right. >> But it's amazing to be part of Imagine because we learn so much from our customers and our partner as well. It's not just that we bring them together and we're talking. We're learning every time. It's becoming a big ecosystem. >> Right. >> And, an idea as big as a bot or a future of work is too big an idea for one company to continue. You want as many people to come. >> Right. >> So, our idea of Imagine was a little bit like Field of Dreams, you build and they'll come and they'll collaborate and it'll become bigger and bigger. >> And look all around us. I mean, we're surrounded by people and really, the ecosystem. >> And the bots as well, there are bots on the walls and everything else. >> Bots on the walls, partners everywhere. So let's dive into it a little bit. I mean, one of the ways that you guys participate in the ecosystem, and the ecosystem participates, is the Bot Store. >> Yes. >> So it's just like any other kind of an app store. >> Exactly. >> You've got people contributing. I assume you guys have contributed stuff. But we saw earlier in the keynote by Accenture, and EY, and Deloitte. And all types of companies are contributing bots into this ecosystem for lots of different functions or applications. So really, an interesting thing. How's that workin' out? Where'd you come up with the idea? And why's that so important? >> At Automation Anywhere we like to ask ourselves hard questions, as the leaders in this space. And we asked ourselves this question, "What can we now do to further accelerate our journey of all our customers to become a digital enterprise?" The answer came that we are to share in the new bot economy. Now once that answer was clear, every economy requires a marketplace. >> Right. >> And that's where the Bot Store came. It's a marketplace where producers meet the consumers, and you connect them. All we do is, we curate and make sure that the right things go up. But other than that, it's just like any other marketplace. And we thought that if we'll build the right marketplace where the producers meet consumers, we have thousands of customers and large companies looking at it. It will allow perfect place where all the right ideas get converted into product. >> Right. >> We have tons of partners who have domain expertise, functional expertise, vertical expertise; they can prioritize their expertise, they can convert it into IP. >> Right. >> They can do it for free, they can monetize it. So there's lots to gain for producers of all these bots. And if I am a consumer, now suddenly my time clock to make further shrinks, because instead of creating these bots all from scratch, I can download them from this Bot Store and snap them together like a Lego block. >> Right. >> So that's how the whole idea came. We launched it just two months ago and we have hundreds-- >> You just launched it two months ago? >> Yeah! And we have hundreds of bots in it. More than 80-100 partners have participated. We are getting at least 20-30 more submissions coming every day, and we have few hundred submissions coming every week. So, just like any free marketplace, it has an exponential nature. And that's the thing we are counting on. >> That's amazing, that you've got that much traction in such a short period of time. >> Thousands of downloads on a daily basis. Thousands of users just in two month's time. >> You know, we go to a ton of shows. We do over a hundred shows a year. And once shows get to a certain size, it starts to change a little bit. But when they're small like this, it's a very intimate affair on a couple floors here at the Sheraton, everyone is still really involved. They're really sharing. >> Yes. >> There's so much sharing of information. Not so much, you know ... Because they're not really competitors. Within their own companies, they're all part of this same team that are trying to implement this new thing. >> Exactly. >> And you really feel it. >> Exactly. >> So, the store's cool, but the bot economy. When you talk about the bot economy, we talk about API economy a lot. >> Yes. >> How do you see the bot economy? What are the factors that drive the bot economy, and how's it gonna evolve over time? >> We look at it as a few elements. The current version, we think that bot economy, like any economy, has a marketplace, which is our Bot Store. We have a program which we call Bot Games, because any good economy, any new economy, one of the trait is that the good idea can come from anyone. >> Right. >> It can come from anyplace. Like, any customers, any partner, anyone can bring. A good economy, what it does is it brings that idea from anyone, and it gives these vehicles for good ideas to take flight. If the idea is good, it becomes viral, and it has vehicles where those ideas can go to market. What we did was, we created a program called Bot Games. Yesterday on May 29th, we had the 1st Inaugural Bot Games. We invited developers, people who are part of these programs and their companies. And we gamified and created different games. And we thought that if we bring all these champions and pioneers and like-minded people in the same room, give them certain same problem, and then gamify it, put a clock on it, a lot of great ideas will come out of it. >> Right. >> And that came. And some of those ideas will make it to the marketplace, like a Bot Store, like an Imagine. >> Right. >> So that's where all the ideas connect to the customers. And the people who bring those ideas, they also come up. So that's the other aspect. So the Bot Games is where the ideas, you can crowdsource from places. Bot Store is where they go to the market. In between there is a gap. And we are trying to remove that gap by creating a stimulus package for this new bot economy. Like any economy time and again requires a stimulus pack, and we have created one. What we have done is that if you want to learn Automation Anywhere, right? If you want to understand, because that gap is you're to understand Automation Anywhere. We have created Automation Anywhere University a year ago. And now anyone can take courses for free to learn how to create bots. Whether they are customers or partners. And then, if you purchase these bots through one of our certified partners, the first three bots in year one are free. So we are removing the friction in between. If you have not started on this journey, your learning is free, you get ideas from different places, we can get these prebuilt bots, and the first three bots, if you purchase it through our partners, they are free. So we are removing that friction. And then, we are supporting that whole economy with the industry's largest customer success program. >> Right. So I'm curious if you know, maybe you don't know, of the bots in the bots store, how many are free and how many are paid, as a percentage? >> Interestingly, I don't have that stat because we don't actually worry about that. We let all our partners and people who are contributing to this Bot Store decide that. >> Right. >> Some bots they may decide to monetize, some they may not. It's listed on the Bot Store. Offhand, I would say-- >> Take a guess. Is it 50/50? A third? Two-thirds? >> The nature of it looks like 50/50. >> That's a good guess. Full caveat, it's a guess. We didn't do the analysis. >> Exactly. But here is the unique aspect. Yesterday we had a Bot Game, and the winner had an amazing idea that none of us had ever think of. He created this bot that automates the COE of all these programs. Now, we are talking. He is thinking of putting that on Bot Store. That's the power of bringing multiple people together. >> Right. >> That's the power of free economy, where the exponential nature of it is what we are counting on. And we are getting on a daily basis these new bot ideas, these new bots that are making it to the Bot Store. Just like your App Store. I go to App Store to get ideas what I can do on my phone. >> Right, right. >> Just like that, now we are finding our customers are going to Bot Store to figure out what else can they automate. >> Right, right. >> And that's been another amazing part of it. >> You know, it's so consistent. All these shows we go to, right? How do you unlock innovation? There's some really simple ways. One is, give more people the power, give more people the tools, and give more people the data. >> Exactly. >> And you'll get stuff out of it that the small subset of people that used to have access to those three things, they never found. They just didn't think of it that way, right? >> Exactly. And then we firmly believe that any technology, anything, once you democratize it, you give it in hands of everyone-- >> Right, right. >> You can't have a thriving economy unless everyone forms their own point of view. Unless everyone creates their own perspective. And that's our vision of this bot economy. We are bringing everyone and giving them these vehicles to try it out. Look, the technology has reached a stage where it's cheaper to try it out than talk about it. >> Yes. >> And we are doing that so that everyone forms their own unique point of view, and then they express that point of view and we connect those points of view to these thousands of customers worldwide. >> Right. >> Good ideas take flight, and all we have to do is create vehicles for those good ideas to take flight. >> Alright. So, Ankur, I gave you the last word before we wrap up here. If we come back next year, a year from now, inspired 2019, what are we gonna be talking about? What's on your roadmap? What're some of the priorities that you guys are workin' on over the next 12 months? >> We are talking about ... The next 12 months, we are looking at how to further accelerate this journey. Because what people are in this, the real problem people are trying to achieve is how to become a digital enterprise. Not just to automate, but how do you create a digital enterprise? You cannot become a digital enterprise unless your operations are digital. You cannot make your operations digital unless your processes are digital. And you cannot do that unless your workforce is digital. So we are trying to create technologies, vehicles, platforms, so that everyone can scale their program. Where pretty much everyone should have a digital colleague. Everyone should be able to create a bot. Everyone should be able to work with a bot. Every process, every department, every system should have a digital workforce working in it and that can allow you to create a digital enterprise that can scale up and scale down with the demand and supply. >> Alright-- >> That's what we are trying to start. >> Well, we look forward to gettin' the update next year. >> Exactly. >> Alright, Ankur, thanks for taking a few minutes out of your busy day with us. >> Thanks for having me here, and I appreciate and enjoy the conversation. >> Alright, he's Ankur, I'm Jeff. We're at Automation Anywhere Imagine 2018. Thanks for watching theCUBE. See you next time.

from New York it's the cube covering blockchain week now here's John furry hello everyone welcome back to this special cube exclusive on the water coverage of the awesome cryptocurrency event going on this week blockchain week New York City D central Anthony do re oh seven a big special event launching some great killer products me up to cube alumni that we introduced at polycon 2018 Genevieve Dec Monroe and Jeromy Gartner great to see you guys thanks for having us so you guys look fabulous you look beautiful you're smart we're on a boat we're partying it feels like Prague it feels like prom feels like we are at the top of another bubble couldn't feel better five more boat parties and then the bubbles officially at the top but we're only had the first boat party well the real existential question is what do we view next you know we've we've graduated from nightclubs and strip clubs and now two super yachts like do we go on a spaceship neck's or a Boeing Jets yeah I mean the options are somewhat limited in how we scale up the crypto parties I actually heard today one of my clients is launching in space a crypto mining operation that's fueled by solar power so we might be going to space Elon Musk wants to get involved I agree like where are we going you guys are awesome I love the creative so this party to me is really a testament of the community talk about the community I see polycon was great in Puerto Rico they had restart week and that but I heard these guys saying here at the central that the community's fragmented is the community fragmented seems like it's not out there or just only one pocket of the community I think the community so we have 10,000 people at consensus okay so these are 10,000 people that have gone down the rabbit hole and they're all at the Hilton in midtown Manhattan kind of going like how'd you get involved why are you here 10,000 people is a lot but I think that yeah we're we're at the decentral party so some of the yeast communities are being fragmented but I think we're having like infrastructure built to kind of connect the broader world to the things whether it's custodial services whether it's like tonight the jocks 2.0 wallet and you know everything that's getting involved there I don't know Jeremy Jeremy it's like an international traveler so you Carly Jeremy it's 100 percent in an echo chamber more importantly rabbit holes are like dark and confusing places that there are they're winding and a lot of people are here for very different reasons and thus when you have all these new entrants to the industry to this technology here for all these different reasons of course you have some fragmentation you know in many regards the ideological and philosophical roots of Bitcoin and blotchy technology have been lost son on many of the new entrants and and so it takes time to get to the point where we're all winding I think different blockchains and different applications of this technology will have different kind of approaches to how people think about investors always gonna be pragma because this is a massively growing industry that touches upon every kind of business and governmental and non-governmental it's actually fragmentation is a relative chairman is Genevieve you I saw you and you guys are working with things from cannabis coin I think you had to cannabis cabin this week in New Yorker yeah we're doing that tomorrow night actually so crypto and cannabis are two the hottest millennial sectors right and so we kind of like to say Agri capital we like to dance on the edge of chaos I actually found out about a cannabis company in Vancouver so just outside Vancouver that is using a crypto mining operation and all the excess heat that is coming off that to power a grow-op so we're literally at the intersection of crypto and cannabis not just for our handling money but handling energy in a different way which is so fast that's real mission impact investing right there you know using energy to grow weed that's the Seidel impact isn't it good bad I mean even as you look at it you know better cannabis healthy cannabis is a mission people look care about we're helping people's wallets and we're helping people's minds right in like ways that the government banks and pharmaceutical companies are fighting against so you know if you can't beat them join them so I welcome Astra Zeneca and the Bank of Canada to come on board our mission this is specially turning into a cube after dark episode Jeremy I gotta get your thoughts on these industries because look at cannabis we joke about it but that's an example of another market this zilean markets that are coming online that are gonna be impacted so fragmentation is a relative terms but hey look at it I mean energy tech is infrastructure tech and solid that's what I'm concerned about who nails the infrastructure for network effects and what's the instrumentation for that that's the number one question that is essential question for the protocols whether it's Theory amore Bitcoin oreos Definity so forth the protocol that provides the strongest and and most adaptable and infrastructure and foundational technology is going to be one of the main ones are those will be the main winners and so the names I mentioned they're up there they're very competitive but it's anybody's game right now I think any blockchain can come along right now and be the winner a decade from now and for entrepreneurs represents a challenge because you have to figure out what blocks came to go build on this is why I am big on investing in interoperable Ledger's technologies that enable the kind of transfer smart contracts and crypto assets between blockchains it's a great great segue let's just get an update since we last talked what are you working on what are you investing in what's new in your world share the update on strangers so now my fund is officially launched where how much we launched with just over 15 million dollars and amazingly we launched at the perfect time we're already up 55% and we got making an investment for a venture fund we actually did the exact WA T investment which transferred over from my personal investment portfolio but doing great I have really run the gamut in terms of investments we're making on the equity side of things and in crypto assets but what we're seeing is really accomplished entrepreneurs coming to this space continue actually more optimism than I had felt at polygon poly car and I was like this market needs to correct in a real way today I think that Corrections been prolonged if we were gonna feel a lot of pain it was gonna be two months ago but instead I think it's gonna be one to three years before the market goes through the correction that we need to see for the real shakeout to happen because so many of these teams that I think are garbage have so much money yeah and they're just floating around they got has worked their way out it's just like a bad burrito at some point it's got a pass Genevieve what are you working on I'll see you've got grit capital what's the update on your end what's new yeah amazing actually literally tonight probably about 60 minutes ago my business partner and I signed one of the fastest-growing exchanges in Canada called Einstein exchanges of quiet so these guys have only ever raised like one and a half million u.s. and they're the biggest exchange in Canada by sign ups active accounts so they're probably doing like almost a hundred million in top-line transaction volumes and they're probably never going public somebody's probably gonna buy them but we're gonna be marketing them across the country getting customers I mean the tagline is it doesn't take I'm Stein to open an account it shouldn't take n Stein it by Bitcoin you can literally get this account set up in under 60 seconds so they're vampires ease-of-use surety reducing the steps it takes to do it and get it up and running fast absolutely like my dad could do it and like alright so we say now follow you on Instagram and Facebook which is phenomenal by the way I got a great lifestyle what's the coolest thing you've done since we last talked to Polycom Wow polycon was kind of a high really peaked and then everyone got sick like our team got said polymath untraceable cuz everybody just got the flu yeah we were like on adrenaline and we kept going ah what's the coolest thing that we've done since then I think it's signing up like cool companies like Einstein we also signed a big cannabis company in Colombia called Chiron they're about to go public I don't know Cole what do you think I don't know maybe what's the coolest thing you've done travel what's your good so last night Jeremy and I just met we're together on a blockchain Research Institute project that Sonova Financial is backing and meeting him so you guys working together on a special project right now how's that going what's that about JCO which is a new sort of financial services firm they're creating what it could effectively be understood as a compliant coin offering that is available to more than just accredited investors and that's they're making ico something that falls within the pre-existing regulatory framework and also accessible to your average Joe which I think it's really important if we're going to follow the initial vision for both blockchain technology and offerings all right final question I know you guys want to get back to your dancing and schmoozing networking doing big deals having fun what is blockchain New York we call about we could pop chain we here in New York what the hell's happening there's been a lot of events what's your guy's assessment of you observed and saw anything can you share for the people who didn't make it to New York or not online reading all the action what's happened so as someone that did not attend consensus spoke at three other events or speaking at three other events I can say with certainty that the New York box chain week has been about bringing together virtually everyone in the industry to connect and kind of catch up with one another which is really important we we don't have that many events Miami was too short the industry's gotten too big but having a full week of activities in New York City has enabled me to kind of foster relationships are oh I yeah man get a lot of work John well I've gotten so much work done I haven't had to actually be a date conferences to reconnect with just about everyone that I want to industry that's really special Genevieve what is your observation what have you observed share some in anecdote some insight on what happened this week I know fluid he started I saw Bilt's I was just chatting with him about it it was started in over the weekend it's gone up and we're now into Thursday tomorrow coming up well I don't think it's a coincidence that Goldman Sachs came out today and said that they were launching some sort of digital currency marketing yeah exactly using the power of the 10,000 people i consensus but yeah i know i agree with what jeremy says it's not really about being at consensus it's about what happens like behind closed doors it's all these decentralized parties that are happening yeah open doors but like it's you know like we hosted a core capital asset we had a hundred people in a suite at the dream hotel and it was just like you put the biggest CEOs of the mining companies in the world together and like put those with investors in a room it's like you know 100 people and that's where the deals happen it's not like in the big you know huge auditorium where like nobody looks at each other and everyone's on their phone well I gotta tell you how do we know we the Entrepreneurship side is booming so I totally love the entrepreneurial side check check check access to capital new kinds of business model stuff economics so we reported on all that to me the big story is Wall Street in New York City has been kind of stuck the products kind of like our old is antiquated like the financial products and like that's why Goldman's coming out they got nothing what they don't have anything what are they got so you see in a stagnant they got a traditional product approximately nothing really like new fresh so you got in comes crypto just do a crypto washer so I think I see the New York crowd going this is something that is exciting and we could product ties potentially so I don't think they know yet what that is but I think some of the things that are going on you guys I like I like so I my dad's always the kind of barometer to this whole thing and he's like when are they gonna come out with like a Salesforce stock column for the blockchain right like some sort of application that it doesn't matter if you're like illegal if you're like in investment banking like some sort of pervasive application that just goes wild you have that yet what is that happening Jeremy Jeremy did the date was it's the Netscape moment if you will the moment that blotching technology becomes tangible and now and in retrospect a few years out we may decide that's great for all the young browsers is a browser the original browse for the Internet that was that moment may have already happened we don't really know it maybe it been something like a theory a more augered you know something where there's a use case but people haven't wrapped their heads around it yet but if that hasn't happened yet it's coming it's where we're on the cusp of it because people know what bitcoin is they've heard of the blockchain it is part of the zeitgeist now and and that cultural relevance it's so important for having that Netscape moment Jeremy Jeremy thanks so much to spend the time here on the ground on the water for our special cube coverage of blockchain week new york city consensus you had all kinds of different events you had the crypto house where we were at tons of fluidity conference all this stuff going on good to see you guys you look great thanks for sharing the update here and the cube special coverage I'm John Faria thanks for watching Thanks

>> Live from midtown Manhattan, it's theCUBE covering Big Data New York City 2017. Brought to you by Silicon Angle Media and its ecosystem sponsors. (upbeat techno music) >> Welcome back, everyone. Live here in New York, Day Three coverage, winding down for three days of wall to wall coverage theCUBE covering Big Data NYC in conjunction with Strata Data, formerly Strata Hadoop and Hadoop World, all part of the Big Data ecosystem. Our next guest is Nenshad Bardoliwalla Co-Founder and Chief Product Officer of Paxata, hot start up in the space. A lot of kudos. Of course, they launched on theCUBE in 2013 three years ago when we started theCUBE as a separate event from O'Reilly. So, great to see the success. And Stephanie McReynolds, you've been on multiple times, VP of Marketing at Alation. Welcome back, good to see you guys. >> Thank you. >> Happy to be here. >> So, winding down, so great kind of wrap-up segment here in addition to the partnership that you guys have. So, let's first talk about before we get to the wrap-up of the show and kind of bring together the week here and kind of summarize everything. Tell about your partnership you guys have. Paxata, you guys have been doing extremely well. Congratulations. Prakash was talking on theCUBE. Great success. You guys worked hard for it. I'm happy for you. But partnering is everything. Ecosystem is everything. Alation, their collaboration with data. That's there ethos. They're very user-centric. >> Nenshad: Yes. >> From the founders. Seemed like a good fit. What's the deal? >> It's a very natural fit between the two companies. When we started down the path of building new information management capabilities it became very clear that the market had strong need for both finding data, right? What do I actually have? I need an inventory, especially if my data's in Amazon S3, my data is in Azure Blob storage, my data is on-premise in HDFS, my data is in databases, it's all over the place. And I need to be able to find it. And then once I find it, I want to be able to prepare it. And so, one of the things that really drove this partnership was the very common interests that both companies have. And number one, pushing user experience. I love the Alation product. It's very easy to use, it's very intuitive, really it's a delightful thing to work with. And at the same time they also share our interests in working in these hybrid multicloud environments. So, what we've done and what we announced here at Strata is actually this bi-directional integration between the products. You can start in Alation and find a data set that you want to work with, see what collaboration or notes or business metadata people have created and then say, I want to go see this in Paxata. And in a single click you can then actually open it up in Paxata and profile that data. Vice versa you can also be in Paxata and prepare data, and then with a single click push it back, and then everybody who works with Alation actually now has knowledge of where that data is. So, it's a really nice synergy. >> So, you pushed the user data back to Alation, cause that's what they care a lot about, the cataloging and making the user-centric view work. So, you provide, it's almost a flow back and forth. It's a handshake if you will to data. Am I getting that right? >> Yeah, I mean, the idea's to keep the analyst or the user of that data, data scientist, even in some cases a business user, keep them in the flow of their work as much as possible. But give them the advantage of understanding what others in the organization have done with that data prior and allow them to transform it, and then share that knowledge back with the rest of the community that might be working with that data. >> John: So, give me an example. I like your Excel spreadsheet concept cause that's obvious. People know what Excel spreadsheet is so. So, it's Excel-like. That's an easy TAM to go after. All Microsoft users might not get that Azure thing. But this one, just take me through a usecase. >> So, I've got a good example. >> Okay, take me through. >> It's very common in a data lake for your data to be compressed. And when data's compressed, to a user it looks like a black box. So, if the data is compressed in Avro or Parquet or it's even like JSON format. A business user has no idea what's in that file. >> John: Yeah. >> So, what we do is we find the file for them. It may have some comments on that file of how that data's been used in past projects that we infer from looking at how others have used that data in Alation. >> John: So, you put metadata around it. >> We put a whole bunch of metadata around it. It might be comments that people have made. It might be >> Annotations, yeah. >> actual observations, annotations. And the great thing that we can do with Paxata is open that Avro file or Parquet file, open it up so that you can actually see the data elements themselves. So, all of a sudden, the business user has access without having to use a command line utility or understand anything about compression, and how you open that file up-- >> John: So, as Paxata spitting out there nuggets of value back to you, you're kind of understanding it, translating it to the user. And they get to do their thing, you get to do your thing, right? >> It's making a Avro or a Parquet file as easy to use as Excel, basically. Which is great, right? >> It's awesome. >> Now, you've enabled >> a whole new class of people who can use that. >> Well, and people just >> Get turned off when it's anything like jargon, or like, "What is that? I'm afraid it's phishing. Click on that and oh!" >> Well, the scary thing is that in a data lake environment, in a lot of cases people don't even label the files with extensions. They're just files. (Stephanie laughs) So, what started-- >> It's like getting your pictures like DS, JPEG. It's like what? >> Exactly. >> Right. >> So, you're talking about unlabeled-- >> If you looked on your laptop, and if you didn't have JPEG or DOC or PPT. Okay, I don't know that this file is. Well, what you have in the data lake environment is that you have thousands of these files that people don't really know what they are. And so, with Alation we have the ability to get all the value around the curation of the metadata, and how people are using that data. But then somebody says, "Okay, but I understand that this file exists. What's in it?" And then with Click to Profile from Alation you're immediately taken into Paxata. And now you're actually looking at what's in that file. So, you can very quickly go from this looks interesting to let me understand what's inside of it. And that's very powerful. >> Talk about Alation. Cause I had the CEO on, also their lead investor Greg Sands from Costanoa Ventures. They're a pretty amazing team but it's kind of out there. No offense, it's kind of a compliment actually. (Stephanie laughs) >> They got a symbolic >> Stephanie: Keep going. system Stanford guy, who's like super-smart. >> Nenshad: Yeah. >> They're on something that's really unique but it's almost too simple to be. Like, wait a minute! Google for the data, it's an awesome opportunity. How do you describe Alation to people who say, "Hey, what's this Alation thing?" >> Yeah, so I think that the best way to describe it is it's the browser for all of the distributed data in the enterprise. Sorry, so it's both the catalog, and the browser that sits on top of it. It sounds very simple. Conceptually it's very simple but they have a lot of richness in what they're able to do behind the scenes in terms of introspecting what type of work people are doing with data, and then taking that knowledge and actually surfacing it to the end user. So, for example, they have very powerful scenarios where they can watch what people are doing in different data sources, and then based on that information actually bubble up how queries are being used or the different patterns that people are doing to consume data with. So, what we find really exciting is that this is something that is very complex under the covers. Which Paxata is as well being built upon Spark. But they have put in the hard engineering work so that it looks simple to the end user. And that's the exact same thing that we've tried to do. >> And that's the hard problem. Okay, Stephanie back ... That was a great example by the way. Can't wait to have our little analyst breakdown of the event. But back to Alation for you. So, how do you talk about, you've been VP of Marketing of Alation. But you've been around the block. You know B2B, tech, big data. So, you've seen a bunch of different, you've worked at Trifacta, you worked at other companies, and you've seen a lot of waves of innovation come. What's different about Alation that people might not know about? How do you describe the difference? Because it sounds easy, "Oh, it's a browser! It's a catalog!" But it's really hard. Is it the tech that's the secret? Is it the approach? How do you describe the value of Alation? I think what's interesting about Alation is that we're solving a problem that since the dawn of the data warehouse has not been solved. And that is how to help end users really find and understand the data that they need to do their jobs. A lot of our customers talk about this-- >> John: Hold on. Repeat that. Cause that's like a key thing. What problem hasn't been solved since the data warehouse? >> To be able to actually find and fully understand, understand to the point of trust the data that you want to use for your analysis. And so, in the world of-- >> John: That sounds so simple. >> Stephanie: In the world of data warehousing-- >> John: Why is it so hard? >> Well, because in the world of data warehousing business people were told what data they should use. Someone in IT decided how to model the data, came up with a KPR calculation, and told you as a business person, you as a CEO, this is how you're going to monitor you business. >> John: Yeah. >> What business person >> Wants to be told that by an IT guy, right? >> Well, it was bounded by IT. >> Right. >> Expression and discovery >> Should be unbounded. Machine learning can take care of a lot of bounded stuff. I get that. But like, when you start to get into the discovery side of it, it should be free. >> Well, no offense to the IT team, but they were doing their best to try to figure out how to make this technology work. >> Well, just look at the cost of goods sold for storage. I mean, how many EMC drives? Expensive! IT was not cheap. >> Right. >> Not even 10, 15, 20 years ago. >> So, now when we have more self-service access to data, and we can have more exploratory analysis. What data science really introduced and Hadoop introduced was this ability on-demand to be able to create these structures, you have this more iterative world of how you can discover and explore datasets to come to an insight. The only challenge is, without simplifying that process, a business person is still lost, right? >> John: Yeah. >> Still lost in the data. >> So, we simply call that a catalog. But a catalog is much more-- >> Index, catalog, anthology, there's other words for it, right? >> Yeah, but I think it's interesting because like a concept of a catalog is an inventory has been around forever in this space. But the concept of a catalog that learns from other's behavior with that data, this concept of Behavior I/O that Aaron talked about earlier today. The fact that behavior of how people query data as an input and that input then informs a recommendation as an output is very powerful. And that's where all the machine learning and A.I. comes to work. It's hidden underneath that concept of Behavior I/O but that's there real innovation that drives this rich catalog is how can we make active recommendations to a business person who doesn't have to understand the technology but they know how to apply that data to making a decision. >> Yeah, that's key. Behavior and textual information has always been the two fly wheels in analysis whether you're talking search engine or data in general. And I think what I like about the trends here at Big Data NYC this weekend. We've certainly been seeing it at the hundreds of CUBE events we've gone to over the past 12 months and more is that people are using data differently. Not only say differently, there's baselining, foundational things you got to do. But the real innovators have a twist on it that give them an advantage. They see how they can use data. And the trend is collective intelligence of the customer seems to be big. You guys are doing it. You're seeing patterns. You're automating the data. So, it seems to be this fly wheel of some data, get some collective data. What's your thoughts and reactions. Are people getting it? Is this by people doing it by accident on purpose kind of thing? Did people just fell on their head? Or you see, "Oh, I just backed into this?" >> I think that the companies that have emerged as the leaders in the last 15 or 20 years, Google being a great example, Amazon being a great example. These are companies whose entire business models were based on data. They've generated out-sized returns. They are the leaders on the stock market. And I think that many companies have awoken to the fact that data as a monetizable asset to be turned into information either for analysis, to be turned into information for generating new products that can then be resold on the market. The leading edge companies have figured that out, and our adopting technologies like Alation, like Paxata, to get a competitive advantage in the business processes where they know they can make a difference inside of the enterprise. So, I don't think it's a fluke at all. I think that most of these companies are being forced to go down that path because they have been shown the way in terms of the digital giants that are currently ruling the enterprise tech world. >> All right, what's your thoughts on the week this week so far on the big trends? What are obvious, obviously A.I., don't need to talk about A.I., but what were the big things that came out of it? And what surprised you that didn't come out from a trends standpoint buzz here at Strata Data and Big Data NYC? What were the big themes that you saw emerge and didn't emerge what was the surprise? Any surprises? >> Basically, we're seeing in general the maturation of the market finally. People are finally realizing that, hey, it's not just about cool technology. It's not about what distribution or package. It's about can you actually drive return on investment? Can you actually drive insights and results from the stack? And so, even the technologists that we were talking with today throughout the course of the show are starting to talk about it's that last mile of making the humans more intelligent about navigating this data, where all the breakthroughs are going to happen. Even in places like IOT, where you think about a lot of automation, and you think about a lot of capability to use deep learning to maybe make some decisions. There's still a lot of human training that goes into that decision-making process and having agency at the edge. And so I think this acknowledgement that there should be balance between human input and what the technology can do is a nice breakthrough that's going to help us get to the next level. >> What's missing? What do you see that people missed that is super-important, that wasn't talked much about? Is there anything that jumps out at you? I'll let you think about it. Nenshad, you have something now. >> Yeah, I would say I completely agree with what Stephanie said which we are seeing the market mature. >> John: Yeah. >> And there is a compelling force to now justify business value for all the investments people have made. The science experiment phase of the big data world is over. People now have to show a return on that investment. I think that being said though, this is my sort of way of being a little more provocative. I still think there's way too much emphasis on data science and not enough emphasis on the average business analyst who's doing work in the Fortune 500. >> It should be kind of the same thing. I mean, with data science you're just more of an advanced analyst maybe. >> Right. But the idea that every person who works with data is suddenly going to understand different types of machine learning models, and what's the right way to do hyper parameter tuning, and other words that I could throw at you to show that I'm smart. (laughter) >> You guys have a vision with the Excel thing. I could see how you see that perspective because you see a future. I just think we're not there yet because I think the data scientists are still handcuffed and hamstrung by the fact that they're doing too much provisioning work, right? >> Yeah. >> To you're point about >> surfacing the insights, it's like the data scientists, "Oh, you own it now!" They become the sysadmin, if you will, for their department. And it's like it's not their job. >> Well, we need to get them out of data preparation, right? >> Yeah, get out of that. >> You shouldn't be a data scientist-- >> Right now, you have two values. You've got the use interface value, which I love, but you guys do the automation. So, I think we're getting there. I see where you're coming from, but still those data sciences have to set the tone for the generation, right? So, it's kind of like you got to get those guys productive. >> And it's not a .. Please go ahead. >> I mean, it's somewhat interesting if you look at can the data scientist start to collaborate a little bit more with the common business person? You start to think about it as a little bit of scientific inquiry process. >> John: Yeah. >> Right? >> If you can have more innovators around the table in a common place to discuss what are the insights in this data, and people are bringing business perspective together with machine learning perspective, or the knowledge of the higher algorithms, then maybe you can bring those next leaps forward. >> Great insight. If you want my observations, I use the crazy analogy. Here's my crazy analogy. Years it's been about the engine Model T, the car, the horse and buggy, you know? Now, "We got an engine in the car!" And they got wheels, it's got a chassis. And so, it's about the apparatus of the car. And then it evolved to, "Hey, this thing actually drives. It's transportation." You can actually go from A to B faster than the other guys, and people still think there's a horse and buggy market out there. So, they got to go to that. But now people are crashing. Now, there's an art to driving the car. >> Right. >> So, whether you're a sports car or whatever, this is where the value piece I think hits home is that, people are driving the data now. They're driving the value proposition. So, I think that, to me, the big surprise here is how people aren't getting into the hype cycle. They like the hype in terms of lead gen, and A.I., but they're too busy for the hype. It's like, drive the value. This is not just B.S. either, outcomes. It's like, "I'm busy. I got security. I got app development." >> And I think they're getting smarter about how their valuing data. We're starting to see some economic models, and some ways of putting actual numbers on what impact is this data having today. We do a lot of usage analysis with our customers, and looking at they have a goal to distribute data across more of the organization, and really get people using it in a self-service manner. And from that, you're being able to calculate what actually is the impact. We're not just storing this for insurance policy reasons. >> Yeah, yeah. >> And this cheap-- >> John: It's not some POC. Don't do a POC. All right, so we're going to end the day and the segment on you guys having the last word. I want to phrase it this way. Share an anecdotal story you've heard from a customer, or a prospective customer, that looked at your product, not the joint product but your products each, that blew you away, and that would be a good thing to leave people with. What was the coolest or nicest thing you've heard someone say about Alation and Paxata? >> For me, the coolest thing they said, "This was a social network for nerds. I finally feel like I've found my home." (laughter) >> Data nerds, okay. >> Data nerds. So, if you're a data nerd, you want to network, Alation is the place you want to be. >> So, there is like profiles? And like, you guys have a profile for everybody who comes in? >> Yeah, so the interesting thing is part of our automation, when we go and we index the data sources we also index the people that are accessing those sources. So, you kind of have a leaderboard now of data users, that contract one another in system. >> John: Ooh. >> And at eBay leader was this guy, Caleb, who was their data scientist. And Caleb was famous because everyone in the organization would ask Caleb to prepare data for them. And Caleb was like well known if you were around eBay for awhile. >> John: Yeah, he was the master of the domain. >> And then when we turned on, you know, we were indexing tables on teradata as well as their Hadoop implementation. And all of a sudden, there are table structures that are Caleb underscore cussed. Caleb underscore revenue. Caleb underscore ... We're like, "Wow!" Caleb drove a lot of teradata revenue. (Laughs) >> Awesome. >> Paxata, what was the coolest thing someone said about you in terms of being the nicest or coolest most relevant thing? >> So, something that a prospect said earlier this week is that, "I've been hearing in our personal lives about self-driving cars. But seeing your product and where you're going with it I see the path towards self-driving data." And that's really what we need to aspire towards. It's not about spending hours doing prep. It's not about spending hours doing manual inventories. It's about getting to the point that you can automate the usage to get to the outcomes that people are looking for. So, I'm looking forward to self-driving information. Nenshad, thanks so much. Stephanie from Alation. Thanks so much. Congratulations both on your success. And great to see you guys partnering. Big, big community here. And just the beginning. We see the big waves coming, so thanks for sharing perspective. >> Thank you very much. >> And your color commentary on our wrap up segment here for Big Data NYC. This is theCUBE live from New York, wrapping up great three days of coverage here in Manhattan. I'm John Furrier. Thanks for watching. See you next time. (upbeat techo music)

>> Announcer: Live from Midtown Manhattan it's theCUBE. Covering Big Data New York City 2017. Brought to you by SiliconANGLE Media and its ecosystem sponsors. >> Welcome back everyone live here in New York City this theCUBE's coverage of our fifth annual annual event that we put on ourselves in conjunction Strata Hadoop now called Strata Data. It's theCUBE and we're covering the scene here at Hadoop World going back to 2010, eight years of Coverage. I'm John Furrier co-host of theCUBE. Usually Dave Vellante is here but he's down covering the Splunk Conference and who was there yesterday was no other than Josh Rogers my next guest the CEO of Syncsort, you were with Dave Vellante yesterday and live on theCUBE in Washington, DC for the Splunk .conf kind of a Big Data Conference but it's a proprietary, branded event for themselves. This is a more industry even here at Big Data NYC that we put on. Welcome back glad you flew up on the on the Concord, the private jet. >> Early morning but it was was fine. >> No good to see you a CEO of Syncsort, you guys have been busy. For the folks watching in theCUBE community know that you've been on many times. The folks that are learning more about theCUBE every day, you guys had an interesting transformations as a company, take a minute to talk about where you've come from and where you are today. Certainly a ton of corporate development activity in your end it, as you guys are seeing the opportunities, you're moving on them. Take a minute to explain. >> So, you know it's been a great journey so far and there's a lot more work to do, but you know Syncsort is one of the first software companies, right. Founded in the late 60's today has a unparalleled franchise in the mainframe space. But over the last 10 years or so we branched out into open systems and delivered high performance data integration solutions. About 4 years ago really started to invest in the Big Data space we had a DNA around performance and scale we felt like that would be relevant in the Big Data space. We delivered a Hadoop focused product and today we focus around that product around helping customers ingest mainframe data assets into their into Hadoop clusters along with other types data. But a specific focus there. That has lead us into understanding a bigger market space that we call Big Iron to Big Data. And what we see in the marketplace is that customers are adapting. >> Just before you get in there I love that term, Big Iron Big Data you know I love Big Iron. Used to be a term for the mainframe for the younger generation out there. But you're really talking about you guys have leveraged experience with the installed base activity that scale call it batched, molded, single threaded, whatever you want to call it. But as you got into the game of Big Data you then saw other opportunities, did I get that right? You got into the game with some Hadoop, then you realize, whoa, I can do some large scale. What was that opportunity? >> The opportunity is that you know large enterprise is absolutely investing heavily in the next generation of analytic technologies in a new stack. Hadoop is a part of that, Spark is a part of that. And they're rapidly adopting these new infrastructures to drive deeper analytics to answer bigger questions and improve their business and in multiple dimensions. The opportunity we saw was that you know the ability for those enterprises to be able to integrate this new kind of architecture with the legacy architectures. So, the old architectures that were powering key applications impede key up producers of data was a challenge, there was multiple technology challenges, there's cultural challenges. And we had this kind of expertise on both sides of the house and and we found that to be unique in the marketplace. So we put a lot of effort into understanding, defining what are the challenges in that Big Iron to Big Data space that helped customers maximize their value out of these investments in next generation architectures. And we define the problem two ways, one is our two components. One is that people are generating more and more data more and more touch points and driving more and more transactions with their customers. And that's generating increased load on the compute environments and they want to figure out how do I run that, you know if I have a mainframe how to run as efficiently as possible contain my costs maximize availability and uptime. At the same time I've got all this new data that I can start to analyze but I got to get it from the area that it's produced into this next generation system. And there's a lot of challenges there. So we started to isolate, you know, what are the specific use cases the present customers challenge and deliver very different IT solutions. Overarching kind of messages around positioning is around solving the Big Iron to Big Data challenge. >> You guys had done some acquisitions and been successful, I want to talk a little bit about the ones that you like right now that happened the past year or two years. I think you've done five in the past two years. A couple key notable ones that set you up kind of give you pole position for some of these big markets, and then after we talk then I want to talk about your ecosystem opportunity. But some of the acquisitions and what's working for you? What's been the big deals? >> So the larger the larger we did in 2016 was a company called Trillium, leader in the data quality space. Long time leader in the data quality space and the opportunity we saw with Trillium was to complement our data movement integration capabilities. A natural complement, but to focus very specifically on how to drive value in this next generation architecture. Particularly in things like Hadoop. what I'd like to be able to do is apply best in class data quality routines directly in that environment. And so we, from our experience in delivering these Big Data solutions in the past, we knew that we could take a lot of technology and create really powerful solutions that were that leverage the native kind of capabilities of Hadoop but had it on a layer of you've proven technology for best in class day quality. Probably the biggest news of the last few weeks has been that we were acquired by a new private equity partner called Centerbridge Partners. In that acquisition actually acquired Syncsort and they acquired a company called Vision Solutions. And we've combined those organizations. >> John: When did that happen? >> The deal was announced July, early July and it closed in the middle of August. And vision solutions is a really interesting company. They're the leader in high availability for the IBM i market. IBM i was originally called AS/400 it's had a couple of different names and a dominant kind of market position. What we liked about that business was A. That market position four thousand customers generally large enterprise. And also you know market leading capability around data replication in real time. >> And we saw IBM. >> Migration data, disaster recovery kind of thing? >> It's DR it's high availability, it's migrations, it's also changed data capture actually. And leveraging all common technology elements there. But it also represents a market leading franchise in IBM i which is in many ways very similar to the mainframe. Run optimized for transactional systems, hard to kind of get at. >> Sounds like you're reconstructing the mainframe in the cloud. >> It's not so much that, it's the recognition that those compute systems still run the world. They still run all the transactions. >> Well, some say the cloud is a software mainframe. >> I think over time you'll see that, we don't see that our business today. There is a cloud aspect our business it's not to move this transactional applications running on those platforms into the cloud yet. Although I suspect that happens at some point. But our point, our interest was more these are the systems that are producing the world's data. And it's hard to to get. >> There are big, big power sources for data, they're not going anywhere. So we've got the expertise to source that data into these next generation systems. And that's a tricky problem for a lot of customers, and and not something. >> That a problem they have. And you guys basically cornered the market on that. >> So think about Big Iron and Big Data as these two components, being able to source data and make a productive using these next generation analytics systems, and also be able to run those existing systems as you know efficiently as possible. >> All right, so how do you talk to customers and I've asked this question before so I just ask again, oh, Syncsort now you got vision you guys are just a bunch of old mainframe guys. What do you know about cloud native? A lot of the hipsters and the young guns out there might not know about some of the things you're doing on the cutting edge, because even though you have the power base of these old big systems, we're just throwing off massive amounts of data that aren't going anywhere. You still are integrated into some cutting edge. Talk about that, that narrative, and how you. >> So I mean the folks that we target. >> I used cloud only as an example. Shiny, cool, new toys. >> Organizations we target and our customers and prospects, and generally we we serve large enterprise. You know large complex global enterprises. They are making significant investments in Hadoop and Splunk and these next generation environments. We approach them and say we believe to get full value out of your investments in these next generation technologies, it would be helpful if you had your most critical data assets available. And that's hard, and we can help you do that. And we can help you do that in a number of ways that you won't be able to find anywhere else. That includes features in our products, it includes experts on the ground. And what we're seeing is there's a huge demand because, you know, Hadoop is really kind of you can see it in the Cloudera and Hortonworks results and the scale of revenue. This is a you know a real foundational component data management this point. Enterprises are embracing it. If they can't solve that integration challenge between the systems that produce all the data and, you know, where they want to analyze the data There's a there's a big value gap. And we think we're uniquely positioned to be able to do that, one because we've got the technical expertise, two, they're all our customers at this point, we have six thousand customers. >> You guys have executed very well. I just got to say you guys are just slowly taking territory down you and you got a great strategy, get into a business, you don't overplay your hand or get over your skis, whatever you want to call it. And you figure it out and see if was a fit. If it is, grab it, if not, you move on. So also you guys have relationships so we're talking about your ecosystem. What is your ecosystem and what is your partner strategy? >> I'll talk a little bit about the overall strategy and I'll talk about how partners fit into that. Our strategy is to identify specific use cases that are common and challenging in our customer set, that fall within this Big Iron to Big Data umbrella. It's then to deliver a solution that is highly differentiated. Now, the third piece of that is to partner very closely with you know the emerging platform vendors in the in the Big Data space. And the reason for that is we're solving an integration challenge for them. Like Cloudera, like Hortonworks, like Splunk. We launched a relationship with Calibra in the middle the year. We just announced our relationship. >> Yeah, for them the benefits of them is they don't do the heavy lifting you've got that covered. >> We can we can solve a lot of pain points they have getting their platforms setup. >> That's hard to replicate on their end, it's not like they're going to go build it. >> Cloudera and Hortonworks, they don't have mainframe skills. They don't understand how to go access >> Classic partnering example. >> But that the other pieces is we do real engineering work with these partnerships. So we build, we write code to integrate and add value to platforms. >> It's not a Barney deal, it's not an optical deal. >> Absolutely. >> Any jazz is critical in the VM world of some of the deals he's been done in the industry referring to his deal, that's seems to be back in vogue thank God, that people going to say they're going to do a deal and they back it with actually following through. What about other partnerships, how else, how you looking at partnering? So, pretty much, where it fits in your business, are people coming to you, are you going to them? >> We certainly have people coming to us. The the key thing, the number one driver is customers. You know, as we understand use cases, as customers introduce us to new challenges that they are facing, we will not just look at how do we solve it, but and what are the other platforms that we're integrating with, and if we believe we can add unique value to that partner we'll approach that partner. >> Let's talk customers, give me some customer use cases that you're working on right now, that you think are notable worth highlighting. >> Sure so we do a lot in the in the financial services space. You know we have a number of customers >> Where there's mainframes. >> Where there's a lot of mainframes, but it's not just in financial services. Here's an interesting one, was insurance company and they were looking at how to transition their mainframe archive strategy. So they have regulations around how long they have to keep data, they had been using traditional mainframe archive technology, very expensive on annual basis and also unflexible. They didn't have access to. >> And performance too. At the end of the day don't forget performance >> They want performance, this was more of an archive use case and what they really wanted was an ability both access the data and also lower the cost of storing the data for the required time from a regulation perspective. And so they made the decision that they wanted to store it in the cloud, they want to store it in S3. There's a complicated data movement there, there's a complicated data translation process there and you need to understand the mainframe and you need to understand AWS and S3 and all those components, and we had all those pieces and all that expertise and were able to solve that. So we're doing that with a few different customers now. But that's just an example of, you know, there's a great ROI, there's a lot more business flexibility then there's a modernization aspect to it that's very attractive. >> Well, great to hear from you today. I'm glad you made it up here, again you were in DC yesterday thanks for coming in, checking out to shows you're certainly pounding the pavement as they say in New York, to quote New Yorker phrase. What's new for you guys, what's coming out? More acquisitions happening? what's the outlook for Syncsort? >> So were were always active on the M&A front. We certainly have a pipeline of activities and there's a lot of different you know interesting spaces, adjacencies that we're exploring right now. There's nothing that I can really talk about there >> Can you talk about the categories you're looking at? >> Sure you know, things around metadata management, things around real-time data movement, cloud opportunities. There's there's some interesting opportunities in the artificial intelligence, machine learning space. Those are all >> Deep learning. >> Deep learning, those are all interesting spaces for us to think about. Security and other space is interesting. So we're pretty active in a lot of adjacencies >> Classic adjacent markets that you're looking at. So you take one step at a time, slow. >> But then we try to innovate on, you know, after the catch, so we did three announcements this week. Transaction tracing for Ironstream and a kind of refresh of data quality for Hadoop approach. So we'll continue to innovate on the organic setup as well. >> Final question the whole private equity thing. So that's done, so they put a big bag of money in there and brought the two companies together. Is there structural changes, management changes, you're the Syncsort CEO is there a new co name? >> The combined companies will operate under the Syncsort name, I'll serve as the CEO. >> Syncsort is the remaining name and you guys now have another company under it. >> Yes, that's right. >> And cash they put in, probably a boatload of cash for corporate development. >> The announcement the announced deal value was $1.2 billion a little over $1.2 billion. >> So you get a checkbook and looking to buy companies? >> We are we're going to continue, as I said yesterday, to Dave, you know I like to believe that we proved the hypothesis were in about the second inning. Can't wait to keep playing the game. >> It's interesting just, real quick while I got you in here, we got a break coming up for the guys. Private equity move is a good move in this transitional markets, you and I have talked about this in the past off-camera. It's a great thing to do, is take, if you're public and you're not really knocking it out of the park. Kill the 90 day shot clock, go private, there seems to be a lot of movement there. Retool and then re-emerge stronger. >> We've never been public, but I will say, the Centerbridge team has been terrific. A lot of resources there and certainly we do talk we're still very quarterly focused, but I think we've got a great partner and look forward to continue. >> The waves are coming, the big waves are coming so get your big surfboard out, we say in California. Josh, thanks for spending the time. Josh Rogers, CEO Syncsort here on theCUBE. More live coverage in New York after this break. Stay with us for our day two of three days of coverage of Big Data NYC 2017. Our event that we hold every year here in conjunction with Hadoop World right around the corner. I'm John Furrier, we'll be right back.

>> Voiceover: Live from midtown Manhattan, it's theCUBE! Covering Big Data New York City 2017. Brought to you by, SiliconANGLE Media and as ecosystems sponsors. >> Okay, welcome back everyone, live in New York City this is theCUBE's coverage of, eighth year doing Hadoop World now, evolved into Strata Hadoop, now called Strata Data, it's had many incarnations but O'Reilly Media running their event in conjunction with Cloudera, mainly an O'Reilly media show. We do our own show called Big Data NYC here with our community with theCUBE bringing you the best interviews, the best people, entrepreneurs, thought leaders, experts, to get the data and try to project the future and help users find the value in data. My next guest is Rob Thomas, who is the General Manager of IBM Analytics, theCUBE Alumni, been on multiple times successfully executing in the San Francisco Bay area. Great to see you again. >> Yeah John, great to see you, thanks for having me. >> You know IBM is really been interesting through its own transformation and a lot of people will throw IBM in that category but you guys have been transforming okay and the scoreboard yet has to yet to show in my mind what's truly happening because if you still look at this industry, we're only eight years into what Hadoop evolved into now as a large data set but the analytics game just seems to be getting started with the cloud now coming over the top, you're starting to see a lot of cloud conversations in the air. Certainly there's a lot of AI washing, you know, AI this, but it's machine learning and deep learning at the heart of it as innovation but a lot more work on the analytics side is coming. You guys are at the center of that. What's the update? What's your view of this analytics market? >> Most enterprises struggle with complexity. That's the number one problem when it comes to analytics. It's not imagination, it's not willpower, in many cases, it's not even investment, it's just complexity. We are trying to make data really simple to use and the way I would describe it is we're moving from a world of products to platforms. Today, if you want to go solve a data governance problem you're typically integrating 10, 15 different products. And the burden then is on the client. So, we're trying to make analytics a platform game. And my view is an enterprise has to have three platforms if they're serious about analytics. They need a data manager platform for managing all types of data, public, private cloud. They need unified governance so governance of all types of data and they need a data science platform machine learning. If a client has those three platforms, they will be successful with data. And what I see now is really mixed. We've got 10 products that do that, five products that do this, but it has to be integrated in a platform. >> You as an IBM or the customer has these tools? >> Yeah, when I go see clients that's what I see is data... >> John: Disparate data log. >> Yeah, they have disparate tools and so we are unifying what we deliver from a product perspective to this platform concept. >> You guys announce an integrated analytic system, got to see my notes here, I want to get into that in a second but interesting you bring up the word platform because you know, platforms have always been kind of reserved for the big supplier but you're talking about customers having a platform, not a supplier delivering a platform per se 'cause this is where the integration thing becomes interesting. We were joking yesterday on theCUBE here, kind of just kind of ad hoc conceptually like the world has turned into a tool shed. I mean everyone has a tool shed or knows someone that has a tool shed where you have the tools in the back and they're rusty. And so, this brings up the tool conversation, there's too many tools out there that try to be platforms. >> Rob: Yes. >> And if you have too many tools, you're not really doing the platform game right. And complexity also turns into when you bought a hammer it turned into a lawn mower. Right so, a lot of these companies have been groping and trying to iterate what their tool was into something else it wasn't built for. So, as the industry evolves, that's natural Darwinism if you will, they will fall to the wayside. So talk about that dynamic because you still need tooling >> Rob: Yes. but tool will be a function of the work as Peter Burris would say, so talk about how does a customer really get that platform out there without sacrificing the tooling that they may have bought or want to get rid of. >> Well, so think about the, in enterprise today, what the data architecture looks like is, I've got this box that has this software on it, use your terms, has these types of tools on it, and it's isolated and if you want a different set of tooling, okay, move that data to this other box where we have the other tooling. So, it's very isolated in terms of how platforms have evolved or technology platforms today. When I talk about an integrated platform, we are big contributors to Kubernetes. We're making that foundational in terms of what we're doing on Private Cloud and Public Cloud is if you move to that model, suddenly what was a bunch of disparate tools are now microservices against a common architecture. And so it totally changes the nature of the data platform in an enterprise. It's a much more fluid data layer. The term I use sometimes is you have data as a service now, available to all your employees. That's totally different than I want to do this project, so step one, make room in the data center, step two, bring in a server. It's a much more flexible approach so that's what I mean when I say platform. >> So operationalizing it is a lot easier than just going down the linear path of provisioning. All right, so let's bring up the complexity issue because integrated and unified are two different concepts that kind of mean the same thing depending on how you look at it. When you look at the data integration problem, you've got all this complexity around governance, it's a lot of moving parts of data. How does a customer actually execute without compromising the integrity of their policies that they need to have in place? So in other words, what are the baby steps that someone can take, the customers take through with what you guys are dealing with them, how do they get into the game, how do they take steps towards the outcome? They might not have the big money to push it all at once, they might want to take a risk of risk management approach. >> I think there's a clear recipe for doing this right and we have experience of doing it well and doing it not so well, so over time we've gotten some, I'd say a pretty good perspective on that. My view is very simple, data governance has to start with a catalog. And the analogy I use is, you have to do for data what libraries do for books. And think about a library, the first thing you do with books, card catalog. You know where, you basically itemize everything, you know exactly where it sits. If you've got multiple copies of the same book, you can distinguish between which one is which. As books get older they go to archives, to microfilm or something like that. That's what you have to do with your data. >> On the front end. >> On the front end. And it starts with a catalog. And that reason I say that is, I see some organizations that start with, hey, let's go start ETL, I'll create a new warehouse, create a new Hadoop environment. That might be the right thing to do but without having a basis of what you have, which is the catalog, that's where I think clients need to start. >> Well, I would just add one more level of complexity just to kind of reinforce, first of all I agree with you but here's another example that would reinforce this step. Let's just say you write some machine learning and some algorithms and a new policy from the government comes down. Hey, you know, we're dealing with Bitcoin differently or whatever, some GPRS kind of thing happens where someone gets hacked and a new law comes out. How do you inject that policy? You got to rewrite the code, so I'm thinking that if you do this right, you don't have to do a lot of rewriting of applications to the library or the catalog will handle it. Is that right, am I getting that right? >> That's right 'cause then you have a baseline is what I would describe it as. It's codified in the form of a data model or in the form on ontology for how you're looking at unstructured data. You have a baseline so then as changes come, you can easily adjust to those changes. Where I see clients struggle is if you don't have that baseline then you're constantly trying to change things on the fly and that makes it really hard to get to this... >> Well, really hard, expensive, they have to rewrite apps. >> Exactly. >> Rewrite algorithms and machine learning things that were built probably by people that maybe left the company, who knows, right? So the consequences are pretty grave, I mean, pretty big. >> Yes. >> Okay, so let's back to something that you said yesterday. You were on theCUBE yesterday with Hortonworks CEO, Rob Bearden and you were commenting about AI or AI washing. You said quote, "You can't have AI without IA." A play on letters there, sequence of letters which was really an interesting comment, we kind of referenced it pretty much all day yesterday. Information architecture is the IA and AI is the artificial intelligence basically saying if you don't have some sort of architecture AI really can't work. Which really means models have to be understood, with the learning machine kind of approach. Expand more on that 'cause that was I think a fundamental thing that we're seeing at the show this week, this in New York is a model for the models. Who trains the machine learning? Machines got to learn somewhere too so there's learning for the learning machines. This is a real complex data problem and a half. If you don't set up the architecture it may not work, explain. >> So, there's two big problems enterprises have today. One is trying to operationalize data science and machine learning that scale, the other one is getting the cloud but let's focus on the first one for a minute. The reason clients struggle to operationalize this at scale is because they start a data science project and they build a model for one discreet data set. Problem is that only applies to that data set, it doesn't, you can't pick it up and move it somewhere else so this idea of data architecture just to kind of follow through, whether it's the catalog or how you're managing your data across multiple clouds becomes fundamental because ultimately you want to be able to provide machine learning across all your data because machine learning is about predictions and it's hard to do really good predictions on a subset. But that pre-req is the need for an information architecture that comprehends for the fact that you're going to build models and you want to train those models. As new data comes in, you want to keep the training process going. And that's the biggest challenge I see clients struggling with. So they'll have success with their first ML project but then the next one becomes progressively harder because now they're trying to use more data and they haven't prepared their architecture for that. >> Great point. Now, switching to data science. You spoke many times with us on theCUBE about data science, we know you're passionate about you guys doing a lot of work on that. We've observed and Jim Kobielus and I were talking yesterday, there's too much work still in the data science guys plate. There's still doing a lot of what I call, sys admin like work, not the right word, but like administrative building and wrangling. They're not doing enough data science and there's enough proof points now to show that data science actually impacts business in whether it's military having data intelligence to execute something, to selling something at the right time, or even for work or play or consume, or we use, all proof is out there. So why aren't we going faster, why aren't the data scientists more effective, what does it going to take for the data science to have a seamless environment that works for them? They're still doing a lot of wrangling and they're still getting down the weeds. Is that just the role they have or how does it get easier for them that's the big catch? >> That's not the role. So they're a victim of their architecture to some extent and that's why they end up spending 80% of their time on data prep, data cleansing, that type of thing. Look, I think we solved that. That's why when we introduced the integrated analytic system this week, that whole idea was get rid of all the data prep that you need because land the data in one place, machine learning and data science is built into that. So everything that the data scientist struggles with today goes away. We can federate to data on cloud, on any cloud, we can federate to data that's sitting inside Hortonworks so it looks like one system but machine learning is built into it from the start. So we've eliminated the need for all of that data movement, for all that data wrangling 'cause we organized the data, we built the catalog, and we've made it really simple. And so if you go back to the point I made, so one issue is clients can't apply machine learning at scale, the other one is they're struggling to get the cloud. I think we've nailed those problems 'cause now with a click of a button, you can scale this to part of the cloud. >> All right, so how does the customer get their hands on this? Sounds like it's a great tool, you're saying it's leading edge. We'll take a look at it, certainly I'll do a review on it with the team but how do I get it, how do I get a hold of this? What do I do, download it, you guys supply it to me, is it some open source, how do your customers and potential customers engage with this product? >> However they want to but I'll give you some examples. So, we have an analytic system built on Spark, you can bring the whole box into your data center and right away you're ready for data science. That's one way. Somebody like you, you're going to want to go get the containerized version, you go download it on the web and you'll be up and running instantly with a highly performing warehouse integrated with machine learning and data science built on Spark using Apache Jupyter. Any developer can go use that and get value out of it. You can also say I want to run it on my desktop. >> And that's free? >> Yes. >> Okay. >> There's a trial version out there. >> That's the open source, yeah, that's the free version. >> There's also a version on public cloud so if you don't want to download it, you want to run it outside your firewall, you can go run it on IBM cloud on the public cloud so... >> Just your cloud, Amazon? >> No, not today. >> John: Just IBM cloud, okay, I got it. >> So there's variety of ways that you can go use this and I think what you'll find... >> But you have a premium model that people can get started out so they'll download it to your data center, is that also free too? >> Yeah, absolutely. >> Okay, so all the base stuff is free. >> We also have a desktop version too so you can download... >> What URL can people look at this? >> Go to datascience.ibm.com, that's the best place to start a data science journey. >> Okay, multi-cloud, Common Cloud is what people are calling it, you guys have Common SQL engine. What is this product, how does it relate to the whole multi-cloud trend? Customers are looking for multiple clouds. >> Yeah, so Common SQL is the idea of integrating data wherever it is, whatever form it's in, ANSI SQL compliant so what you would expect for a SQL query and the type of response you get back, you get that back with Common SQL no matter where the data is. Now when you start thinking multi-cloud you introduce a whole other bunch of factors. Network, latency, all those types of things so what we talked about yesterday with the announcement of Hortonworks Dataplane which is kind of extending the YARN environment across multi-clouds, that's something we can plug in to. So, I think let's be honest, the multi-cloud world is still pretty early. >> John: Oh, really early. >> Our focus is delivery... >> I don't think it really exists actually. >> I think... >> It's multiple clouds but no one's actually moving workloads across all the clouds, I haven't found any. >> Yeah, I think it's hard for latency reasons today. We're trying to deliver an outstanding... >> But people are saying, I mean this is head room I got but people are saying, I'd love to have a preferred future of multi-cloud even though they're kind of getting their own shops in order, retrenching, and re-platforming it but that's not a bad ask. I mean, I'm a user, I want to move from if I don't like IBM's cloud or I got a better service, I can move around here. If Amazon is too expensive I want to move to IBM, you got product differentiation, I might want to to be in your cloud. So again, this is the customers mindset, right. If you have something really compelling on your cloud, do I have to go all in on IBM cloud to run my data? You shouldn't have to, right? >> I agree, yeah I don't think any enterprise will go all in on one cloud. I think it's delusional for people to think that so you're going to have this world. So the reason when we built IBM Cloud Private we did it on Kubernetes was we said, that can be a substrate if you will, that provides a level of standards across multiple cloud type environments. >> John: And it's got some traction too so it's a good bet there. >> Absolutely. >> Rob, final word, just talk about the personas who you now engage with from IBM's standpoint. I know you have a lot of great developers stuff going on, you've done some great work, you've got a free product out there but you still got to make money, you got to provide value to IBM, who are you selling to, what's the main thing, you've got multiple stakeholders, could you just clarify the stakeholders that you're serving in the marketplace? >> Yeah, I mean, the emerging stakeholder that we speak with more and more than we used to is chief marketing officers who have real budgets for data and data science and trying to change how they're performing their job. That's a major stakeholder, CTOs, CIOs, any C level, >> Chief data officer. >> Chief data officer. You know chief data officers, honestly, it's a mixed bag. Some organizations they're incredibly empowered and they're driving the strategy. Others, they're figure heads and so you got to know how the organizations do it. >> A puppet for the CFO or something. >> Yeah, exactly. >> Our ops. >> A puppet? (chuckles) So, you got to you know. >> Well, they're not really driving it, they're not changing it. It's not like we're mandated to go do something they're maybe governance police or something. >> Yeah, and in some cases that's true. In other cases, they drive the data architecture, the data strategy, and that's somebody that we can engage with right away and help them out so... >> Any events you got going up? Things happening in the marketplace that people might want to participate in? I know you guys do a lot of stuff out in the open, events they can connect with IBM, things going on? >> So we do, so we're doing a big event here in New York on November first and second where we're rolling out a lot of our new data products and cloud products so that's one coming up pretty soon. The biggest thing we've changed this year is there's such a craving for clients for education as we've started doing what we're calling Analytics University where we actually go to clients and we'll spend a day or two days, go really deep and open languages, open source. That's become kind of a new focus for us. >> A lot of re-skilling going on too with the transformation, right? >> Rob: Yes, absolutely. >> All right, Rob Thomas here, General Manager IBM Analytics inside theCUBE. CUBE alumni, breaking it down, giving his perspective. He's got two books out there, The Data Revolution was the first one. >> Big Data Revolution. >> Big Data Revolution and the new one is Every Company is a Tech Company. Love that title which is true, check it out on Amazon. Rob Thomas, Bid Data Revolution, first book and then second book is Every Company is a Tech Company. It's theCUBE live from New York. More coverage after the short break. (theCUBE jingle) (theCUBE jingle) (calm soothing music)