>>welcome back. And thanks for joining us for our second session. External data, your new leading indicators. We'll be hearing from industry leaders as they share best practices and challenges in leveraging external data. This panel will be a true conversation on the part of the possible. All right, let's get to >>it >>today. We're excited to be joined by thought spots. Chief Data Strategy Officer Cindy Housing Deloitte's chief data officer Manteo, the founder and CEO of Eagle Alfa. And it Kilduff and Snowflakes, VP of data marketplace and customer product strategy. Matt Glickman. Cindy. Without further ado, the floor is yours. >>Thank you, Mallory. And I am thrilled to have this brilliant team joining us from around the world. And they really bring each a very unique perspective. So I'm going to start from further away. Emmett, Welcome. Where you joining us from? >>Thanks for having us, Cindy. I'm joining from Dublin, Ireland, >>great. And and tell us a little bit about Eagle Alfa. What do you dio >>from a company's perspective? Think of Eagle Alfa as an aggregator off all the external data sets on a word I'll use a few times. Today is a big advantage we could bring companies is we have a data concierge service. There's so much data we can help identify the right data sets depending on the specific needs of the company. >>Yeah. And so, Emma, you know, people think I was a little I kind of shocked the industry. Going from gardener to a tech startup. Um, you have had a brave journey as well, Going from financial services to starting this company, really pioneering it with I think the most data sets of any of thes is that right? >>Yes, it was. It was a big jump to go from Morgan Stanley. Uh, leave the comforts of that environment Thio, PowerPoint deck and myself raising funding eight years ago s So it was a big jump on. We were very early in our market. It's in the last few years where there's been real momentum and adoption by various types of verticals. The hedge funds were first, maybe then private equity, but corporate sar are following quite quickly from behind. That will be the biggest users, in our view, by by a significant distance. >>Yeah, great. Thank um, it So we're going to go a little farther a field now, but back to the U. S. So, Juan, where you joining us from? >>Hey, Cindy. Thanks for having me. I'm joining you from Houston, Texas. >>Great. Used to be my home. Yeah, probably see Rice University back there. And you have a distinct perspective serving both Deloitte customers externally, but also internally. Can you tell us about that? >>Yeah, absolutely. So I serve as the Lord consultants, chief data officer, and as a professional service firm, I have the responsibility for overseeing our overall data agenda, which includes both the way we use data and insights to run and operate our own business, but also in how we develop data and insights services that we then take to market and how we serve our dealers and clients. >>Great. Thank you, Juan. And last but not least, Matt Glickman. Kind of in my own backyard in New York. Right, Matt? >>Correct. Joining I haven't been into the city and many months, but yes, um, based in New York. >>Okay. Great. And so, Matt, you and Emmett also, you know, brave pioneers in this space, and I'm remembering a conversation you and I shared when you were still a J. P. Morgan, I believe. And you're Goldman Sachs. Sorry. Sorry. Goldman. Can you Can you share that with us? >>Sure. I made the move back in 2015. Um, when everyone thought, you know, my wife, my wife included that I was crazy. I don't know if I would call it Comfortable was emitted, but particularly had been there for a long time on git suffered in some ways. A lot of the pains we're talking about today, given the number of data, says that the amount of of new data sets that are always demand for having run analytics teams at Goldman, seeing the pain and realizing that this pain was not unique to Goldman Sachs, it was being replicated everywhere across the industry, um, in a mind boggling way and and the fortuitous, um, luck to have one of snowflakes. Founders come to pitch snowflake to Goldman a little bit early. Um, they became a customer later, but a little bit early in 2014. And, you know, I realized that this was clearly, you know, the answer from first principles on bond. If I ever was going to leave, this was a problem. I was acutely aware of. And I also was aware of how much the man that was in financial services for a better solution and how the cloud could really solve this problem in particular the ability to not have to move data in and out of these organizations. And this was something that I saw the future of. Thank you, Andi, that this was, you know, sort of the pain that people just expected to pay. Um, this price if you need a data, there was method you had thio. You had to use you either ftp data in and out. You had data that was being, you know, dropped off and, you know, maybe in in in a new ways and cloud buckets or a P i s You have to suck all this data down and reconstruct it. And God forbid the formats change. It was, you know, a nightmare. And then having issues with data, you had a what you were seeing internally. You look nothing like what the data vendors were seeing because they want a completely different system, maybe model completely differently. Um, but this was just the way things were. Everyone had firewalls. Everyone had their own data centers. There was no other way on git was super costly. And you know this. I won't even share the the details of you know, the errors that would occur in the pain that would come from that, Um what I realized it was confirmed. What I saw it snowflake at the time was once everyone moves to run their actual workloads in this in the cloud right where you're now beyond your firewall, you'll have all this scale. But on top of that, you'll be able to point at data from these vendors were not there the traditional data vendors. Or, you know, this new wave of alternative data vendors, for example, like the ones that eagle out for brings together And bring these all these data sets together with your own internal data without moving it. Yeah, this was a fundamental shift of what you know, it's in some ways, it was a side effect of everyone moving to the cloud for costs and scale and elasticity. But as a side effect of that is what we talked about, You know it snowflake summit, you know, yesterday was this notion of a data cloud that would connect data between regions between cloud vendors between customers in a way where you could now reference data. Just like your reference websites today, I don't download CNN dot com. I point at it, and it points me to something else. I'm always seeing the latest version, obviously, and we can, you know, all collaborate on what I'm seeing on that website. That's the same thing that now can happen with data. So And I saw this as what was possible, and I distinctly asked the question, you know, the CEO of the time Is this possible? And not only was it possible it was a fundamental construct that was built into the way that snowflake was delivered. And then, lastly, this is what we learned. And I think this is what you know. M It also has been touting is that it's all great if data is out there and even if you lower that bar of access where data doesn't have to move, how do I know? Right? If I'm back to sitting at Goldman Sachs, how do I know what data is available to me now in this this you know, connected data network eso we released our data marketplace, which was a very different kind of marketplace than these of the past. Where for us, it was really like a global catalog that would elect a consumer data consumer. Noah data was available, but also level the playing field. Now we're now, you know, Eagle, Alfa, or even, you know, a new alternative data vendor build something in their in their basement can now publish that data set so that the world could see and consume and be aligned to, you know, snowflakes, core business, and not where we wouldn't have to be competing or having to take, um, any kind of custody of that data. So adding that catalog to this now ubiquitous access, um really changed the game and, you know, and then now I seem like a genius for making this move. But back then, like I said, we've seen I seem like instant. I was insane. >>Well, given, given that snowflake was the hottest aipo like ever, you were a genius. Uh, doing this, you know, six years in advance. E think we all agree on that, But, you know, a lot of this is still visionary. Um, you know, some of the most leading companies are already doing this. But one What? What is your take our Are you best in class customers still moving the data? Or is this like they're at least thinking about data monetization? What are you seeing from your perspective? >>Yeah, I mean, I did you know, the overall appreciation and understanding of you know, one. I got to get my house in order around my data, um, has something that has been, you know, understood and acted upon. Andi, I do agree that there is a shift now that says, you know, data silos alone aren't necessarily gonna bring me, you know, new and unique insights on dso enriching that with external third party data is absolutely, you know, sort of the the ship that we're seeing our customers undergo. Um, what I find extremely interesting in this space and what some of the most mature clients are doing is, you know, really taking advantage of these data marketplaces. But building data partnerships right there from what mutually exclusive, where there is a win win scenario for for you know, that organization and that could be, you know, retail customers or life science customers like with pandemic, right the way we saw companies that weren't naturally sharing information are now building these data partnership right that are going are going into mutually benefit, you know, all organizations that are sort of part of that value to Andi. I think that's the sort of really important criteria. And how we're seeing our clients that are extremely successful at this is that partnership has benefits on both sides of that equation, right? Both the data provider and then the consumer of that. And there has to be, you know, some way to ensure that both parties are are are learning right, gaining you insights to support, you know, whatever their business organization going on. >>Yeah, great one. So those data partnerships getting across the full value chain of sharing data and analytics Emmett, you work on both sides of the equation here, helping companies. Let's say let's say data providers maybe, like, you know, cast with human mobility monetize that. But then also people that are new to it. Where you seeing the top use cases? Well, >>interestingly, I agree with one of the supply side. One of the interesting trends is we're seeing a lot more data coming from large Corporates. Whether they're listed are private equity backed, as opposed to maybe data startups that are earning money just through data monetization. I think that's a great trend. I think that means a lot of the best. Data said it data is yet to come, um, in terms off the tough economy and how that's changed. I think the category that's had the most momentum and your references is Geo location data. It's that was the category at our conference in December 2000 and 12 that was pipped as the category to watch in 2019. On it didn't become that at all. Um, there were some regulatory concerns for certain types of geo data, but with with covert 19, it's Bean absolutely critical for governments, ministries of finance, central banks, municipalities, Thio crunch that data to understand what's happening in a real time basis. But from a company perspective, it's obviously critical as well. In terms of planning when customers might be back in the High Street on DSO, fourth traditionally consumer transaction data of all the 26 categories in our taxonomy has been the most popular. But Geo is definitely catching up your slide. Talked about being a tough economy. Just one point to contradict that for certain pockets of our clients, e commerce companies are having a field day, obviously, on they are very data driven and tech literate on day are they are really good client base for us because they're incredibly hungry, firm or data to help drive various, uh, decision making. >>Yeah, So fair enough. Some sectors of the economy e commerce, electron, ICS, healthcare are doing great. Others travel, hospitality, Um, super challenging. So I like your quote. The best is yet to come, >>but >>that's data sets is yet to come. And I do think the cloud is enabling that because we could get rid of some of the messy manual data flows that Matt you talked about, but nonetheless, Still, one of the hardest things is the data map. Things combining internal and external >>when >>you might not even have good master data. Common keys on your internal data. So any advice for this? Anyone who wants to take that? >>Sure I can. I can I can start. That's okay. I do think you know, one of the first problems is just a cataloging of the information that's out there. Um, you know, at least within our organization. When I took on this role, we were, you know, a large buyer of third party data. But our organization as a whole didn't necessarily have full visibility into what was being bought and for what purpose. And so having a catalog that helps us internally navigate what data we have and how we're gonna use it was sort of step number one. Um, so I think that's absolutely important. Um, I would say if we could go from having that catalog, you know, created manually to more automated to me, that's sort of the next step in our evolution, because everyone is saying right, the ongoing, uh, you know, creation of new external data sets. It's only going to get richer on DSO. We wanna be able to take advantage of that, you know, at the at the pacing speed, that data is being created. So going from Emanuel catalog to anonymous >>data >>catalog, I think, is a key capability for us. But then you know, to your second point, Cindy is how doe I then connect that to our own internal data to drive greater greater insights and how we run our business or how we serve our customers. Andi, that one you know really is a It's a tricky is a tricky, uh, question because I think it just depends on what data we're looking toe leverage. You know, we have this concept just around. Not not all data is created equal. And when you think about governance and you think about the management of your master data, your internal nomenclature on how you define and run your business, you know that that entire ecosystem begins to get extremely massive and it gets very broad and very deep on DSO for us. You know, government and master data management is absolutely important. But we took a very sort of prioritized approach on which domains do we really need to get right that drive the greatest results for our organization on dso mapping those domains like client data or employee data to these external third party data sources across this catalog was really the the unlocked for us versus trying to create this, you know, massive connection between all the external data that we're, uh, leveraging as well as all of our own internal data eso for us. I think it was very. It was a very tailored, prioritized approach to connecting internal data to external data based on the domains that matter most to our business. >>So if the domains so customer important domain and maybe that's looking at things, um, you know, whether it's social media data or customer transactions, you prioritized first by that, Is that right? >>That's correct. That's correct. >>And so, then, Matt, I'm going to throw it back to you because snowflake is in a unique position. You actually get to see what are the most popular data sets is is that playing out what one described are you seeing that play out? >>I I'd say Watch this space. Like like you said. I mean this. We've you know, I think we start with the data club. We solve that that movement problem, which I think was really the barrier that you tended to not even have a chance to focus on this mapping problem. Um, this notion of concordance, I think this is where I see the big next momentum in this space is going to be a flurry of traditional and new startups who deliver this concordance or knowledge graph as a service where this is no longer a problem that I have to solve internal to my organization. The notion of mastering which is again when everyone has to do in every organization like they used to have to do with moving data into the organization goes away. And this becomes like, I find the best of breed for the different scopes of data that I have. And it's delivered to me as a, you know, as a cloud service that just takes my data. My internal data maps it to these 2nd and 3rd party data sets. Um, all delivered to me, you know, a service. >>Yeah, well, that would be brilliant concordance as a service or or clean clean master data as a service. Um, using augmented data prep would be brilliant. So let's hope we get there. Um, you know, so 2020 has been a wild ride for everyone. If I could ask each of you imagine what is the art of the possible or looking ahead to the next to your and that you are you already mentioned the best is yet to come. Can you want to drill down on that. What what part of the best is yet to come or what is your already two possible? >>Just just a brief comment on mapping. Just this week we published a white paper on mapping, which is available for for anyone on eagle alfa dot com. It's It's a massive challenge. It's very difficult to solve. Just with technology Onda people have tried to solve it and get a certain level of accuracy, but can't get to 100% which which, which, which makes it difficult to solve it. If if if there is a new service coming out against 100% I'm all ears and that there will be a massive step forward for the entire data industry, even if it comes in a few years time, let alone next year, I think going back to the comment on data Cindy. Yes, I think boards of companies are Mawr and Mawr. Viewing data as an asset as opposed to an expense are a cost center on bond. They are looking therefore to get their internal house in order, as one was saying, but also monetize the data they are sitting on lots of companies. They're sitting on potentially valuable data. It's not all valuable on a lot of cases. They think it's worth a lot more than it is being frank. But in some cases there is valuable data on bond. If monetized, it can drop to the bottom line on. So I think that bodes well right across the world. A lot of the best date is yet to come on. I think a lot of firms like Deloitte are very well positioned to help drive that adoption because they are the trusted advisor to a lot of these Corporates. Um, so that's one thing. I think, from a company perspective. It's still we're still at the first base. It's quite frustrating how slow a lot of companies are to move and adopt, and some of them are haven't hired CDO. Some of them don't have their internal house in order. I think that has to change next year. I think if we have this conference at this time next year, I would expect that would hopefully be close to the tipping point for Corporates to use external data. And the Malcolm Gladwell tipping point on the final point I make is I think, that will hopefully start to see multi department use as opposed to silos again. Parliaments and silos, hopefully will be more coordinated on the company's side. Data could be used by marketing by sales by r and D by strategy by finance holds external data. So it really, hopefully will be coordinated by this time next year. >>Yeah, Thank you. So, to your point, there recently was an article to about one of the airlines that their data actually has more value than the company itself now. So I know, I know. We're counting on, you know, integrators trusted advisers like Deloitte to help us get there. Uh, one what? What do you think? And if I can also drill down, you know, financial services was early toe all of this because they needed the early signals. And and we talk about, you know, is is external data now more valuable than internal? Because we need those early signals in just such a different economy. >>Yeah, I think you know, for me, it's it's the seamless integration of all these external data sources and and the signals that organizations need and how to bring those into, you know, the day to day operations of your organization, right? So how do you bring those into, You know, you're planning process. How do you bring that into your sales process on DSO? I think for me success or or where I see the that the use and adoption of this is it's got to get down to that level off of operations for organizations. For this to continue to move at the pace and deliver the value that you know, we're all describing. I think we're going to get there. But I think until organizations truly get down to that level of operations and how they're using this data, it'll sort of seem like a Bolton, right? So for me, I think it's all about Mawr, the seamless integration. And I think to what Matt mentioned just around services that could help connect external data with internal data. I'll take that one step beyond and say, How can we have the data connect itself? Eso I had references Thio, you know, automation and machine learning. Um, there's significant advances in terms of how we're seeing, you know, mapping to occur in a auto generated fashion. I think this specific space and again the connection between external and internal data is a prime example of where we need to disrupt that, you know, sort of traditional data pipeline on. Try to automate that as much as possible. And let's have the data, you know, connect itself because it then sort of supports. You know, the first concept which waas How do we make it more seamless and integrated into, you know, the business processes of the organization's >>Yeah, great ones. So you two are thinking those automated, more intelligent data pipelines will get us there faster. Matt, you already gave us one. Great, Uh, look ahead, Any more to add to >>it, I'll give you I'll give you two more. One is a bit controversial, but I'll throw that you anyway, um, going back to the point that one made about data partnerships What you were saying Cindy about, you know, the value. These companies, you know, tends to be somehow sometimes more about the data they have than the actual service they provide. I predict you're going to see a wave of mergers and acquisitions. Um, that it's solely about locking down access to data as opposed to having data open up. Um to the broader, you know, economy, if I can, whether that be a retailer or, you know, insurance company was thes prime data assets. Um, you know, they could try to monetize that themselves, But if someone could acquire them and get exclusive access that data, I think that's going to be a wave of, um, in a that is gonna be like, Well, we bought this for this amount of money because of their data assets s. So I think that's gonna be a big wave. And it'll be maybe under the guise of data partnerships. But it really be about, you know, get locking down exclusive access to valuable data as opposed to trying toe monetize it itself number one. And then lastly, you know. Now, did you have this kind of ubiquity of data in this interconnected data network? Well, we're starting to see, and I think going to see a big wave of is hyper personalization of applications where instead of having the application have the data itself Have me Matt at Snowflake. Bring my data graph to applications. Right? This decoupling of we always talk about how you get data out of these applications. It's sort of the reverse was saying Now I want to bring all of my data access that I have 1st, 2nd and 3rd party into my application. Instead of having to think about getting all the data out of these applications, I think about it how when you you know, using a workout app in the consumer space, right? I can connect my Spotify or connect my apple music into that app to personalize the experience and bring my music list to that. Imagine if I could do that, you know, in a in a CRM. Imagine I could do that in a risk management. Imagine I could do that in a marketing app where I can bring my entire data graph with me and personalize that experience for, you know, for given what I have. And I think again, you know, partners like thoughts. But I think in a unique position to help enable that capability, you know, for this next wave of of applications that really take advantage of this decoupling of data. But having data flow into the app tied to me as opposed to having the APP have to know about my data ahead of time, >>Yeah, yeah, So that is very forward thinking. So I'll end with a prediction and a best practice. I am predicting that the organizations that really leverage external data, new data sources, not just whether or what have you and modernize those data flows will outperform the organizations that don't. And as a best practice to getting there, I the CDOs that own this have at least visibility into everything they're purchasing can save millions of dollars in duplicate spend. So, Thio, get their three key takeaways. Identify the leading indicators and market signals The data you need Thio. Better identify that. Consolidate those purchases and please explore the data sets the range of data sets data providers that we have on the thought spot. Atlas Marketplace Mallory over to you. >>Wow. Thank you. That was incredible. Thank you. To all of our Panelists for being here and sharing that wisdom. We really appreciate it. For those of you at home, stay close by. Our third session is coming right up and we'll be joined by our partner AWS and get to see how you can leverage the full power of your data cloud complete with the demo. Make sure to tune in to see you >>then

>>from around the >>globe. It's the Cube with digital coverage of AWS reinvent 2020 sponsored by Intel and AWS. Yeah, >>Hi. We are the Cube live covering AWS reinvent 2020. I'm Lisa Martin, and I've got one of our cube alumni back with me. Mike Miller is here. General manager of A W s AI Devices at AWS. Mike, welcome back to the Cube. >>Hi, Lisa. Thank you so much for having me. It's really great to join you all again at this virtual reinvent. >>Yes, I think last year you were on set. We have always had to. That's at reinvent. And you you had the deep race, your car, and so we're obviously socially distance here. But talk to me about deepracer. What's going on? Some of the things that have gone on the last year that you're excited >>about. Yeah, I'd love to tell. Tell you a little bit about what's been happening. We've had a tremendous year. Obviously, Cove. It has restricted our ability to have our in person races. Eso we've really gone gone gangbusters with our virtual league. So we have monthly races for competitors that culminate in the championship. Um, at reinvent. So this year we've got over 100 competitors who have qualified and who are racing virtually with us this year at reinvent. They're participating in a series of knockout rounds that are being broadcast live on twitch over the next week. That will whittle the group down to AH Group of 32 which will have a Siris of single elimination brackets leading to eight finalists who will race Grand Prix style five laps, eight cars on the track at the same time and will crown the champion at the closing keynote on December 15th this year. >>Exciting? So you're bringing a reinforcement, learning together with with sports that so many of us have been missing during the pandemic. We talked to me a little bit about some of the things that air that you've improved with Deep Racer and some of the things that are coming next year. Yeah, >>absolutely so, First of all, Deep Racer not only has been interesting for individuals to participate in the league, but we continue to see great traction and adoption amongst big customers on dare, using Deep Racer for hands on learning for machine learning, and many of them are turning to Deep Racer to train their workforce in machine learning. So over 150 customers from the likes of Capital One Moody's, Accenture, DBS Bank, JPMorgan Chase, BMW and Toyota have held Deep Racer events for their workforces. And in fact, three of those customers Accenture, DBS Bank and J. P. Morgan Chase have each trained over 1000 employees in their organization because they're just super excited. And they find that deep racers away to drive that excitement and engagement across their customers. We even have Capital one expanded this to their families, so Capital One ran a deep raise. Their Kids Cup, a family friendly virtual competition this past year were over. 250 Children and 200 families got to get hands on with machine learning. >>So I envisioned some. You know, this being a big facilitator during the pandemic when there's been this massive shift to remote work has have you seen an uptick in it for companies that talking about training need to be ableto higher? Many, many more people remotely but also train them? Is deep Racer facilitator of that? Yeah, >>absolutely. Deep Racer has ah core component of the experience, which is all virtualized. So we have, ah, console and integration with other AWS services so that racers can participate using a three d racing simulator. They can actually see their car driving around a track in a three D world simulation. Um, we're also selling the physical devices. So you know, if participants want to get the one of those devices and translate what they've done in the virtual world to the real world, they can start doing that. And in fact, just this past year, we made our deep race or car available for purchase internationally through the Amazon Com website to help facilitate that. >>So how maney deep racers air out there? I'm just curious. >>Oh, thousands. Um, you know, And there what? What we've seen is some companies will purchase you, know them in bulk and use them for their internal leagues. Just like you know, JP Morgan Chase on DBS Bank. These folks have their own kind of tracks and racers that they'll use to facilitate both in person as well as the virtual racing. >>I'm curious with this shift to remote that we mentioned a minute ago. How are you seeing deepracer as a facilitator of engagement. You mentioned engagement. And that's one of the biggest challenges that so Maney teams develops. Processes have without being co located with each other deep Brister help with that. I mean, from an engagement perspective, I think >>so. What we've seen is that Deep Racer is just fun to get your hands on. And we really lower the learning curve for machine learning. And in particular, this branch called reinforcement Learning, which is where you train this agent through trial and error toe, learn how to do a new, complex task. Um, and what we've seen is that customers who have introduced Deep Racer, um, as an event for their employees have seen ah, very wide variety of employees. Skill sets, um, kind of get engaged. So you've got not just the hardcore deep data scientists or the M L engineers. You've got Web front end programmers. You even have some non technical folks who want to get their hands dirty. Onda learn about machine learning and Deep Racer really is a nice, gradual introduction to doing that. You can get engaged with it with very little kind of coding knowledge at all. >>So talk to me about some of the new services. And let's look at some specific use case customer use cases with each service. Yeah, >>absolutely. So just to set the context. You know, Amazon's got hundreds. A ws has hundreds of thousands of customers doing machine learning on AWS. No customers of all sizes are embedding machine learning into their no core business processes. And one of the things that we always do it Amazon is We're listening to customers. You know, 90 to 95% of our road maps are driven by customer feedback. And so, as we've been talking to these industrial manufacturing customers, they've been telling us, Hey, we've got data. We've got these processes that are happening in our industrial sites. Um, and we just need some help connecting the dots like, how do we really most effectively use machine learning to improve our processes in these industrial and manufacturing sites? And so we've come up with these five services. They're focused on industrial manufacturing customers, uh, two of the services air focused around, um, predictive maintenance and, uh, the other three services air focused on computer vision. Um, and so let's start with the predictive maintenance side. So we announced Amazon Monitor On and Amazon look out for equipment. So these services both enable predictive maintenance powered by machine learning in a way that doesn't require the customer to have any machine learning expertise. So Mono Tron is an end to end machine learning system with sensors, gateway and an ML service that can detect anomalies and predict when industrial equipment will require maintenance. I've actually got a couple examples here of the sensors in the gateway, so this is Amazon monitor on these little sensors. This little guy is a vibration and temperature sensor that's battery operated, and wireless connects to the gateway, which then transfers the data up to the M L Service in the cloud. And what happens is, um, the sensors can be connected to any rotating machinery like pump. Pour a fan or a compressor, and they will send data up to the machine learning cloud service, which will detect anomalies or sort of irregular kind of sensor readings and then alert via a mobile app. Just a tech or a maintenance technician at an industrial site to go have a look at their equipment and do some preventative maintenance. So um, it's super extreme line to end to end and easy for, you know, a company that has no machine learning expertise to take advantage of >>really helping them get on board quite quickly. Yeah, >>absolutely. It's simple tea set up. There's really very little configuration. It's just a matter of placing the sensors, pairing them up with the mobile app and you're off and running. >>Excellent. I like easy. So some of the other use cases? Yeah, absolutely. >>So So we've seen. So Amazon fulfillment centers actually have, um, enormous amounts of equipment you can imagine, you know, the size of an Amazon fulfillment center. 28 football fields, long miles of conveyor belts and Amazon fulfillment centers have started to use Amazon monitor on, uh, to monitor some of their conveyor belts. And we've got a filament center in Germany that has started using these 1000 sensors, and they've already been able to, you know, do predictive maintenance and prevent downtime, which is super costly, you know, for businesses, we've also got customers like Fender, you know, who makes guitars and amplifiers and musical equipment. Here in the US, they're adopting Amazon monitor on for their industrial machinery, um, to help prevent downtime, which again can cost them a great deal as they kind of hand manufacture these high end guitars. Then there's Amazon. Look out for equipment, which is one step further from Amazon monitor on Amazon. Look out for equipment. Um provides a way for customers to send their own sensor data to AWS in order to build and train a model that returns predictions for detecting abnormal equipment behavior. So here we have a customer, for example, like GP uh, E P s in South Korea, or I'm sorry, g S E P s in South Korea there in industrial conglomerate, and they've been collecting their own data. So they have their own sensors from industrial equipment for a decade. And they've been using just kind of rule basic rules based systems to try to gain insight into that data. Well, now they're using Amazon, look out for equipment to take all of their existing sensor data, have Amazon for equipment, automatically generate machine learning models on, then process the sensor data to know when they're abnormalities or when some predictive maintenance needs to occur. >>So you've got the capabilities of working with with customers and industry that that don't have any ML training to those that do have been using sensors. So really, everybody has an opportunity here to leverage this new Amazon technology, not only for predicted, but one of the things I'm hearing is contact list, being able to understand what's going on without having to have someone physically there unless there is an issue in contact. This is not one of the words of 2020 but I think it probably should be. >>Yeah, absolutely. And in fact, that that was some of the genesis of some of the next industrial services that we announced that are based on computer vision. What we saw on what we heard when talking to these customers is they have what we call human inspection processes or manual inspection processes that are required today for everything from, you know, monitoring you like workplace safety, too, you know, quality of goods coming off of a machinery line or monitoring their yard and sort of their, you know, truck entry and exit on their looking for computer vision toe automate a lot of these tasks. And so we just announced a couple new services that use computer vision to do that to automate these once previously manual inspection tasks. So let's start with a W A. W s Panorama uses computer vision toe improve those operations and workplace safety. AWS Panorama is, uh, comes in two flavors. There's an appliance, which is, ah, box like this. Um, it basically can go get installed on your network, and it will automatically discover and start processing the video feeds from existing cameras. So there's no additional capital expense to take a W s panorama and have it apply computer vision to the cameras that you've already got deployed, you know, So customers are are seeing that, um, you know, computer vision is valuable, but the reason they want to do this at the edge and put this computer vision on site is because sometimes they need to make very low Leighton see decisions where if you have, like a fast moving industrial process, you can use computer vision. But I don't really want to incur the cost of sending data to the cloud and back. I need to make a split second decision, so we need machine learning that happens on premise. Sometimes they don't want to stream high bandwidth video. Or they just don't have the bandwidth to get this video back to the cloud and sometimes their data governance or privacy restrictions that restrict the company's ability to send images or video from their site, um, off site to the cloud. And so this is why Panorama takes this machine learning and makes it happen right here on the edge for customers. So we've got customers like Cargill who uses or who is going to use Panorama to improve their yard management. They wanna use computer vision to detect the size of trucks that drive into their granaries and then automatically assign them to an appropriately sized loading dock. You've got a customer like Siemens Mobility who you know, works with municipalities on, you know, traffic on by other transport solutions. They're going to use AWS Panorama to take advantage of those existing kind of traffic cameras and build machine learning models that can, you know, improve congestion, allocate curbside space, optimize parking. We've also got retail customers. For instance, Parkland is a Canadian fuel station, um, and retailer, you know, like a little quick stop, and they want to use Panorama to do things like count the people coming in and out of their stores and do heat maps like, Where are people visiting my store so I can optimize retail promotions and product placement? >>That's fantastic. The number of use cases is just, I imagine if we had more time like you could keep going and going. But thank you so much for not only sharing what's going on with Deep Racer and the innovations, but also for show until even though we weren't in person at reinvent this year, Great to have you back on the Cube. Mike. We appreciate your time. Yeah, thanks, Lisa, for having me. I appreciate it for Mike Miller. I'm Lisa Martin. You're watching the cubes Live coverage of aws reinvent 2020.

>>live from Atlanta, Georgia. It's the Q covering Answerable Fest 2019. Brought to you by >>Red Hat. >>Okay, welcome back. It runs two cubes. Live coverage of Ansel Fest here in Atlanta, Georgia. I'm John for a host of the Cube with stewed Minutemen. Analysts were looking angle. The Cube are next to guest Tom Anderson and most product owner. Red Hat is part of the sensible platform automation properly announced. And Richard Henshaw, product manager. Guys, welcome to the Cube Way had all the execs on yesterday and some customers all pretty jazzed up about this year, mainly around just the timing of how automation is really hitting the scene and some of the scale that's going on. You guys had big news with the answerable automation platform. New addition to the portfolio. What's the feedback? >>So far, I think the feedback has been super positive. We have customers have come to us. A lot of the last little one said, Hey, we're maturing. We're moving along the automation maturity curve, right, and we have multiple teams coming to us and saying, Hey, can you help us connect this other team? We've had a lot of success doing cloud provisioning or doing network automation were doing security automation. What have you and they're coming to us and saying, Help us give us kind of the story if you will, to be able to connect these other teams in our organization. And so that way I kind of feel the pole for this thing to move from a tool that automates this or that. This task for that task. Too much more of a platform center. >>It seems to be scaling out in terms of what automation is touching these days. And look at the numbers six million plus activations on get Hub versus other projects. So activities high in the community. But this seems to be much more broader. Scope now. Bring more things together. What's the rationale behind? What's the reasoning? What's the strategy? But the main thing is, >>automation is got to that point where it's becoming the skill set that we do. So it was always the focus. You know, I'm a database administrator. I'm assists out, man. I'm a middle where I'm a nap deaf on those people, then would do task inside their job. But now we're going to the point off, actually, anybody that can see apiece. Technology can automate piece technology in the clouds have shown This is the way to go forward with the things what we had. We bring that not just in places where it's being created from scratch, a new How do you bring that into what's existing? Because a lot of our customers have 20 or 30 years like a heritage in the I T estate. How do you do with all of that? You can't just rebuild everything into new as well. So you gotta be ableto automate across both of those areas and try and keep. You know, we say it's administrative efficiency versus organization effectiveness. Now how do I get to the point of the organization? Could be effective, supposed just doing things that make my job easier. And that's what we're gonna bring with applying automation capability that anybody can take advantage of. >>Richard. I actually felt the keynote demo this morning did a nice job of that line that they set it up with is this is this is tools that that all the various roles and teams just get it, and it's not the old traditional okay, I do my piece and set it up and then throw it over the wall. There was that, you know? Oh, I've got the notification and then some feedback loops and, you know, we huddled for something and it gets done rather fast, not magic. It's still when I get a certain piece done. Okay, I need to wait for it's actually be up and running, but you know, you're getting everybody into really a enterprise collaboration, almost with the tool driving those activities together >>on that. And that's why yesterday said that focus on collaboration is the great thing. All teams need to do that to be more successful because you get Maur inclusivity, Maurin puts. But organizations also need to coordinate what activities they're doing because they have rules, regulations, structures and standards they have to apply. Make sure that those people can do things in a way that's guided for them so that they're they're effective at what they're trying to do. >>Okay, I think I'm going to explain what's in the platform first because an engine and tower and there, what else is in there, what's new? What's what our customers is going to see. That's new. That's different >>it's the new components are automation Hope Collections, which is a technology inside answer ball itself. On also Automation Analytics and the casing is that engine and terrorist of the beating heart of the platform. But it's about building the body around the outside. So automation is about discover abilities like, What can we find out? What automation can I do that I'm allowed to do? Um, and let six is about the post activity. So I've automated all these things. I've done all this work well, How did it go? Who did what, who did? How much of what? How well did it work? How much did it failed? Succeeds and then, once you build on that, you don't start to expand out into other areas. So what? KP eyes, How much of what I do is automated versus no automated? You can start to instigate other aspects of business change, then Gamification amongst teams. Who's the Who's the boat? The closest motive here into the strategy input source toe How? >>Find out what's working right, essentially and sharing mechanism to for other groups in terms of knowing what's happening >>and how is my platform performing which areas are performing well, which airs might not be performing well. And then, as we move down the road, kind of how my performing against my peers are other organizations that are automating using the ants will automation platform doing? And am I keeping up on my doing better? That kind of stuff. >>So, Tom, there's a robust community as we was talking about. Their platform feels like it builds on yet to change the dynamic a little bit. When you talk about the automation hub and collections, you've already got a long list of the ecosystem vendors that are participating here. Bring us two through a little bit. What led Thio. You know all these announcements and where you expect, you know, how would this change the dynamics of >>the body? And maybe we'll split up that question. I'll talk a little bit about partners because it's both partners and customers in community here that's been driving us this way. I'll talk a little bit about partners and Rich talk about the customer piece here, which is partners have been traditionally distributing their content there. Ansel automation content through our engine capability. So our engine release cycle, or cadence, has been sort of the limiting factor to how fast they can get content out to their users and what what the collections does is part of the platforms allows us to separate those things. Rich talked about it yesterday in his keynote, having that stable platform. But you having yet having content be able to read fast. And our partners love that idea because they can content. They can develop content, create content, get into their users hands faster. So partners like at five and Microsoft you've seen on stage here are both huge contributors. And they've been part of the pole for us to get to the platform >>from a customer perspective. And the thing I love most about doing this job with the gas of customers is because I was a customer on Guy was danceable customer, and then I came over to this side on Dhe. I now go and see customers. I see what they've done, and I know what that's what I want to do. Or that's what I was trying to do. And she started to see those what people wanted to achieve, and I was said yesterday it is moving away from should I automate. How would we automate Maura? What should I automate? And so we'll start to see how customers are building their capabilities. And there's no there's many different ways people do. This is about different customers, >>you know. What's interesting is you guys have such a great success formula first. Well, congratulations. It's great to see how this is turning into such a wider market, because is not just the niche configuration management. More automation become with cloud to point a whole new wider category. So congratulations. The formula we see with success is good product, community customers adopting and then ecosystem that seems to be the successful former in these kinds of growth growth waves you guys experiencing? What is the partnering with you mentioned? S five Microsoft? Because that, to me, is gonna be a tipping point in a tel sign for you guys because you got the community. You got the customers that check check ecosystem. What's the partner angle? How do they involve? Take us through that. What's going on? They're >>so you're absolutely so you know, kind of platform velocity will be driven by partner adoption and how many things customers can automate on that platform or through that platform and for us I mean, the example was in the demo this morning where they went to the automation hub and they pulled down the F five collection, plugged it into a workflow, and they were automating. What are partners? Experience through their customers is Look, if I'm a customer, I have a multi cloud environment or hybrid cloud environment. I've got automation from AWS. I've got azure automation via more automation. Five. Got Sisko. I've got Palo Alto. I've got all these different automation tools to try and string them together, and the customers are coming and telling those vendors Look, we don't want to use your automation to end this automation tooling that one we want to use Ansel is the common substrate if you will automation substrate across this platform. So that's motivating the partners to come to us and say, Hey, I had I was out five Aspire last week, and they're all in a natural. I mean, it's really impressive to see just how much there in unanswerable and how much they're being driven by their customers when they do Ansell workshops without five, they say the attendance is amazing so they're being pulled by their customers and therefore the partners are coming to us. And that's driving our platform kind of usability across the across the scale. >>Another angle we'll see when we talk to the engineers of the partners that are actually doing the work to work with danceable is that they're seeing is ah, change also in how they it's no longer like an individual customer side individual day center because everything is so much more open and so much more visible. You know there's value in there, making it appealing and easy for their customers to gain advantage of what they're doing. And also the fact that the scales across those customers as well because they have their internal team's doing it, saying the same things and so bringing them to an automation capable, like Ansel have to push. That means that they also gained some of the customers appreciation for them, making it easier to do their tasking collaboration with us and you know, the best collaborations. We've got some more partners, all initiated by customers, saying Hey, I want you to go and get danceable content, >>the customer driving a lot of behavior, the guest system. Correct. On the just another point, we've been hearing a lot of security side separate sector, but cyber security. A lot of customers are building teams internally, Dev teams building their own stacks and then telling the suppliers a support my AP eyes. So now you start to see more of a P I integration point. Is that something that is gonna be something that you guys gonna be doubling down on? What's that? What's the approach there? How does that partner connected scale with the customers? So we've >>been eso Ansel security automation, which is the automation connecting I. P. S. C. P. S that kind of stuff. It is almost a replay of what we did the network automation space. So we saw a need in the network automation space. We feel that we became a catalyst in the community with our partners and our customers and our and our contributors. And after about three years now, Ansel Network automation is a huge piece of our business and adoption curve. We're doing the exactly see the exact same thing in the security automation space compliance. The side over here, we're talking about kind of automating the connections between your firewalls, your threat detection systems and all that kind of stuff. So we're working with a set of partners, whether it's Cisco, whether it's Palo Alto, whether it's whether it's resilient by the EMS, resilient and being able to connect and automate the connections between the threat and the response and and all of that kind of >>the same trajectory as the network automation >>Zach. Same trajectory, just runnin the same play and it's working out right now. We're on that kind of early part of that curve, that adoption curve, and we have partners jumping in with us. >>You're talking to customers. We've heard certain stories. You know how I got, you know, 1000 hours of work down to a dozen hours of work there. Is there anything built into the tool today that allows them to kind of generate those those hero stats O. R. Any anything along those lines? >>Talk about analytic committee from yes, >>well, again without any analytic side. I mean, those things starts become possible that one of the things we've been doing is turning on Maur more metrics. And it's actually about mining the data for the customer because Tower gives this great focal point for all the automation that's going on. It's somewhere that everything comes through. So when we export that and then we can we can do that work for all the customers rather than have to duel themselves. Then you start to build those pictures and we start with a few different areas. But as we advance with those and start, see how people use them and start having that conversation customers about what data they want to use and how they want to use it, I think that's gonna be very possible. You know, it's so >>important. E think was laid out here nicely. That automation goes from a tactical solution to more strategic, but more and more how customers can leverage that data and be data driven. That's that's gonna drive them for it. And any good customer examples you have of the outcomes. No, you're talking to a lot of >>PS one from this morning. Yeah, >>so I mean, I'll be Esther up this morning, and I think that the numbers they used in the demo that she's like, you know, last year they did 100,000 from launch to the end of the year. 100,000 changes through their platform on this year so far that in a 1,000,000. So now you know, from my recollection, that's about the same time frame on either side of the year. So that's a pretty impressive acceleration. Side of things. We've had other ones where people have said, You know how many times you were telling some customers yesterday? What used to take eight hours to a D R test with 20 or 30 people in for the weekend now takes 12 minutes for two People on the base is just pushing a few buttons just as they go through and confirm everything worked that that type of you can't get away from that type of change. >>J. P. Morgan example yesterday was pretty compelling. I mean, time savings and people are, I mean, this legit times. I mean, we're talking serious order of magnitude, time savings. So that's awesome. Then I want to ask you guys, Next is we're seeing another pattern in the market where amongst your customer base, where it's the same problem being automated, allover the place so playbooks become kind of key as that starts to happen is that where the insights kind of comes in? Can you help us kind of tie that together? Because if I'm a large enterprise with its I'm decentralized or centralized, are organized problem getting more gear? I'm getting more clouds, game or operations. There's more surface area of stuff and certainly five g I ot is coming around the corner. Mention security. All this is expanding to be much more touchpoints. Automation seems to be the killer app for this automation, those mundane task, but also identifying new things, right? Can you guys comment on that? >>Yeah, so maybe I'll start rich. You could jump in, which is a little bit around, uh, particularly those large accounts where you have these different disparate teams taking a approach to automate something, using Ansel and then be able to repeat or reuse that somewhere else. The organization. So that idea of being for them to be able to curate they're automation content that they've created. Maybe they pulled something down from galaxy. Maybe they've got something from our automation husband. They've made it their own, and now they want to curate that and spread it across the organization to either obviously become more efficient, but also in four standards. That's where automation hub is going to come into play here. Not only will it be a repo for certify content from us and our partners, but it will also be an opportunity for them to curate their own content and share it across the organization. >>Yeah, I think when you tie those two things together and you've got that call discover abilities, I had away go and find what I want. And then the next day, the next day, after you've run the automation, you then got the nerve to say, Well, who's who's using the right corporate approved rolls? Who's using the same set of rolls from the team that builds the standards to make sure you're gonna compliant build again, showing the demo That's just admin has his way of doing it, puts the security baseline application on top and you go, Oh, okay, who's running that security baseline continuously every time. So you can both imposed the the security standards in the way the build works. But you can also validate that everybody is actually doing the security standards. >>You what I find fascinating about what you guys are doing, and I think this is came out clearly yesterday and you guys are talking about it. And some of the community conversations is a social construct here. Going on is that there's a cultural shift where the benefits that you guys are throwing off with the automation is creating a network effect within the companies. So it's not just having a slack channel on texting. The servers are up or down. It's much more of a tighter bond between the stakeholders inside the company's. Because you have people from different geography is you have champions driving change. And there's some solidarity happening between the groups of people, whether they're silo door decentralized. So there's a whole new social network, almost a cultural shift that's happening with the standardization of the substrate. Can you guys comment on this dynamic? Did you see this coming? You planning forward? Are you doubling down on it? >>I think so. And we talk about community right on how important that is. But how did you create that community internally and so ask balls like the catalyst so most teams don't actually need to understand in their current day jobs. Get on all the Dev ops, focus tools or the next generation. Then you bring answer because they want to automate, and suddenly they go. Okay, Now I need to understand source control, and it's honest and version. I need to understand how to get pulls a full request on this and so on and so forth on it changes that provides this off. The catalyst for them to focus on what changed they have to make about how they work, because what they wanted to do was something that requires them to do you no good disciplines and good behaviors that previously there was no motivation or need to do. I think >>Bart for Microsoft hit on that yesterday. You know, if you saw Bart Session but their network engineers having to get familiar with concepts of using automation almost like software development, life cycles right and starting to manage those things in repose. And think of it that way, which is intimidating at first for people who are not used to. But once they're over that kind of humping understand that the answer language itself is simple, and our operations person admin can use it. No problem, >>he said himself. Didn't my network engineers have become network developers. >>It's funny watching and talking to a bunch of customers. They all have their automation journey that they're going through. And I hear the Gamification I'm like, Okay, what if I have certain levels I have to reach in it unlocked capabilities, you know, in the community along the way. Maybe that could build a built in the future. >>Maybe it's swag based, you know, you >>get level C shows that nice work environment when you're not talking about the server's down on some slack channel when you're actually focusing on work. Yeah, so that mean that's the shift. That's what I'm saying, going >>firefighting to being able to >>do for throwing bombs. Yeah, wars. And the guy was going through this >>myself. Now you start a lot of the different team to the deaf teams and the ops teams. And I say it would be nice if these teams don't have to talk to complain about something that hadn't worked. It was Mexican figured it was just like I just like to talk to you because you're my friend. My colleague and I'd like to have a chat because everything's working because it's all automated, so it's consistent. It's repeatable. That's a nice, nice way. It can change the way that people get to interact because it's no longer only phoned me up when something's wrong. I think that absent an interesting dynamic >>on our survey, our customer base in our community before things one of the four things that came up was happier employees. Because if they're getting stuff done and more efficient, they have more time to actually self actualizing their job. That becomes an interesting It's not just a checkbox in some HR manual actually really impact. >>And I kind of think the customers we've heard talk rvs, gentlemen, this morning gave me a lot of the fear initially is, well, I automate myself out of a job, and what we've heard from everybody is that's not absolutely That's not actually true at all. It just allows them to do higher value things that, um or pro >>after that big data, that automation thing. That's ridiculous. >>I didn't use it yesterday. My little Joe Comet with that is when I tried to explain to my father what I do. Andi just said Well, in the 19 seventies, they said that computers you mean we'll do a two day week on? That hasn't come >>true. Trade your beeper and for a phone full of pots. But Richard, Thanks for coming on. Thanks for unpacking the ants. Full automation platforms with features. Congratulations. Great to see the progress. Thank you, Jonah. Everybody will be following you guys to Cuba. Coverage here in Atlanta, First Amendment Stevens for day two of cube coverage after this short break.

>>live from Atlanta, Georgia. It's the Q covering Answerable Fest 2019. Brought to you by Red Hat. >>Hey, welcome back, everyone. It's the cubes. Live coverage here in Atlanta, Georgia, for answerable fast. Part of redheads. Big news. Ansel Automation Platform was announced. Among other things, they're great products. I'm John for ear, with my coast to minimum, but two great guests. You unpack all the automation platform features and benefits. Walter Bentley, senior manager. Automation Practicing red hat and vj Job Olu, director of Red Hat Consulting Guys Thanks for coming on. Thanks. So the activity is high. The buzz this year seems to be at an inflection point as this category really aperture grows big time seeing automation, touching a lot of things. Standardization. We heard glue layer standard substrate. This is what answer is becoming so lots of service opportunity, lot of happy customers, a lot of customers taking it to the next level. And a lot of customers trying to consolidate figure out hadn't make answerable kind of a standard of other couples coming in. You guys on the front lines doing this. What's the buzz? What's the main store? What's the top story going on around the service is how to deploy this. What are you guys seeing? >>So I think what we're seeing now is customers. Reactor building automation. For a long time, I have been looking at it at a very tactical level, which is very department very focused on silo. Whether country realizes with this modern develops and the change in how they actually go to the market, they need to bring the different teams together. So they're actually looking at watching my enterprise automation strategy be how to actually take what I've learned in one organization. And I still roll it across the enterprise so that now struggling and figuring out how to be scared, what we have, how do we change the culture of the organization to collaborate a lot more and actually drive automation across enterprise? >>Walter One of the things we've been we've talked about all the time in the Cube, and it's become kind of cliche. Digital transformation. Okay, I heard that before, and three things people process, technology, process and capability you guys have done You mentioned the siloed having capabilities that's been there. Check was done very, very well as a product technology Red hat in the portfolio. Great synergies. We talked about rail integration, all the benefits there. But the interesting thing this year that I've noticed is the people side of the equation is interesting. The people are engaged, is changing their role because automation inherently changes there, function in the organization because it takes away probably the mundane tasks. This is a big part of the equation. You guys air hitting that mark. How do you How are you guys seeing that? How you accelerating that has that changing your job, >>right? So customers are now economy realizing that going after automation in a very tactical manner is not exactly getting them what they want as a far as a return on investment in the automation. And what they're realizing is that they need to do more. And they're coming to us and more of an enterprise architectural level and say we want to talk mortgage grander strategy. And what they're coming to realize is that having just one small team of people that were calling the Dev Ops team is not gonna be ableto drive that adoption across the organization. So what we're trying to do is work with customers to show them how they collaboration in the culture of peace is huge. It's a huge part of adopting automation. Answerable is no longer considered a emerging tech anymore. And and I when I say that, I mean a lot of organizations are using answerable in many different ways. They're past that point, and now they're moving on to the next part, which is what is our holistic strategy and how we're gonna approach automation. And And we wanted leverage danceable, unanswerable tower to do that. >>Does that change how you guys do your roll out your practices in some of your programs? >>Well, we did have to make some adjustments in the sense of recognizing that the cultural piece is a pivotal part of it, and we can go in and we can write playbooks and rolls, and we can do all those things really great. But now we need to go in and help them structure themselves in a way where they can foster that collaboration and keep a moment. >>And I'll actually add on to that so reactive, large, open innovation labs three years ago, and what we have to learn doing that is using labs and allows practices to actually help customers embrace new culture and change. How they actually operate has actually helped us take those practices and bring it into our programs and kind of drive that to our customers. So we actually run our automation adoption program and the journey for customers through those practices that we actually learned in open innovation loves like open practice, library, even storming priority sliders and all of those modern techniques. So the goal is to help our customers understand those practices and actually embrace them and bring them into the organization to drive the change that that's looking for within the organization. >>A. J. Is there anything particular for those adoption practices when you're talking about Cloud? Because the communication amongst teams silos, you know, making things simpler is something that we absolutely do need for cloud. So I'm just curious how you connect kind of the cloud journey with the automation journey. >>So all of the journey program that actually created, whether it's a contender adoption program or the automation adoption program, we actually followed the same practices. So whether you're actually focused on a specific automation to, like, answerable or actually embarking on hybrid multicolored journey. We actually use the same practices so the customers don't have toe learn new things every time you have to go from one product, one of the so that actually brings a consistent experience to customers in driving change within the organization. So let's picture whether it is focusing automation focused on cloud migrating to the cloud. The practices remained the same, and the focus is about not trying to boil the ocean on day one. Try to break it into manageable chunks that give it a gun back to the business quickly learned from the mistakes that you make in each of the way and actually build upon it and actually be successful. >>So, Walter, I always love when we get to talk to the people that are working straight with customers because you come here to the conference, it's like, Oh, it's really easy Get started. It doesn't matter what role or what team you're in. Everybody could be part of it. But when you get to the actual customers, they're stumbling blocks. You know what are some of those things? What are some of the key things that stop people from taking advantage of all the wonderful things that all the users here are doing >>well. One of the things that I've identified and we've identified as a team is a lot of organizations always want to blow the ocean. And when and when it comes down to automation, they feel that if they are not doing this grand transformation and doing this this huge project, then they're not doing automation. And the reality is is that we're Trent with showing them that you can break things up into smaller chunks, as Visi alluded to. And even if you fail, you fail fast and you can start over again because you're dealing with things in a smaller chunk. And we've also noticed that by doing that, we're able to show them to return on investment faster so they can show their leadership, and their leadership can stand behind that and want to doom. Or so that's one of the areas. And then I kind of alluded to the other area, which is you have to have everybody involved. You want just subject matter experts riding content to do the automation. You don't want that just being one silo team. You want to have everybody involved and collaborate as much as possible. >>Maybe can you give us an example? Is about the r A y How fast to people get the results and, you know, prove toe scale this out. >>So with the automation adoption journey, what we're able to do is is that we come in and sit down with our customers and walk them through how to properly document their use cases. What the dependencies, What integration points, possibly even determining what is that? All right, ranking for that use case. And then we move them very quickly in the next increment. And in the next increment, we actually step them through, taking those use cases, breaking them down into minimum viable products and then actually putting those in place. So within a 90 day or maybe a little bit more than a little bit more than the 90 day window, were able to show the customer in many different parts of the organization how they're able to take advantage of automation and how the return on investment with hopes of obviously reducing either man hours or being able to handle something that is no a mundane task that you had to do manually over and over again. >>What are some of the things that people get confused about when they look at the breath of what's going on with the automation platform? When I see tool to platform, transitions are natural. We've seen that many times in the industry that you guys have had product success, got great community, that customers, they're active. And now you've got an ecosystem developing so kind of things air popping on all cylinders here. >>So the biggest challenge that we're actually being seeing customers is they actually now come to realize that it's very difficult to change the culture of the organization right there, actually embarking on this journey and the biggest confusion that is, how do we actually go make those changes? How do we bring some of the open practice some of the open source collaboration that Riddle had into the organization so they actually can operate in a more open source, collaborative way, and what we have actually learned is we actually have what we call its communities of practice within Red Hack. It is actually community off consultants, engineers and business owners. The actual collaborate and work together on offering the solutions to the market. So we're taking those experiences back to our customers and enabling them to create those communities of practice and automation community that everybody can be a part off. They can share experiences and actually learn from each other much easier than kind of being a fly on the wall or kind of throwing something or defense to see what sticks and what does not. >>What's interesting about the boiling the ocean comment you mentioned Walter and B J is your point. There is, is that the boil? The ocean is very aspirational. We need change rights. That's more of the thing outcome that they're looking for. But to get there is really about taking those first steps, and the folks on the front lines have you their applications. They're trying to solve or manage. Getting those winds is key. So one of things that I'm interested in is the analytics piece showing the victory so in the winds early is super important because that kind of shows the road map of what the outcome may look like versus the throw the kitchen, sink at it and, you know, boil the ocean of which we know to the failed strategy. Take us through those analytics. What are some of the things that people tend to knock down first? What are some of the analytical points that people look at for KP eyes? Can you share some insight into that? >>Sure, sure. So we always encourage our customers to go after the platform first. And I know that may sound the obvious, but the platform is something that is pretty straightforward. Every organization has it. Every organization struggles with provisioning, whether of a private cloud, public cloud, virtualization, you name it. So we have the customer kind of go after the platform first and look at some of their day to operations. And we're finding that that's where the heaviest return on investment really sits. And then once you get past that, we can start looking like in the end, work flows. You know, can they tie service now to tower, to be able to make a complete work flow of someone that's maybe requesting a BM, and they can actually go through that whole workflow by by leveraging tower and integration point like service. Now those air where we're finding that the operators of these systems going getting the fastest benefit. And it also, of course, benefits the business at the end of the day because they get what they need a lot fast. >>It's like a best practice and for you guys, you've seen that? Yes, sir. Docked with that out of E. J. What's your comment on all this? >>So going back to the question on metrics Automation is great, but it does not provide anybody to the business under the actually show. What was the impact, whether it's from a people standpoint, cost standpoint or anything else. So what we try to drive is enable customers. You can't build the baseline off where they are today, and as they're going through the incremental journey towards automation, measure the success of that automation against the baseline. And that actually adds the other way back to the customer. As a business you didn't get to see. I was creating a storage land. I was doing it probably 15 times a month. Take it or really even automated. It spend like a day created a playbook. I'll save myself probably half, of course, and that could be doing something that's better. So building those metrics and with the automation analytics that actually came in the platform trying those bass lines. So the number of executions, actually the huge value they'll actually be ableto realize the benefits of automation and measure the success off within enterprise. >>So I'm a customer prospect, like I want to get a win. I don't want to get fired. I won't get promoted. Right, I say, Okay, I gotta get a baseline and knock down some playbooks. Knock that down first. That what you're gonna getting it. That's a good starting. >>Starting. Understand your baseline today. Plan your backlog as to what you want to knock down. And once you know them down, build a dashboard as to what the benefits were, what the impact was actually built upon it. You actually will see an incremental growth in your success with automation. >>And then you go to the workflow and too, and that's your selling point for the next level. Absolutely good playbook. Is that the automation programs that in a nutshell or is that more of a best practice >>those components of the ah, the automation adoption journey that we allow the customer to kind of decide how they want their journey to be crafted. Of course, we have a very specific way of going about and walking them through it. But we allowed in the kind of crap that journey and that is those the two components that make up the automation. >>We're gonna put you guys on the spot with the tough question We heard from G. P. Morgan yesterday on the Kino, which I thought was very compelling. You know, days, hours, two minutes. All this is great stuff. It's real impact. Other customers validate that. So, congratulations. Can you guys share any anecdotal stories? You know, the name customers? Just about situations Where customs gone from this to this old way, new way and throw some numbers around Shearson Samantha >>is not a public reference, but I like to give you a customer. Exactly. Retail company. When we first actually went and ran a discovery session, it took them 72 days to approach in an instance. And the whole point was not because it took that long. It because every task haven't s l. A We're actually wait for the Acela manually. Go do that. We actually went in >>with our 72 hours, two days, two days, >>actually, going with the automation? We Actually, it was everybody was working on the S L. A. We actually brought it down to less than a day. So you just gave the developers looking to code 71 days back for him to start writing code. So that's the impact that we see automation bringing back to the customers, right? And you'll probably find the use causes across everywhere. Whether J. P. Morgan Chase you actually had the British Army and everyone here on states talking about it. It is powerful, but it is powerful relief you can measure and learn from it >>as the baseline point. Get some other examples because that's that's, uh, that's 70 days is that mostly delay its bureaucracy. It's It's so much time. >>It's manual past and many of the manual tasks that actually waiting for a person to do the task >>waterfall past things sound, although any examples you can >>yes, so the one example that always stands out to me and again, it's a pretty interviewing straight forward. Is Citrix patching? So we work with the organization. They were energy company, and they wanted to automate patching their searches environment, patching this citrus environment took six weekends and it took at least five or six engineers. And we're talking about in bringing an application owners, the folks who are handling the bare metal, all all that whole window. And by automating most of the patching process, we were able to bring it down to one weekend in one engineer who could do it from home and basically monitor the process instead of having to be interactive and active with it. And to me, that that was a huge win. Even though it's, you know, it's such dispatching. >>That's the marketing plan. Get your weekends back. Absolutely awesome. Shrimp on the barbecue, You know, Absolutely great job, guys. Thanks for the insight. Thanks. Come on. The key. Really appreciate it. Congratulations. Thank you. Thanks for sharing this queue here. Live coverage. Danceable fest. Where the big news is the ass. Full automation platform. Breaking it down here on the Q. I'm John. First to Minutemen. We're back with more coverage after this short break

>>live from Atlanta, Georgia. It's the Q covering Answerable Fest 2019. Brought to you by Red Hat. >>Okay, welcome back. Everyone is the live Cube coverage for two days here in Atlanta, Georgia for instable fest. I'm John Furrier, My Coast stupid in with the Cube. Ted Julian, vice president, product management, formerly CEO. Resilient now part of an IBM company. Back to doing V P of product management. Again, you don't really ask. Welcome to welcome back to the Cube. Good to see you. It's a >>pleasure to be here. Thanks. >>So I see product management. Holistic thinking is the big discussion here. The thing that's coming out of this event is configuration management, a siloed point activity now, more of a platform. You're seeing more of a systems architecture thinking going into some of these platform discussion. Security certainly has been there. They're here now. A lot of pressure, the out of things built in with security but maintaining the onslaught of threats and landscape changes going on. That's what you do. >>It's rough out there. >>What what's going on? What are the key trends that customers should be aware of when thinking about configurations? Because automation can help. Yeah, maybe all use cases, but >>way need to do something and because customers definitely need help. The alerts that they're dealing with them both in the volume and the severity is like nothing we've ever seen before. At the same time we're talking about earlier, right, the regulatory impact also really big difference just in the last two or three years. Huge skills, gap shortage also a critical problem. People can't find enough people to do this work. That's very difficult to keep so clearly we need to do something different. And there's no doubt that orchestration and automation and configuration management, as a component of that is we've barely scratched the surface of the potential there. To help solve some of >>the open source is, is helping a lot of people now. Seeing the light first was cloud, the skeptics said. There's no security and cloud now. There is open source securities there, but still, proprietary systems have security. But the mayor may not be talented. Your point, so automation is an opportunity. How are companies dealing with the mishmash or the multi platform solutions that are out there >>at your right to ask the question it is driving, um, the problem in a big way. Years ago we tried this security automation within security, like in the early days of firewalls and the Web and stuff like that, and it didn't go well. Unintended consequences. But think two things have changed. The environments changed, which has raised the stakes for the need to be able to do this stuff to a whole different level. But at the same time, the technology matured enormously. There's been multiple platforms shifts since then, and so security teams. They're both kind of desperate for a better solution, but also better options now than they had before. And so it's for this reason that we're starting to see people adopt orchestration and automation now in a way that we didn't see in the last time around. >>But the thing is that we were hearing here is that people are trying to automate the same things and some of these holes in the infrastructure, whether it's an S three bucket, this is basic stuff. This is not rocket science. Yeah, so on these known use cases, this makes total sense that a playbook or automation could help kind of feel those holes. >>We talk about it as a journey, you know? And I don't think any two organizations journey is the same, nor does it really even need to be the same. So we've seen some customers, for example, take the approach of what's a high volume type of incident that we deal with. And if we could apply orchestration and automation, they were gonna get great our eye right? We see 4000 phishing attacks every month or what have you. And that's certainly one way to do it. Yeah, but those other times with one, >>though, I have to go >>into that point. There's other people that are like, you know, gathering forensics on an end point right now. Incredibly manual process. We need to be able to do that globally. Do we do it every day? No, we don't. But if we could automate that and get those results back in more like a couple hours, as opposed to two days, because the guy we need in Sweden is out of the office or whatever, that could mean the difference between ah, low level incident were able to contain and something that goes global. And so that's the use case we wanna chase, so I don't think there's a right or wrong answer. >>Depends on the environment. Ah, whole host of the whole thing about security is no general purpose software anymore. You have to really make it custom because every environments different. >>I mean, gosh, you guys Aaron Arcee, right? It's nuts. There's thousands of vendors. I mean, there's hundreds of vendors that are really products. They're not the features masquerading as products that are masquerading as companies. But there's a reason why that's been the case, and it's because the risk is so high. >>The desperation to >>yes, exactly good word choice. Yeah. >>So what? One of the things that reminded me of security is this morning hearing about, you know, J P. Morgan going through the transformation from the ticketing system. Tau wait to make a great case study two. I need to be able to automate things. So, you know, we know that response time is so critically important in the security area. So tell us how that meshes together from security and automation toe be able to response, and you know, whether it be patching or, you know, responding to an attack, >>there's huge opportunity gains there on. We've seen customers do some really remarkable things that start with what you're discussing, which is if we could automate that fishing process to a degree and we have 4000 of those a month and we're able to maybe shrink a response time by 80 some or more percent, which is what we've seen. That's a lot of savings right there. And you know, the meat and potatoes there is. You already have a fishing Neil Alias. Probably that that employees report those phishing attacks, too. But what if we just monitored that? We stripped those emails, stripped out the attachments, and we could automate all the manual grunt work that an analyst would otherwise do right? Is that and is there in execute a ble? Is that execute herbal? Unknown bad? What command and control servers is it talk to? Are those known bads those air 10 tabs That analyst could have opening their browser if we could automate all of that. So when they go into the case, it's all just sitting there for them. Huge time saver. >>It's the great proof point of the people plus machines. How do you make make sure that the people that when they get the information, they're not having to do too much grunt work. They get really focused on the things where their expertise in skill sets are needed, as opposed to just buried. You >>nailed it. I mean, automation is a great role to play, but it really is a subset of orchestration. It's when you can bring those two things together and really fuse the people process and technology via orchestration. That's when you get really game changing improvements. >>Talk about the relationship between you guys or silly, unanswerable. Where's the fit? What you guys doing together? Why year give a quick plug for what you working on? >>Yeah, absolutely. So just by working with customers, we kind of discovered that there was this growing groundswell of answerable use within our customer base. It was largely an I T, whereas that IBM resilient. We're selling mainly in a security. Um, and once we uncovered that were like, Oh my gosh, there's all these integrations that already exists. They're already using them for I t use cases on that side of the house, but a lot of the same work needs to be done as part of a security workflow. And so we built our integration where, literally you install that integration into resilient. And we have a visual workflow editor where you can define a sophisticated workflow. And what's that? Integration is in place. All of your instable integrations air there for you. You drag and drop them on near workflow. You can string them all together. I mean, it's really, really powerful. >>It's interesting. Stew and I and David Lattin Ovary Brother Q. Post. We got hundreds of events we see every conference. Everyone's going for the control plane layer. Don't control the data. I mean, it's aspiration, but it's You can't just say it. You gotta earn it. What's happening here is interesting in this country. Configuration management. Little sector is growing up because they control the plumbing, the control of the hardware, the piece parts right to the operating system. So the abstraction lee. It provides great value as it moves up the stack, no doubt, and this is where the impact is, and you guys are seeing it. So this dependency between or the interdependence between software glue that ties the core underpinnings together, whether it's observe ability data. It's not a silo, just context, which they're integrating together. This the collision course? Yeah. What's the impact gonna be here? What's your thesis on this? >>That's why there is such great synergy is because they are really were sort of the domain expertise Doreen experts on the security point of view and our ability to leverage that automation set of functions that answerable provides into this framework where you can define that workflow and all the rest that specific to some security use cases eyes just very, very complimentary to one another. >>This is a new kind of a 2.0 Kana infrastructure dynamic, where this enables program ability. Because if these are the control switch is on the gear and the equipment and the network routes, >>yeah, and where things get really interesting is when you do that in the context of ah, workflow and a case management system, which is part of what we provide, then you get a lot of really valuable metrics that are otherwise lost. If you're purely just at a point to point tool to to automation realm, and that allows you to look at organizational improvements because you're able to marry. Well, first of all, you can do things like better understand what kind of value those I t controls. Air providing you and the automation that you're able to deliver. But you can relate that to your people in your process as well. And so you can see, for example, that while we have two teams, they're doing that the ones in the day shift ones in the night shift. They have access to the same tool sets, but ones more effective than the other. First of all, you know that. But then, having known that you can now drill into that and figure out OK, why is the day shift better than the night shift? And you can say, Oh, well, they're doing things a little bit differently, maybe with how they're orchestrating this other team is, Or maybe they're not orchestrating it. All right? And you're having that. And then now you are able to knowledge share and, um improve that process to drive that continuous improvement. >>So this operational efficiency comes from breaking down these siloed exactly mentality data sets or staff? >>Yeah, and pairing. That was not just as I said, the IittIe automation aspect of weaken now do that 80% faster. But what about the people in the process aspect? We even bring that into the mix as well. You get that next limit layer of insight which kind of allows you to tap into another layer of productivity. >>So this is an alignment issue. This brings that back. The core cultural shift of Dev ups. This is the beginning of what operationalize ng Dev ops looks like. >>Yes. Yeah, >>people are working together. >>It's really, really well put. I mean, it gets back to how this question got started, which is what is this energy? And to me, this energy really is that you have these siloed all too often siloed functions of I t operations and security operations. And this integration between resilient and answerable is the glue that starts to pull those two things together to unlock everything we just talked about. >>Awesome. That's great. >>Yeah, well, you know, research has shown that you know, Dev Ops embracing, delivering and shipping code more frequently actually can improve security. Not You know what? We have to go through this separate process and slow everything down. So are you seeing what? What is that kind of end state organization look like? Oh, >>I mean, that's a huge transformation. And it's something that on the security field we've been struggling with for the longest time, because when we were in kind of a waterfall mode of sort of doing things I mean your timeframe of uncovering a security issue, addressing it in code code, getting deployed to a meaningful enough fashion and over a long enough time to get a benefit that could be years, right? But now that we're in this model, I mean, that could be so much, much more quickly obtained and obviously not only other great just General Roo I improvements that come from that, but your ability to shrink the threat window as a result of this as well as huge and that is crucial because all the same things that us, the good guys they're doing to be able to automate our defenses, the bad guys, they're doing the same thing in terms of how they're automating their attacks. And so we really have to. We have no choice. >>So, Ted, you were acquired by IBM. IBM made quite sizeable acquisition with Red Hat. Tell us what your IBM with danceable. How that should play out >>there is just enormous potential. And answerable is a big, big piece of it, without a doubt. And I think we're just scratching the tip of the iceberg for the benefits. They're just in the from resilience point of view. And, you know, we're not to stay in touch because we have some really interesting things coming down the pike in terms of next gen platforms and the role that that answer will complain those two and how those stretch across the security portfolio with an IBM more broadly and then even beyond that. >>Well, we want to keep in touch. We certainly have initiated Cube coverage this year on security. Cyber little bit going for a broader than the enterprise. Looking at the edge edges. You know about the perimeter. Being just disabled by this new service area takes one penetration lightbulb I p address. So again, organizing and configuring these policy based systems sounds like a configuration problem. Yeah, it is. This is where the software's gonna do it. Ted, Thanks for coming on. Sharing the insights. Any other updates on your front. What do you are most interested in what? Give us a quick update on what you're working on. >>Um, well, we're just getting started with the answerable stuff, so that's particularly notable here, but also kind of modern, modernizing our portfolio, and that really gets to the whole open shift side of the equation and the Red Hat acquisition as well, So not ready to announce anything yet. But some interesting things going on there that that kind of pull this all together and that serve as just one part of the foundation for the marriage between red at 9 p.m. and wanna sneak a value can bring the >>customers any sneak peek at all on the new direct. Sorry time. At least lips sink ships Don't do it. Love to no. >>Blame me for asking. >>Hey, I got a feeling hasn't automation. And somewhere in there Ted, thanks for sharing your insights. It was great to see Cuba coverage here. Danceable fest. I'm jumpers to minimum, breaking out all the action as this new automation feeds A I's gonna change the stack game as data is moving up to stack. This isn't Cube. Bring all the data will be back up to the short break. >>Um

>>live from Atlanta, Georgia. It's the Q covering answerable Best 2019. Brought to you by Red Hat. >>Welcome back. Everyone keeps live coverage of answerable fast here in Atlanta. Georgia John for my coach do Minutemen were here. Stephanie chairs to the vice president of general manager of the rail business unit. Red Hat. Great to see you. Nice to see you, too. You have all your three year career. IBM now Invincible. Back, Back in the fold. >>Yeah. >>So last time we chatted at Red Hat Summit Rail. Eight. How's it going? What's the update? >>Yeah, so we launched. Related some. It was a huge opportunity for arrested Sort of Show it off to the world. A couple of key things we really wanted to do There was make sure that we showed up the red hat portfolio. It wasn't just a product launch. It was really a portfolio. Lunch feedback so far on relate has been great. We have a lot of adopters on their early. It's still pretty early days. When you think about it, it's been about a little over 445 months. So, um, still early days the feedback has been good. You know it's actually interesting when you run a subscription based software model, because customers can choose to go to eight when they need those features and when they assess those features and they can pick and choose how they go. But we have a lot of folks who have areas of relate that they're testing the feature function off. >>I saw a tweet you had on your Twitter feed 28 years old, still growing up, still cool. >>Yeah, >>I mean 28 years old, The world's an adult now >>know Lennox is running. The enterprise is now, and now it's about how do you bring new innovation in when we launched Relate. We focused really on two sectors. One was, how do we help you run your business more efficiently? And then how do we help you grow your business with innovation? One of the key things we did, which is probably the one that stuck with me the most, was we actually partnered with the Redhead Management Organization and we pulled in the capability of what's called insights into the product itself. So all carbon subscription 678 all include insights, which is a rules based engine built upon the data that we have from, you know, over 15 years of helping customers run large scale Lennox deployments. And we leverage that data in order to bring that directly to customers. And that's been huge for us. And it's not only it's a first step into getting into answerable. >>I want to get your thoughts on We're here and Ansel Fest ate one of our two day coverage. The Red Hat announced the answer Automation platform. I'll see. That's the news. Why is this show so important in your mind? I mean, you see the internal. You've seen the history of the industry's a lot of technology changes happening in the modern enterprises. Now, as things become modernized both public sector and commercial, what's the most important thing happening? Why is this as well fest so important this year? >>To me, it comes down to, I'd say, kind of two key things. Management and automation are becoming one of the key decision makers that we see in our customers, and that's really driven by. They need to be efficient with what they have running today, and they need to be able to scale and grow into innovation. platform. So management and automation is a core critical decision point. I think the other aspect is, you know, Lennox started out 28 years ago proving to the world how open source development drives innovation. And that's what you see here. A danceable fest. This is the community coming together to drive innovation, super modular, able to provide impact right from everything from how you run your legacy systems to how you bring security to it into how do you bring new applications and deploy them in a safe and consistent way? It spans the whole gambit. >>So, Stephanie, you know, there's so much change going on in the industry you talked about, you know what's happening in Relate. I actually saw a couple of hello world T shirts which were given out at Summit in Boston this year, maybe help tie together how answerable fits into this. How does it help customers, you know, take advantage of the latest technology and and and move their companies along to be able to take advantage of some of the new features? >>Yeah, and so I really believe, of course, that unopened hybrid cloud, which is our vision of where people want to go, You need Lennox. So Lenox sits at the foundation. But to really deploy it in in a reasonable way in a Safeway in an efficient way, you need management on automation. So we've started on this journey. When we launched, we announced its summit that we brought in insights and that was our first step included in we've seen incredible uptick. So, um, when we launch, we've seen 87% increase since May in the number of systems that are linked in, we're seeing 33% more increase in coverage of rules based and 152% increase in customers who are using it. What that does is it creates a community of people using and getting value from it, but also giving value back because the more data we have, the better the rules get. So one interesting thing at the end of May, the engineering team they worked with all the customers that currently have insights. Lincoln and they did a scan for Specter meltdown, which, of course, everyone knows about in the industry with the customers who had systems hooked up, they found 100 and 76,000 customer systems that were vulnerable to Spector meltdown. What we did was we had unanswerable playbook that could re mediate that problem. We proactively alerted those customers. So now you start to see problems get identified with something like insights. Now you bring an answerable and answerable tower. You can effectively decide. So I want to re mediate. I can re mediate automatically. I can schedule that remediation for what's best for my company. So, you know, we've tied these three things together kind of in the stepwise function. In fact, if you have a real subscription, you've hooked up to insights. If insights finds an issue, there's a fix it and with answerable, creates a playbook. Now I can use that playbook and answerable tower so really ties through nicely through the whole portfolio to be able to to do everything in feeling. >>It also creates collaboration to these playbooks can be portable, move across the organization, do it once. That's the automation pieces that >>yeah, absolutely. So now we're seeing automation. How do you look at it across multiple teams within an organization so you could have a tower, a tower admin be able to set rules and boundaries for teams, I can have an array l writes. I t operations person be able to create playbooks for the security protocols. How do I set up a system being able to do things repeatedly and consistently brings a whole lot of value and security and efficiency? >>One of the powers of answerable is that it can live in a header Ji. In this environment, you got your windows environment. You know, I've talked of'em where customers that are using it and, of course, in cloud help help us understand kind of the realm. You know why rail plus answerable is, you know, an optimal solution for customers in those header ingenious environment. And what would love I heard a little bit in the keynote about kind of the road map where it's going. Maybe you can talk to about where those would fit together. >>Yeah, perfect and e think your comment about Header genius World is is Keith. That is the way we live, And folks will have to live in a head or a genius, a cz far as the eye can see. And I think that's part of the value, right to bring choice when you look at what we do with rail because of the close collaboration we have between my team and Theo team. That in the management bu around insights are engineering team is actively building rules so we can bring added value from the sense of we have our red Hat engineers who build rail creating rules to mitigate things, to help things with migration. So us develop well, Aden adoption. We put in in place upgrades, of course, in the product. But also there's a whole set of rules curated, supported by red hat that help you upgrade to relate from a prior version. So it's the tight engineering collaboration that we can bring. But to your point, it's, you know, we want to make sure that answerable and answerable tower and the rules that are set up bring added value to rebel and make that simple. But it does have to be in a head of a genius world. I'm gonna live with neighbors in any data center. Of course, >>what one of the pieces of the announcement talked about collections, eyes there, anything specific from from your team that it should be pointed out about from a collections in the platform announcement. >>So I think I think his collection starts to starts to grow on. Git brings out sort of the the simplicity of being pulled. It pulled playbooks and rolls on and pull that all in tow. One spot. We'll be looking at key scenarios that we pulled together that mean the most Terrell customers. Migration, of course, is one. We have other spaces, of course. Where we work with key ecosystem partners, of course, ASAP, Hana, running on rail has been a big focus for us in partnership with S A P. We have a playbook for installing ASAP Hana on Well, so this collaboration will continue to grow. I think collections offers a huge opportunity for a simpler experience to be able to kind of do a automated solution, if you will kind of on your floor >>automation for all. That's the theme here. >>That's what I >>want to get your thoughts on. The comment you made about analytical analytics keep it goes inside rail. This seems to be a key area for insights. Tying the two things together so kind of cohesive. But decoupled. I see how that works. What kind of analytical cables are you guys serving up today and what's coming around the corner because environments are changing. Hybrid and multi cloud are part of what everyone's talking about. Take care of the on premises. First, take care of the public cloud. Now, hybrids now on operating model has to look the same. This is a key thing. What kind of new capabilities of analytics do you see? >>Yes, that's it. So let me step you through that a little bit because because your point is exactly right. Our goal is to provide a single experience that can be on Prem or off Prem and provides value across both, as as you choose to deploy. So insights, which is the analytics engine that we use built upon our data. You can have that on Prem with. Well, you can have it off from with well, in the public cloud. So where we have data coming in from customers who are running well on the public cloud, so that provides a single view. So if you if you see a security vulnerability, you can skin your entire environment, Which is great. Um, I mentioned earlier. The more people we have participating, the more value comes so new rules are being created. So as a subscription model, you get more value as you go. And you can see the automation analytics that was announced today as part of the platform. So that brings analytics capabilities to, you know, first to be able to see what who's running what, how much value they're getting out of analytics, that the presentation by J. P. Morgan Chase was really compelling to see the value that automation is delivering to them. For a company to be ableto look at that in a dashboard with analytics automation, that's huge value, they can decide. Do we need to leverage it here more? Do we need to bring it value value here? Now you combine those two together, right? It's it, And being informed is the best. >>I want to get your reaction way Make common. Are opening student in our opening segment around the J. P. Morgan comment, you know, hours, two minutes, days, two minutes, depending on what the configurations. Automation is a wonderful thing. Where pro automation, as you know, we think it's gonna be huge category, but we took, um ah survey inside our community. We asked our practitioners in our community members about automation, and then they came back with the following. I want to get your reaction. Four. Major benefits. Automation focused efforts allows for better results. Efficiency. Security is a key driver in all this. You mentioned that automation drives job satisfaction, and then finally, the infrastructure Dev ops folks are getting re skilled up the stack as the software distraction. Those are the four main points of why automation is impacting enterprise. Do you agree with that? You make comments on some of those points? >>No, I do. I agree. I think skills is one thing that we've seen over and over again. Skills is skills. His key. We see it in Lennox. We have to help, right? Bridge window skills in tow. Lennox skills. I think automation that helps with skills development helps not only individuals but helps the company. I think the 2nd 2nd piece that you mentioned about job satisfaction at the end of the day, all of us want to have impact. And when you can leverage automation for one individual toe, have impact that that is much broader than they could do before with manual tasks. That's just that's just >>you know, Stew and I were talking also about the one of the key note keywords that kept on coming out and the keynote was scales scales, driving a lot of change in the industry at many levels. Certainly, software automation drives more value. When you have scale because you scaling more stuff, you can manually configure his stuff. A scale software certainly is gonna be a big part of that. But the role of cloud providers, the big cloud providers see IBM, Amazon, all the big enterprises like Microsoft. They're traveling massive scale. So there's a huge change in the open source community around how to deal with scale. This is a big topic of conversation. What's your thoughts on this? Sending general opinions on how the scales change in the open source equation. Is it more towards platforms, less tools, vice versa? Is there any trends? You see? >>I think it's interesting because I think when I think a scale, I think both volume right or quantity as the hyper scale ours do. I think also it's about complexity. I think I think the public clouds have great volume that they have to deal with in numbers of systems, but they have the ability to customize leveraging development teams and leveraging open source software they can customize. They can customize all the way down to the servers and the processor chips. As we know for most folks, right, they scale. But when they scale across on Prem in off from its adding complexity for them. And I think automation has value both in solving volume issues around scale, but also in complexity issues around scale. So even you know mid size businesses if they want a leverage on Prem, an off ramp to them, that's complexity scale. And I think automation has a huge amount of value to >>bring that abstracts away. The complexity automated, absolutely prized job satisfaction but also benefits of efficiency >>absolutely intimately. The greatest value of efficiency is now. There's more time to bring an innovation right. It's a zoo, Stephanie. >>Last thing I wondering, What feedback are you hearing from customers? You know, one of the things that struck me we're talking about the J. P. Morgan is they made great progress. But he said they had about a year of working with security of the cyber, the control groups to help get them through that knothole of allowing them toe really deploy automation. So, you know, usually something like answerable. You think? Oh, I can get a team. Let me get it going. But, oh, wait, no, Hold on. Corporate needs to make its way through. What is that something you hear generally? Is that a large enterprise thing? You know what? What are you hearing from customers that you're >>talking? I think I think we see it more and more, and it came up in the discussions today. The technical aspect is one aspect. The sort of cultural or the ability to pull it in is a whole separate aspect. And you think that technology from all of us who are engineers, we think, Well, that's the tough bit. But actually, the culture bit is just it's hard. One thing that that I see over and over again is the way cos air structured has a big impact. The more silo the teams are, do they have a way to communicate because fixing that so that you, when you bring in automation, it has that ability to sort of drive more ubiquitous value across. But if you're not structured toe leverage that it's really hard if your I T ops guys don't talk to the application folks bringing that value is very hard, so I think it is kind of going along in parallel right. The technical capabilities is one aspect. How you get your organization structure to reap the benefits is another aspect, and it's a journey. That's that's really what I see from folks. It is a journey. And, um, I think it's inspiring to see the stories here when they come back and talk about it. But to me the most, the greatest thing about it's just start right. Just start wherever you are and and our goal is to try and help on ramps for folks wherever their journey is, >>is a graft over people's careers and certainly the modernization of the enterprise and public sector and governments from how they procure technology to how they deploy and consume it is radically changing very quickly. By the way too scale on these things were happening. I've got to get your take on. I want to get your expert opinion on this because you have been in the industry of some of the different experiences. The cloud one Datta was the era of compute storage startups started Airbnb start all these companies examples of cloud scale. But now, as we start to get into the impact to businesses in the enterprise with hybrid multi cloud, there's a cloud. 2.0 equation again mentioned Observe Ability was just network management at White Space. Small category. Which company going public? It's important now kind of subsystem of cloud 2.0, automation seems to feel the same way we believe. What's your definition of cloud to point of cloud? One daughter was simply stand up some storage and compete. Use the public cloud and cloud to point is enterprise. What does that mean to you? What? How would you describe cloud to point? >>So my view is Cloud one Dato was all about capability. Cloud to Dato is all about experience, and that is bringing a whole do way that we look at every product in the stack, right? It has to be a seamless, simple experience, and that's where automation and management comes in in spades. Because all of that stuff you needed incapability having it be secure, having it be reliable, resilient. All of that still has to be there. But now you now you need the experience or to me, it's all about the experience and how you pull that together. And that's why we're hoping. You know, I'm thrilled here to be a danceable fast cause. The more I can work with the teams that are doing answerable and insights and the management aspect in the automation, it'll make the rail experience better >>than people think it's. Software drives it all. Absolutely. Adam, Thanks for sharing your insights on the case. Appreciate you coming back on and great to see you. >>Great to be here. Good to see >>you. Coverage here in Atlanta. I'm John for Stupid Men Cube coverage here and answerable Fest Maur coverage. After the short break, we'll be right back. >>Um

>> live from Boston, Massachusetts. It's the Cube covering A W s reinforce 2019. Brought to you by Amazon Web service is and its ecosystem partners. >> Well, welcome back. Everyone's Cube Live coverage here in Boston, Massachusetts, for AWS. Reinforce Amazon Web sources. First inaugural conference around security. It's not Osama. It's a branded event. Big time ecosystem developing. We have returning here. Cube Alumni Bill Jeff for VP of strategy and the partnerships that Iron Net Cyber Security Company. Welcome back. Thanks. General Keith Alexander, who was on a week and 1/2 ago. And it was public sector summit. Good to see you. Good >> to see you. Thanks for >> having my back, but I want to get into some of the Iran cyber communities. We had General Qi 1000. He was the original commander of the division. So important discussions that have around that. But don't get your take on the event. You guys, you're building a business. The minute cyber involved in public sector. This is commercial private partnership. Public relations coming together. Yeah. Your models are sharing so bringing public and private together important. >> Now that's exactly right. And it's really great to be here with eight of us were really close partner of AWS is we'll work with them our entire back in today. Runs on AWS really need opportunity. Get into the ecosystem, meet some of the folks that are working that we might work with my partner but to deliver a great product, right? And you're seeing a lot of people move to cloud, right? And so you know some of the big announcement that are happening here today. We're willing. We're looking to partner up with eight of us and be a first time provider for some key new Proactiv elves. AWS is launching in their own platform here today. So that's a really neat thing for us to be partnered up with this thing. Awesome organization. I'm doing some of >> the focus areas around reinforcing your party with Amazon shares for specifics. >> Yes. So I don't know whether they announced this capability where they're doing the announcement yesterday or today. So I forget which one so I'll leave that leave that leave that once pursued peace out. But the main thing is, they're announcing couple of new technology plays way our launch party with them on the civility place. So we're gonna be able to do what we were only wanted to do on Prem. We're gonna be able to do in the cloud with AWS in the cloud formation so that we'll deliver the same kind of guy that would deliver on prime customers inside their own cloud environments and their hybrid environment. So it's a it's a it's a sea change for us. The company, a sea change for a is delivering that new capability to their customers and really be able to defend a cloud network the way you would nonpregnant game changer >> described that value, if you would. >> Well, so you know, one of the key things about about a non pregnant where you could do you could look at all the flows coming past you. You look at all the data, look at in real time and develop behavior. Lana looks over. That's what we're doing our own prime customers today in the cloud with his world who looked a lox, right? And now, with the weight of your capability, we're gonna be able to integrate that and do a lot Maur the way we would in a in a in a normal sort of on Prem environment. So you really did love that. Really? Capability of scale >> Wagon is always killed. The predictive analytics, our visibility and what you could do. And too late. Exactly. Right. You guys solve that with this. What are some of the challenges that you see in cloud security that are different than on premise? Because that's the sea, So conversation we've been hearing. Sure, I know on premise. I didn't do it on premises for awhile. What's the difference between the challenge sets, the challenges and the opportunities they provide? >> Well, the opportunities air really neat, right? Because you've got that even they have a shared responsibility model, which is a little different than you officially have it. When it's on Prem, it's all yours essential. You own that responsibility and it is what it is in the cloud. Its share responsible to cloud provider the data holder. Right? But what's really cool about the cloud is you could deliver some really interesting Is that scale you do patch updates simultaneously, all your all your back end all your clients systems, even if depending how your provisioning cloud service is, you could deliver that update in real time. You have to worry about. I got to go to individual systems and update them, and some are updated. Summer passed. Some aren't right. Your servers are packed simultaneously. You take him down, you're bringing back up and they're ready to go, right? That's a really capability that for a sigh. So you're delivering this thing at scale. It's awesome now, So the challenge is right. It's a new environment so that you haven't dealt with before. A lot of times you feel the hybrid environment governed both an on Prem in sanitation and class sensation. Those have to talkto one another, right? And you might think about Well, how do I secure those those connections right now? And I think about spending money over here when I got all seduced to spend up here in the cloud. And that's gonna be a hard thing precisely to figure out, too. And so there are some challenges, but the great thing is, you got a whole ecosystem. Providers were one of them here in the AWS ecosystem. There are a lot here today, and you've got eight of us as a part of self who wants to make sure that they're super secure, but so are yours. Because if you have a problem in their cloud, that's a challenge. Them to market this other people. You talk about >> your story because your way interviews A couple weeks ago, you made a comment. I'm a recovering lawyer, kind of. You know, we all laughed, but you really start out in law, right? >> How did you end up here? Yeah, well, the truth is, I grew up sort of a technology or myself. My first computer is a trash 80 a trs 80 color computer. RadioShack four k of RAM on board, right. We only >> a true TRS 80. Only when I know what you're saying. That >> it was a beautiful system, right? Way stored with sword programs on cassette tapes. Right? And when we operated from four Keita 16 k way were the talk of the Rainbow Computer Club in Santa Monica, California Game changer. It was a game here for 16. Warning in with 60 give onboard. Ram. I mean, this is this is what you gonna do. And so you know, I went from that and I in >> trouble or something, you got to go to law school like you're right >> I mean, you know, look, I mean, you know it. So my dad, that was a chemist, right? So he loved computers, love science. But he also had an unrequited political boners body. He grew up in East Africa, Tanzania. It was always thought that he might be a minister in government. The Socialist came to power. They they had to leave you at the end of the day. And he came to the states and doing chemistry, which is course studies. But he still loved politics. So he raised at NPR. So when I went to college, I studied political science. But I paid my way through college doing computer support, life sciences department at the last moment. And I ran 10 based. He came on climate through ceilings and pulled network cable do punch down blocks, a little bit of fibrous placing. So, you know, I was still a murderer >> writing software in the scythe. >> One major, major air. And that was when when the web first came out and we had links. Don't you remember? That was a text based browser, right? And I remember looking to see him like this is terrible. Who would use http slash I'm going back to go for gophers. Awesome. Well, turns out I was totally wrong about Mosaic and Netscape. After that, it was It was it was all hands on >> deck. You got a great career. Been involved a lot in the confluence of policy politics and tech, which is actually perfect skill set for the challenge we're dealing. So I gotta ask you, what are some of the most important conversations that should be on the table right now? Because there's been a lot of conversations going on around from this technology. I has been around for many decades. This has been a policy problem. It's been a societal problem. But now this really focus on acute focus on a lot of key things. What are some of the most important things that you think should be on the table for techies? For policymakers, for business people, for lawmakers? >> One. I think we've got to figure out how to get really technology knowledge into the hands of policymakers. Right. You see, you watch the Facebook hearings on Capitol Hill. I mean, it was a joke. It was concerning right? I mean, anybody with a technology background to be concerned about what they saw there, and it's not the lawmakers fault. I mean, you know, we've got to empower them with that. And so we got to take technologist, threw it out, how to get them to talk policy and get them up on the hill and in the administration talking to folks, right? And one of the big outcomes, I think, has to come out of that conversation. What do we do about national level cybersecurity, Right, because we assume today that it's the rule. The private sector provides cyber security for their own companies, but in no other circumstance to expect that when it's a nation state attacker, wait. We don't expect Target or Wal Mart or any other company. J. P. Morgan have surface to air missiles on the roofs of their warehouses or their buildings to Vegas Russian bear bombers. Why, that's the job of the government. But when it comes to cyberspace, we expect Private Cummings defending us everything from a script kiddie in his basement to the criminal hacker in Eastern Europe to the nation state, whether Russia, China, Iran or North Korea and these nation states have virtually a limited resource. Your armies did >> sophisticated RND technology, and it's powerful exactly like a nuclear weaponry kind of impact for digital. >> Exactly. And how can we expect prices comes to defend themselves? It's not. It's not a fair fight. And so the government has to have some role. The questions? What role? How did that consist with our values, our principles, right? And how do we ensure that the Internet remains free and open, while still is sure that the president is not is not hampered in doing its job out there. And I love this top way talk about >> a lot, sometimes the future of warfare. Yeah, and that's really what we're talking about. You go back to Stuxnet, which opened Pandora's box 2016 election hack where you had, you know, the Russians trying to control the mean control, the narrative. As you pointed out, that that one video we did control the belief system you control population without firing a shot. 20 twenties gonna be really interesting. And now you see the U. S. Retaliate to Iran in cyberspace, right? Allegedly. And I was saying that we had a conversation with Robert Gates a couple years ago and I asked him. I said, Should we be Maur taking more of an offensive posture? And he said, Well, we have more to lose than the other guys Glasshouse problem? Yeah, What are your thoughts on? >> Look, certainly we rely intimately, inherently on the cyber infrastructure that that sort of is at the core of our economy at the core of the world economy. Increasingly, today, that being said, because it's so important to us all the more reason why we can't let attacks go Unresponded to write. And so if you're being attacked in cyberspace, you have to respond at some level because if you don't, you'll just keep getting punched. It's like the kid on the playground, right? If the bully keeps punching him and nobody does anything, not not the not the school administration, not the kid himself. Well, then the boy's gonna keep doing what he's doing. And so it's not surprising that were being tested by Iran by North Korea, by Russia by China, and they're getting more more aggressive because when we don't punch back, that's gonna happen. Now we don't have to punch back in cyberspace, right? A common sort of fetish about Cyrus is a >> response to the issue is gonna respond to the bully in this case, your eggs. Exactly. Playground Exactly. We'll talk about the Iran. >> So So if I If I if I can't Yeah, the response could be Hey, we could do this. Let them know you could Yes. And it's a your move >> ate well, And this is the key is that it's not just responding, right. So Bob Gates or told you we can't we talk about what we're doing. And even in the latest series of alleged responses to Iran, the reason we keep saying alleged is the U. S has not publicly acknowledged it, but the word has gotten out. Well, of course, it's not a particularly effective deterrence if you do something, but nobody knows you did it right. You gotta let it out that you did it. And frankly, you gotta own it and say, Hey, look, that guy punch me, I punch it back in the teeth. So you better not come after me, right? We don't do that in part because these cables grew up in the intelligence community at N S. A and the like, and we're very sensitive about that But the truth is, you have to know about your highest and capabilities. You could talk about your abilities. You could say, Here are my red lines. If you cross him, I'm gonna punch you back. If you do that, then by the way, you've gotta punch back. They'll let red lines be crossed and then not respond. And then you're gonna talk about some level of capabilities. It can't all be secret. Can't all be classified. Where >> are we in this debate? Me first. Well, you're referring to the Thursday online attack against the intelligence Iranian intelligence community for the tanker and the drone strike that they got together. Drone take down for an arm in our surveillance drones. >> But where are we >> in this debate of having this conversation where the government should protect and serve its people? And that's the role. Because if a army rolled in fiscal army dropped on the shores of Manhattan, I don't think Citibank would be sending their people out the fight. Right? Right. So, like, this is really happening. >> Where are we >> on this? Like, is it just sitting there on the >> table? What's happening? What's amazing about it? Hi. This was getting it going well, that that's a Q. What's been amazing? It's been happening since 2012 2011 right? We know about the Las Vegas Sands attack right by Iran. We know about North Korea's. We know about all these. They're going on here in the United States against private sector companies, not against the government. And there's largely been no response. Now we've seen Congress get more active. Congress just last year passed to pass legislation that gave Cyber command the authority on the president's surgery defenses orders to take action against Russia, Iran, North Korea and China. If certain cyber has happened, that's a good thing, right to give it. I'll be giving the clear authority right, and it appears the president willing to make some steps in that direction, So that's a positive step. Now, on the back end, though, you talk about what we do to harden ourselves, if that's gonna happen, right, and the government isn't ready today to defend the nation, even though the Constitution is about providing for the common defense, and we know that the part of defense for long. For a long time since Secretary Panetta has said that it is our mission to defend the nation, right? But we know they're not fully doing that. How do they empower private sector defense and one of keys That has got to be Look, if you're the intelligence community or the U. S. Government, you're Clinton. Tremendous sense of Dad about what you're seeing in foreign space about what the enemy is doing, what they're preparing for. You have got to share that in real time at machine speed with industry. And if you're not doing that and you're still count on industry to be the first line defense, well, then you're not empowered. That defense. And if you're on a pair of the defense, how do you spend them to defend themselves against the nation? State threats? That's a real cry. So >> much tighter public private relationship. >> Absolutely, absolutely. And it doesn't have to be the government stand in the front lines of the U. S. Internet is, though, is that you could even determine the boundaries of the U. S. Internet. Right? Nobody wants an essay or something out there doing that, but you do want is if you're gonna put the private sector in the in the line of first defense. We gotta empower that defense if you're not doing that than the government isn't doing its job. And so we gonna talk about this for a long time. I worked on that first piece of information sharing legislation with the House chairman, intelligence Chairman Mike Rogers and Dutch Ruppersberger from Maryland, right congressman from both sides of the aisle, working together to get a fresh your decision done that got done in 2015. But that's just a first step. The government's got to be willing to share classified information, scaled speed. We're still not seeing that. Yeah, How >> do people get involved? I mean, like, I'm not a political person. I'm a moderate in the middle. But >> how do I How do people get involved? How does the technology industry not not the >> policy budgets and the top that goes on the top tech companies, how to tech workers or people who love Tad and our patriots and or want freedom get involved? What's the best approach? >> Well, that's a great question. I think part of is learning how to talk policy. How do we get in front policymakers? Right. And we're I run. I run a think tank on the side at the National Institute at George Mason University's Anton Scalia Law School Way have a program funded by the Hewlett Foundation who were bringing in technologists about 25 of them. Actually. Our next our second event. This Siri's is gonna be in Chicago this weekend. We're trained these technologies, these air data scientists, engineers and, like talk Paul's right. These are people who said We want to be involved. We just don't know how to get involved And so we're training him up. That's a small program. There's a great program called Tech Congress, also funded by the U. A. Foundation that places technologists in policy positions in Congress. That's really cool. There's a lot of work going on, but those are small things, right. We need to do this, its scale. And so you know, what I would say is that their technology out there want to get involved, reach out to us, let us know well with our partners to help you get your information and dad about what's going on. Get your voice heard there. A lot of organizations to that wanna get technologies involved. That's another opportunity to get in. Get in the building is a >> story that we want to help tell on be involved in David. I feel passion about this. Is a date a problem? So there's some real tech goodness in there. Absolutely. People like to solve hard problems, right? I mean, we got a couple days of them. You've got a big heart problems. It's also for all the people out there who are Dev Ops Cloud people who like to work on solving heart problems. >> We got a lot >> of them. Let's do it. So what's going on? Iron? Give us the update Could plug for the company. Keith Alexander found a great guy great guests having on the Cube. That would give the quick thanks >> so much. So, you know, way have done two rounds of funding about 110,000,000. All in so excited. We have partners like Kleiner Perkins Forge point C five all supporting us. And now it's all about We just got a new co CEO in Bill Welshman. See Scaler and duo. So he grew Z scaler. $1,000,000,000 valuation he came in to do Oh, you know, they always had a great great exit. Also, we got him. We got Sean Foster in from from From Industry also. So Bill and Sean came together. We're now making this business move more rapidly. We're moving to the mid market. We're moving to a cloud platform or aggressively and so exciting times and iron it. We're coming toe big and small companies near you. We've got the capability. We're bringing advanced, persistent defense to bear on his heart problems that were threat analytics. I collected defence. That's the key to our operation. We're excited >> to doing it. I call N S A is a service, but that's not politically correct. But this is the Cube, so >> Well, look, if you're not, if you want to defensive scale, right, you want to do that. You know, ECE knows how to do that key down here at the forefront of that when he was in >> the government. Well, you guys are certainly on the cutting edge, riding that wave of common societal change technology impact for good, for defence, for just betterment, not make making a quick buck. Well, you know, look, it's a good business model by the way to be in that business. >> I mean, It's on our business cards. And John Xander means it. Our business. I'd say the Michigan T knows that he really means that, right? Rather private sector. We're looking to help companies to do the right thing and protect the nation, right? You know, I protect themselves >> better. Well, our missions to turn the lights on. Get those voices out there. Thanks for coming on. Sharing the lights. Keep covers here. Day one of two days of coverage. Eight of us reinforce here in Boston. Stay with us for more Day one after this short break.

(upbeat music) >> Live from Las Vegas, it's theCUBE! Covering Informatica World 2019. Brought to you by Informatica. >> Welcome back everyone to theCUBE's live coverage of Informatica World here in Las Vegas. I am your host, Rebecca Knight. We are joined by John Lieto. He is the Director, Data Management at Wolters Kluwer. Thank you so much for coming on the show. >> Very welcome. >> So, Wolters Kluwer is a global provider of professional information, software solutions, tax information. Tell our viewers a little bit more about the company and about your role at the company. >> Yeah, so Wolters Kluwer, I would say probably 20 years ago, was a typical holding company. Has a very long history of publishing in Europe. It's over 185 years old in Europe. But, went on a journey to acquire businesses that were in the services business with a focus on legal, but there are also big concentrations in health divisions, tax and accounting, really a professional company. Very, very, very big in print. What happened over the last 10, 15 years though, it's completely flipped over to digital. In fact, it's been one of the more successful transformations. So now we're mostly in the digital space and electronic space. So where I come in, and my business unit comes in, CT Corporation is a 126-year-old company. Number one player in registered agent services. Legal information, helping companies like Informatica stay in compliance. United States is 50 states with 50 sets of rules, plus international. So typically, companies of any size get a provider. Sometimes their law firms will do it, but a lot of times, it's going to be CT Corporations, things like that. My role in the company, I've been there 19 years, I've had a mix of roles, mostly in the business but a little technical. I'm the Director of Data Management, I am basically in charge of managing governance and data quality for the business. It is focused on the customer right now and all things related to customer, but we're expanding into other domains like vendors, products, suppliers and supporting of pretty large digital transformation. >> So I'm sure in your role you have a lot of practical insights for MDM practitioners but before we go there, I want to hear from you about the customer mindset, I mean, this is a moment for data governance and security... >> Sure >> and privacy, a real inflection point, and like Wolters Kluwer, so many companies undergoing their own digital transformations. How would you describe the customer mindset about all of this? How are customers wrapping their brains around it? >> So for us, we're not in a very regulated business. We touch customers that are heavily regulated, but we're not, we're a service company, right? Most of the stuff, the data we deal with is public knowledge, right? A company's data is public knowledge, you can go in any state website and find out when Informatica was formed, who the board of directors are, so it's all public. But customers are extremely sensitive about where their data is, and what we're doing with it, so we were on top of that, especially for our foreign customers. Internally the CT and Wolters Kluwer we have to be very, very, very customer-focused 'cause it's a very direct service, right? So it's all about the customer. How we got to this point of using Informatica MDM, Massive Data Management, is trying to get close to the customer, trying to understand the customer. Our customers go from J P Morgan to these big, big, big companies that have investments in companies that you wouldn't even know they're related to that customer. So they rely on us to help them stay compliant. How do I deal with these diverse businesses that are under my portfolio, and how do I keep them compliant in the States? So we have all this data and we help our customers understand it, and know what to do next, almost anticipate where they're going to fall out of compliance in the State. >> So what is your advice for the people who are really starting, for the executives starting at square one, trying to think about a master data management solution? >> Yeah, great question. And it's really where the heart of my devotion has been the last year. I would say the most important thing is start with a business case. Understand where your business is going. Make it about what outcomes are you looking for. Really thoroughly understand that. Also take the systems or the subjects that are important to you, your company, and profile it. Understand that data. You can come to an MDM project, a master data management project, with so much knowledge first, don't just say, well everybody is doing master data management, we should do it too. I mean, it might be true, but you're really not going to get the outcomes. And then focus your project to hit those business goals, 'cause MDM is a process and a tool, it's not an answer. You need to use that tool to get to where you are, so for us the number one thing was reduce duplication, okay, MDM tools do that, so we're trying to get to the golden record, okay. Data quality, I don't have the good phone numbers I have bad email addresses, oh, mass data management does that too. So, again, it's going for the outcomes you're driving for, and MDM happens to be a good tool for that. >> So it's really about defining the objectives before you even jump in. >> Absolutely. >> Do you recommend experiments? What's the approach you... >> Wonderful question. In data we call it profiling, right? And you want to go in small wins, because one of the things that will happen to anyone in this space is the business is really not sure about this investment. These days, data is becoming so huge that's becoming a lot easier for guys like me to win a business case, but two years ago it was pretty hard. I'm sorry I just lost my train of thought. >> But that's an interesting point, just talking about the overcoming the skepticism within these companies to latch on to this idea, and as you were saying, the announcing the small wins, really getting everyone on board. >> Thank you. What we did is, we had profiled, found a problem, oh, we have definitive cost duplication, we've got email addresses that are completely bogus. Let's just to take those two. And we did small little pilots. We'd use tools we had, completely manual ad-hoc, let's fix 200 records, let's take a really important customer that we're trying to onboard, or expand, and let's fix that data, and then show the outcomes. Go for the quick wins. Communicate, communicate, communicate. Once we did that, and we did a series of, I want to say, 30 or 40 of these. That built our requirement set. We built the requirement set by doing. It was so easy that way to show victories, but too, to really get the requirements to a point where we could build the system. We happened to fall on that method, from prior learnings of not doing well on projects that had nothing to do with MDM. So for this one, I think the other piece of advice that I would give folks, is we built a data management team of business analysts that know our business and data. It is really critical that you keep this function out of IT. IT is your supporter and your partner. This does not go to IT. So we know our data. I have a guy on my team that's 45 years in the company, a woman who's 28 years in the company, just for example. So we can do a lot without a tool, and what's happening is now we are live for going on eight months now, and we're staying on top, making sure the tool's delivering what it's supposed to deliver, based on our deep knowledge. >> And I think that what you're talking about really, is introducing this technology and this new way of thinking, and it's really all about change management. >> It truly is. >> One of the things that we're talking a lot here in theCUBE about is the skills gap, and this is a problem throughout the technology industry. How big a problem is it for you at Wolters Kluwer? And what are you doing to make sure that you have the right technical talent on your team, and as we're saying, not just the technical talent but also the understanding of the business? >> One thing to understand is Wolters Kluwer is a fairly big company, and we as a company are just starting this journey. I have a small data management team in one business unit at Wolters Kluwer. There's another business unit within our health division that has data management, and that's all that I know of that is a formal data management. That's pretty small, so it's just beginning. What we're doing, we're trying to communicate, communicate, communicate. I am having some success because in our next huge journey, which is a digital transformation, a six-year project, data now is center. I've been asked to actually be the business sponsor for the data track, which, two years ago, that would not have happened. So I take that as a win, but you make a fair point, skills and understanding, both at the business and technical level is always a challenge, and it's justifying bringing in that skill set. No we can just outsource that, or we'll just use a consultant. I'm right now fighting a battle to bring in a data architect, full-time, they don't understand that... >> Just that role. >> You have to architect things. We've now done that, so what you have, because I' doing the data governance piece right now, and what I'm finding is, it's not the Wild West, but you can't always know what the parts of the organization is doing, and a lack of an architect is not keeping all the plumbing all centralized. So, a I build this data governance, I'm going to centralize data definitions and data glossary, data catalog, but I'm going to be looking around and going, okay, how do I actually have the technology piece architected correctly and that's the piece I'm really trying to pump, so hopefully when we build this data layer we're building my goal is to prove to the business that you need to fill this role. It's not me, it's going to be someone who really is deep, deep, deep in architecture. >> Hire a contractor, get that small win. >> That's what we're doing. (laughing) >> And then, the proof. I learned that from you, John. >> I'm actually in the process of just doing that. >> Excellent! >> One of those vendors is here. >> Well, we'll look forward to talking to you next year and hearing an update. >> Yeah, there you go. >> John Lieto, thank you so much for coming on theCUBE. >> You're very welcome, thank you. >> I'm Rebecca Knight, we will have more of theCUBE's live coverage of Informatica World. Stay tuned! (upbeat musing)

>> from our studios in the heart of Silicon Valley, Palo Alto, California It is a cute conversation. >> Hi, I'm Peter. Boris, And welcome to another cube conversation from our wonderful studios and beautiful Paolo Alto, California. One of the biggest challenge that every enterprises faces how to attend to the volumes of data that are being generated by applications. But more importantly, that the business is now requiring because they want to find new derivative sources of value in their digital business. Transformations is gonna require a significant retooling and rethinking of how we used eight is an asset. And the directions that infrastructure, data management and business are gonna move together over the course of next few years. Now, have that conversation. Got a couple of great guests here. Josie Swoop is a VP of marketing veritas. Welcome to Cuba or back to the Cube. Yeah, thanks. Peter and Rick Clark is a CEO of opt are welcome. Thank you for the first time. >> Great to be here, >> So let me start here. Joey, why don't we start with you? Give us a quick update on Veritas and where your customers are indicating the direction needs to go. >> We've just had, ah, record breaking financial year for us, which ended in end of March. So since divestiture from semantic, as you know better, Toss has been through a transformation and then on a path to growth. So our core businesses are humming with just like I said, the second half of the year specifically was great for us. What we're hearing from customers, Peter, is that they want to elevate their their business problems away from infrastructure to business outcomes. That what they ask veritas to do is, can you abstract away some of those infrastructure plumbing problems, storage, security, data protection and focus on what the applications can give us. That's number one. Number two is Can we standardize? I mean, the example of Southwest comes to mind, right? They have the same plane so they can reroute those planes anytime they have the same pilots flying those planes so they can to standardize. So they collapsed better. And then, lastly, to your point value of data over volume. Everybody talks about the volume. What about the value of data? What is veritas do for for me? Mr. You know God's a customer in our tax extract value of that data, which is growing day by day. >> Well, one of the most interesting things about this challenge of businesses faces they try to attend to these things is that data is often characterizes the new oil. And we we push back against that Because >> data is a new kind of asset, it's an asset that's easily copied. It's an asset that's easily shared. You can easily integrate it. You can apply it to multiple uses with zero loss of fidelity and what it does currently. And so the whole notion of creating new options in the value of data's intrinsic to the questions of digital business. So that suggests that we need to start thinking Maur about data protection, not just from the standpoint of protecting data once it's been created and is sitting there so we can recover it. But new types of utilization, new ways of thinking about data data as it's going to be used, understanding more about dating, protecting that Rick, would you kind of Does that resonate? >> Yeah, absolutely. You know, one of the things that we've sort of seed in the marketplace is certainly over the last 10 years, the Data Sena has become so complex. This is massive fragmentation of data across highly virtualized infrastructures. And then, when public clouds came along, customers didn't really know what workloads they should move up into those clouds. And so what we saw is a huge problem. Is areas of cost and efficiencies, massive problems of risk and then obviously the amount of money that cos of spending on compliance. And so what we were really focusing on is the gaps. What do you not know about? And so we would really >> about your data >> about your data. Exactly. So we really measure the hot beat off the data protection environment, and from that we could actually see where are you? Risk where your exposure, where you're spending too much money, >> Where's your opportunities? Seize your opportunities. So we've got a notion of the the solution that folks are looking for, something that provides greater visibility into their end and data from a risk exposure opportunity. New sources of utilization standpoint talk a bit about how >> at four >> rounds out the veritas portfolio as it pertains of these things that you're seeing customers asked for taking data closer to outcomes and away from the device orientation? >> Absolutely. So Vatos has always been known to be a leader and data protection. We've done that for over 20 years. We also were the first pioneers in software defined storage. And we're number one in market share, according to I. D. C and Gardner as well. Ah, but again to my earlier point, customers have been asking. So what? We've done the plumbing really well and you've scaled. How do you take this to the next level? Extract value from all that data you're sitting on top of that you're protecting. And that's where apt are comes into the picture. We've built some tools natively within veritas of the last three or four years where we try to go and classify the data on in jest, identify things like P I information sensitive data, rock data, redundant, obsolete, trivial data that we can delete. There was a customer who recently deleted 30,000,000 files, just press the delete button and this isn't a highly regulated environment, >> but they were still pretty darn eggs. >> They definitely where but we were able to give them that visualization and information that they required. Now the question those customers are asking us or we're asking us. Before avatar came into the picture was at the infrastructure level. How do I know how much I'm spending on my data protection environments? Do I know where the growth ISS is it all in the traditional workloads of oracle ASAP, Or is it in virtual or is it in the cloud? Right. Am I putting too much data on tape? Is it costing me enough? Can extract the value from that data. So they were asking us infrastructure visualization and i D analytics. Questions which only apt are could answer. And we have some joint customers they were actually using. Apt are already not just with to monitor the vatos ecosystem, but even some of our competitors and the broader i t ecosystem on a single planet class. And that's where I think after really shines is is the agnostic approach they take beyond just veritas are beyond just another storage vendor. >> Well, so way certainly subscribed to this notion that data protection is going to It's gonna be extended, but it's gonna become a strategic digital business capability that does have to be re funk around the concept of data value and sounds like that's the direction you're taking, and you guys have clearly seen that as well. But obviously some of your customers have seen it. So talk to us a little bit about how customers helped you two guys together. >> Yeah, that's a great question. Was interesting. Actually. We had some of the largest companies in the globe actually using ourself with many of the fortune Tien using up self with J. P. Morgan Chase quote calm Western digital. And they came to us with these very precise problems around, you know, howto optimize my risk within the environment, had a streamline, obviously the costs and compliance. And we found that they were very common questions. And so we actually created this agnostic intelligence built into the software a rules engine that would have to correlate data from all of these disparate data sources. Whether Tom primer on the cloud tying that together would provide impactful insights to our customers that could sold real world problems. And we'll do it with kind of what we call the easy button. One of the big problems with a lot of software products out there today. Is there a point solutions to manage pots of the infrastructure companies wanted a single pane of glass where I could see everything across all of my storage. All of my data protection on prim and cloud. And that's really what we bring to the table, that single paying the class. And we do it very simply at scale for the largest customers. And that's in many ways was the synergy, obviously, with a partnership with Veritas. >> So give us some sense of how how customers will see the benefits of this from a rollout standpoint over the next 6 to 18. >> Right? So Step One in this journey for us is to ensure there are customers. Understand that we're going to continue to have that open an agnostic approach Apt are suddenly is not gonna become proprietary batter toss product. It's going to continue on its on its mission to be agnostic across various storage data protection and cloud environments. That's number one. Number two is we're gonna bring the the artificial intelligence and machine learning capabilities that we have in house with Veritas combined that with some of the things that Rick just docked, abide with the capabilities adapt our has combine, it's our customers can gain. I know add value. The one plus one equals three approach there as well. So those air, like the two key pillars for us going forward and eventually will extend apt are to an end to in Data Analytics platform not just I d analytics, where we're looking at infrastructure, but an end to end data. Plus I t analytics platform that spans Veritas is will Is the broader a IittIe ecosystem? >> Well, so it's good to hear that you're gonna let apt are continue to focus on data value as opposed to veritas value. Right talk. Talk to me a little bit. About what Does that analytics piece really mean? Howard Customers going to use it? How are they using it today? How are they gonna >> let me carry that? Said is roughly 30,000 unique metrics that we actually gather across the whole I t infrastructure and we'll look at a classic use cases. One of exposure. What? A lot of companies been enormous amount of money on the data protection infrastructure. The using disparity, tools and technologies they don't always go with. One platform like net backup is an example, right? And so with that, come challenges because there's gonna be gaps they might be backing up a Windows server where they're the backup policy says they're just backing up. The C drive will interrogate VM, where all the hyper visor will look at the network and see that there's a D Dr attached to that volume as well. And there's no backup data protection policy. So enormous amount of exposure if they tried to do a restore, obviously, from the d Dr where there's no protection, right from a cost perspective, there's an enormous amount of white space problem in the storage industry. More and more companies are moving from spinning distal flash arrays. A lot of companies is struggling with How do I protect those old flash A raise the using snapshots that using cloud they're tearing to the cloud the using different backup products. Obviously, we'd prefer that they used their backup, but with our software, we can provide that that inside across the entire data protection framework and storage and show you where is your risk? Where is your inefficiency, where you double protecting things into spending too much, much money? This whole notion of data protection is transaction. A lot of people do what's called distant, distant eight still being voted off site. How do you know that all those transactions are successful? How do you know you can restore based on those s L A's and tying that into you? See, M d B. That's what appetite does. >> So I'ma throw a little bit of a curveball here. So having worked within 90 worked with N i t organizations, it can be I ke historically can has been rolled to the compartmentalizing segment you administrated for servers in Australia for storage of people who are administrating applications and and subsystems. And the cloud is munge ing a fair amount of that together. But one of the places that has always required coordination, collaboration and even more important practice has been in the area of restore firms were shops that did not practice how they would restore, you know, hopefully they never had a problem. But if they did have a problem, if they hadn't practiced that process, they would likely we're not gonna be successful in bringing the business up. Gets even more important digital business. Can you give us a little bit of visibility into how this combination taking the metadata, the metrics of visibility. Taking the high quality service is bringing them together is going to streamline, restore within their prices. >> So first, let me address the first point you made, which is what I call the rise of the versatile is too right. So there are no more specialists in certain jobs. The versatile listen, the cloud or in virtual tend to do three or four jobs when there's back up our story virtualization itself on DDE. What the's Verceles want is to explain an easy barton to restore their VM environment or their big data. And my mother there Hadoop environment. They're not really worried. As a central I t. Team that Hey, what am I going to do with the entire data estate? How did I restore that? So that's the first step. Second step, as the world of I t gets more more complicated on the rise of the worst list continues to happen. Thes folks want to be able to have a resiliency plan. They want to be able to rehearse these restores right, and if they don't have a resiliency plan built in if the data protection is so siloed and does not help them build a resiliency plan. And to end that restore is not gonna be successful. Likely? Right. And that's where Veritas and companies like Veritas come in to help them build those resiliency plans and to end. >> But let me take you back to so the financial industry, for example, there are rules about how fast you you have to be able to restore. I gotta believe that visibility into data that is a value level can help set priorities. Because sometimes you want to bring up this application of this class of applications of this class of users of functions before you bring up those so does does apt are apt are going to provide even greater clarity in the crucial restore >> at 70. One of the biggest challenges for >> a lot of companies with restores is actually finding the data. We had a classic use case with a large Fortune 10 company where they had a bunch of service that were being backed up. There were bolted off the tape, and then it was obviously a different backup product they were using. The actually lost the catalog. The data was still there on tape. They had millions of tapes in the vaults, and they used apt title, identify the barcodes and recover that data literally within a matter of hours. And so not only can we find you your freshest copy the most recent copy, if that's what you want, but we can find where is your data? Because in a lot of cases there's multiple replications, multiple copies of the data across all sorts of assets within your >> infrastructure. Interesting. So last thoughts. When we have you back in the Cube in a year, Where you guys going? Big? >> Hey, listen, the two things that I talked about we're going to continue to expand the support of the ecosystem. The world of I t. Whether it's on Prem virtual or in the cloud with Apt are we? We're going to continue to invest in the artificial Intelligence and ML capabilities are not just apt are but all of that tosses ecosystem and you'll see amore integrated approach on the platform based approach on standardization When we come here >> next, guys, thank you so much. Great conversation. Thanks for being here in the Cube to talk about this important relation between data tooling and sources of business value. Rick Clark is the vice president of the outdoor business unit. Used to be the CEO of actor, but now the vice president. The outdoor business unit Veritas. Josie Stroop is vice president of marketing of Veritas. Once again, guys, thanks very much for being here. Thank you so much for having us. And once again, I'm Peter Burgers. You've been listening to another cube conversation until next time.

>> No. Yeah. Wait. >> Hi, everyone, and welcome to the big data. Deep Dive with the Cube on AMC TV. I'm Richard Schlessinger, and I'm here with tech industry entrepreneur and wicked bond analyst Dave Volonte and Silicon Angle CEO and editor in chief John Furrier. For this last segment in our show, we're talking about the future of big data and there aren't two better guys to talk about that you and glad that you guys were here. Let me sort of tee up the this conversation a little bit with a video that we did. Because the results of big data leveraging are only as good as the data itself. There has to be trust that the data is true and accurate and as unbiased as possible. So AMC TV addressed that issue, and we're just trying to sort of keep the dialogue going with this spot. >> We live in a world that is in a constant state of transformation, political natural transformation that has many faces, many consequences. A world overflowing with information with the potential to improve the lives of millions with prospects of nations with generations in the balance way are awakening to the power of big data way trust and together transform our future. >> So, Gentlemen Trust, without that, where are we and how big of an issue is that in the world of big data? Well, you know, the old saying garbage in garbage out in the old days, the single version of the truth was what you were after with data warehousing. And people say that we're further away from a single version of the truth. Now with all this data. But the reality is with big data and these new algorithms you, khun algorithmic Lee, weed out the false positives, get rid of the bad data and mathematically get to the good data a lot faster than you could before. Without a lot of processes around it. The machines can do it for you. So, John, while we were watching that video, you murmured something about how this is the biggest issue. This is cutting edge stuff. This is what I mean. >> Trust, trust issues and trust the trust equation. Right now it is still unknown. It's evolving fast. You see it with social networks, Stevens go viral on the internet and and we live in a system now with mobility and cloud things. Air scaling infinitely, you know, these days and so good day two scales, big and bad data scales being so whether it's a rumor on you here and this is viral or the data data, trust is the most important issue, and sometimes big data can be creepy. So a. This really, really important area. People are watching it on DH. Trust is the most important thing. >> But, you know, you have to earn trust, and we're still sort of at the beginning of this thing. So what has to happen to make sure that you know you don't get the garbage in, so you get the garbage. >> It's iterative and and we're seeing a lot of pilot projects. And then those pilot projects get reworked, and then they spawn into new projects. And so it's an evolution. And as I've said many, many times, it's very early we've talked about, were just barely scratching the surface here. >> It's evolving, too, and the nature of the data is needs to be questioned as well. So what kind of data? For instance, if you don't authorize your data to be viewed, there's all kinds of technical issues around. >> That's one side of it, But the other side of it, I mean, they're bad people out there who would try to influence, Uh, you know what? Whatever conclusions were being drawn by big data programs, >> especially when you think about big data sources. So companies start with their internal data, and they know that pretty well. They know where the warts are. They know how to manipulate. It's when they start bringing in outside data that this gets a lot fuzzier. >> Yeah, it's a problem. And security talk to a guy not long ago who thought that big data could be used to protect big data, that you could use big data techniques to detect anomalies in data that's coming into the system, which is poetic if nothing else, that guys think data has told me that that that's totally happened. It's a good solution. I want to move on because way really want to talk about how this stuff is going to be used. Assuming that these trust issues can be solved on and you know, the best minds in the world are working on this issue to try to figure out how to best, you know, leverage the data, we all produce, which has been measured at five exabytes every two days. You know, somebody made an analogy with, like something. If a bite was a paper clip and you stretched five exabytes worth of paper clips, they would go to the moon or whatever. Anyway, it's a lot of bike. It's a lot of actually, I think that's a lot of fun and back way too many times one hundred thousand times I lost track of my paper. But anyway, the best minds are trying to figure out, you know, howto, you know, maximize that the value that data. And they're doing that not far from here where we sit. Uh, Emmett in a place called C Sale, which was just recently set up, See Sail stands for the computer signs, an artificial intelligence lab. So we went there not long ago. It's just, you know, down the Mass. Pike was an easy trip, and this is what we found. It's fascinating >> Everybody's obviously talking about big data all the time, and you hear it gets used to mean all different types of things. So he thinks we're trying to do in the big data. Is he? Still program is to understand what are the different types of big data that exists in the world? And how do we help people to understand what different problems or fall under the the overall umbrella of big data? She sells the largest interdepartmental laboratory and mitt, so there's about one hundred principal investigators. So that's faculty and sort of senior research scientists. About nine hundred students who are involved, >> basically with big data, almost anything to do with it has to be in a much larger scale than we're used to, and the way it changes that equation is you have to You have to have the hardware and software to do the things you're used to doing. You have to meet them of comedy's a larger size a much larger size >> of times. When people talk about big data, they, I mean, not so much the volume of the data, but that the data, for example, is too complex for their existing data. Processing system to be able to deal with it. So it's I've got information from Social network from Twitter. I've got your information from a person's mobile phone. Maybe I've got information about retail records. Transactions hole Very diverse set of things that need to be combined together. What this clear? It says this is If you added this, credit it to your query, you would remove the dots that you selected. That's part of what we're trying to do here. And big data is he sail on. Our big data effort in general at MIT is toe build a set of software tools that allow people to take all these different data sets, combine them together, asked questions and run algorithms on top of them that allowed him to extracting sight. >> I'm working with it was dragged by NASA, but the purpose of my work right now is Tio Tio. Take data sets within Davis's, and instead of carrying them for table results, you query them, get visualizations. So instead of looking at large sets of numbers and text him or not, you get a picture and gave the motivation Behind that is that humans are really good into pretty pictures. They're not so that interpreting huge tables with big data, that's a really big issue. So this will have scientists tio visualize their data sets more quickly so they can start exploring And, uh, just looking at it faster, because with big data, it's a challenge to be able to visualize an exploiter data. >> I'm here just to proclaim what you already know, which is that the hour of big data has arrived in Massachusetts, and >> it's a very, very exciting time. So Governor Patrick was here just a few weeks ago to announce the Mass Big Data Initiative. And really, I think what he recognizes and is partly what we recognize here is that there's a expertise in the state of Massachusetts in areas that are related to big data, partly because of companies like AMC, as well as a number of other companies in this sort of database analytic space, CMC is a partner in our big data detail, initiatives and big data and See Sale is industry focused initiative that brings companies together to work with Emmet T. Think about it. Big data problems help to understand what big data means for the companies and also to allow the companies to give feedback. Tow us about one of the most important problems for them to be working on and potentially expose our students and give access to these companies to our students. >> I think the future will tell us, and that's hard to say right now, because way haven't done a lot of thinking, and I was interpreting and Big Data Way haven't reached our potential yet, and I just there's just so many things that we can't see right now. >> So one of the things that people tell us that are involved in big data is they have trouble finding the skill sets the data. Science can pick capability and capacity. And so seeing videos like this one of them, it is a new breed of students coming out there. They're growing up in this big data world, and that's critical to keep the big data pipeline flowing. And Jon, you and I have spent a lot of time in the East Coast looking at some of the big data cos it's almost a renaissance for Massachusetts in Cambridge and very exciting to see. Obviously, there's a lot going on the West Coast as well. Yeah, I mean, I'll say, I'm impressed with Emmett and around M I. T. In Cambridge is exploding with young, young new guns coming out of there. The new rock stars, if you will. But in California we're headquartered in Palo Alto. You know we in a chance that we go up close to Google Facebook and Jeff Hammer backer, who will show a video in a second that I interview with him and had dupe some. But he was the first guy a date at Facebook to build the data platform, which now has completely changed Facebook and made it what it is. He's also the co founder of Cloudera The Leader and Had Duke, which we've talked about, and he's the poster child, in my opinion of a data scientist. He's a math geek, but he understands the world problems. It's not just a tech thing. It's a bigger picture. I think that's key. I mean, he knows. He knows that you have to apply this stuff so and the passion that he has. This video from Jeff Hammer Bacher, cofounder of Cloud Ear, Watches Video. But and then the thing walk away is that big data is for everyone, and it's about having the passion. >> Wait. Wait. >> Palmer Bacher Data scientists from Cloudera Cofounder Hacking data Twitter handle Welcome to the Cube. >> Thank you. >> So you're known in the industry? I'LL see. Everyone knows you on Twitter. Young Cora heavily follow you there at Facebook. You built the data platform for Facebook. One of the guys mean guys. They're hacking the data over Facebook. Look what happened, right? I mean, the tsunami that Facebook has this amazing co founder Cloudera. You saw the vision on Rommedahl always quotes on the Cube. We've seen the future. No one knows it yet. That was a year and a half ago. Now everyone knows it. So do you feel about that? Is the co founder Cloudera forty million thousand? Funding validation again? More validation. How do you feel? >> Yeah, sure, it's exciting. I think of you as data volumes have grown and as the complexity of data that is collected, collected and analyzed as increase your novel software architectures have emerged on. I think what I'm most excited about is the fact that that software is open source and we're playing a key role in driving where that software is going. And, you know, I think what I'm most excited about. On top of that is the commodification of that software. You know, I'm tired of talking about the container in which you put your data. I think a lot of the creativity is happening in the data collection integration on preparation stage. Esso, I think. You know, there was ah tremendous focus over the past several decades on the modeling aspect of data way really increase the sophistication of our understanding, you know, classification and regression and optimization. And all off the hard court model and it gets done. And now we're seeing Okay, we've got these great tools to use at the end of the pipe. Eso Now, how do we get more data pushed through those those modeling algorithm? So there's a lot of innovative work. So we're thinking at the time how you make money at this or did you just say, Well, let's just go solve the problem and good things will happen. It was it was a lot more the ladder. You know, I didn't leave Facebook to start a company. I just left Facebook because I was ready to do something new. And I knew this was a huge movement and I felt that, you know, it was very gnashing and unfinished a software infrastructure. So when the opportunity Cloudera came along, I really jumped on it. And I've been absolutely blown away by the commercial success we've had s o. I didn't I certainly didn't set out with a master plan about how to extract value from this. My master plan has always been to really drive her duped into the background of enterprise infrastructure. I really wanted to be as obvious of a choice as Lennox and you See you, you're We've talked a lot at this conference and others about, you know, do moving from with fringe to the mainstream commercial enterprises. And all those guys are looking at night J. P. Morgan Chase. Today we're building competitive advantage. We're saving money, those guys, to have a master plan to make money. Does that change the dynamic of what you do on a day to day basis, or is that really exciting to you? Is an entrepreneur? Oh, yeah, for sure. It's exciting. And what we're trying to do is facilitate their master plan, right? Like we wanted way. Want to identify the commonalities and everyone's master plan and then commoditize it so they can avoid the undifferentiated heavy lifting that Jeff Bezos points out. You know where you know? No one should be required, Teo to invest tremendous amounts of money in their container anymore, right? They should really be identifying novel data sources, new algorithms to manipulate that data, the smartest people for using that data. And that's where they should be building their competitive advantage on. We really feel that, you know, we know where the market's going on. We're very confident, our product strategy. And I think over the next few years, you know, you guys are gonna be pretty excited about the stuff we're building, because I know that I'm personally very excited. And yet we're very excited about the competition because number one more people building open source software has never made me angry. >> Yeah, so So, you know, that's kind of market place. So, you know, we're talking about data science building and data science teams. So first tell us Gerald feeling today to science about that. What you're doing that, Todd here, around data science on your team and your goals. And what is a data scientist? I mean, this is not, You know, it's a D B A for her. Do you know what you know, sheriff? Sure. So what's going on? >> Yeah, So, you know, to kind of reflect on the genesis of the term. You know, when we were building out the data team at Facebook, we kind of two classes of analysts. We had data analysts who are more traditional business intelligence. You know, building can reports, performing data, retrieval, queries, doing, you know, lightweight analytics. And then we had research scientists who are often phds and things like sociology or economics or psychology. And they were doing much more of the deep dive, longitudinal, complex modeling exercises. And I really wanted to combine those two things I didn't want to have. Those two folks be separate in the same way that we combined engineering and operations on our date infrastructure group. So I literally just took data analyst and research scientists and put them together and called it data scientist s O. So that's kind of the the origin of the title on then how that's translating what we do at Clyde era. So I've recently hired to folks into a a burgeoning data science group Cloudera. So the way we see the market evolving is that you know the infrastructure is going to be commoditized. Yes, mindset >> to really be a data scientists, and you know what is way should be thinking about it. And there's no real manual. Most people aboard that math skills, economic kinds of disciplines you mentioned. What should someone prepared themselves? How did they? How does someone wanna hire data scientist had, I think form? Yeah, kinds of things. >> Well, I tend to, you know, I played a lot of sports growing up, and there's this phrase of being a gym rat, which is someone who's always in the gym just practicing. Whatever support is that they love. And I find that most data scientists or sort of data rats, they're always there, always going out for having any data. So you're there's a genuine curiosity about seeing what's happening and data that you really can't teach. But in terms of the skills that are required, I didn't really find anyone background to be perfect. Eso actually put together a course at University California, Berkeley, and taught it this spring called Introduction to Data Science, and I'm teaching and teaching it again this coming spring, and they're actually gonna put it into the core curriculum. Uh, in the fall of next year for computer science. >> Right, Jack Harmer. Bakar. Thanks so much for that insight. Great epic talk here on the Cube. Another another epic conversations share with the world Live. Congratulations on the funding. Another forty months. It's great validation. Been congratulations for essentially being part of data science and finding that whole movement Facebook. And and now, with Amaar Awadallah and the team that cloud there, you contend a great job. So congratulations present on all the competition keeping you keeping a fast capitalism, right? Right. Thank >> you. But it's >> okay. It's great, isn't it? That with all these great minds working in this industry, they still can't. We're so early in this that they still can't really define what a data scientist is. Well, what does talk about an industry and its infancy? That's what's so exciting. Everyone has a different definition of what it is, and that that what that means is is that it's everyone I think. Data science represents the new everybody. It could be a housewife. It could be a homemaker to on eighth grader. It doesn't matter if you see an insight and you see something that could be solved. Date is out there, and I think that's the future. And Jeff Hamel could talked about spending all this time and technology with undifferentiated heavy lifting. And I'm excited that we are moving beyond that into essentially the human part of Big Data. And it's going to have a huge impact, as we talked about before on the productivity of organizations and potentially productivity of lives. I mean, look at what we've talked about this this afternoon. We've talked about predicting volcanoes. We've talked about, you know, the medical issues. We've talked about pretty much every aspect of life, and I guess that's really the message of this industry now is that the folks who were managing big data are looking too change pretty much every aspect of life. This is the biggest inflexion point in history of technology that I've ever seen in the sense that it truly affects everything and the data that's generated in the data that machine's generate the data that humans generate, data that forest generate things like everything is generating data. So this's a time where we can actually instrument it. So this is why this massive disruption, this area and disruption We should say the uninitiated is a good thing in this business. Well, creation, entrepreneurship, copies of being found it It's got a great opportunity. Well, I appreciate your time, I unfortunately I think that's going to wrap it up for our big date. A deep dive. John and Dave the Cube guys have been great. I really appreciate you showing up here and, you know, just lending your insights and expertise and all that on DH. I want to thank you the audience for joining us. So you should stay tuned for the ongoing conversation on the Cube and to emcee TV to be informed, inspired and hopefully engaged. I'm Richard Schlessinger. Thank you very much for joining us.