>> Narrator: theCUBE's live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (bright music) >> Hey everyone! Welcome back. Good evening from Barcelona, Spain. It's theCUBE, the leader in live tech coverage. As you well know, Lisa Martin and Dave Nicholson. Day two of our coverage of MWC 23. Dave, we've been talking about sexy stuff all day. It's about to get, we're bringing sexy back. >> It's about to get hot. >> It's about to get hot. We've had two guests with us, two senior consultants from the product planning, networking and emerging server solutions group at Dell, Heather Raheel and James Bryan. Welcome guys. >> Thanks for having us. >> Thanks for having us. >> Really appreciate it. >> Lisa: Dude, you're bringing sexy back. >> I know. We are. We are. We wanted to bring it, yes. >> This is like XR8000 >> We've been talking about this all day. It's here... >> Yes. Yes. Talk to us about why this is so innovative. >> So, actually we wanted to bring this, getting a lot of attention here on site. Matter of fact, we even have a lot of our competition taking pictures of it. And why is it so innovative? So one of the things that we've done here is we've taken a lot of insights and feedback from our customers that are looking at 5G deployments and looking at how do they, basically, bring commercial off the shelf to a very proprietary industry. So what we've done is we've built a very flexible and scalable form factor in the XR8000. And so this is actually a product that we've purposely built for the telecommunications space. Specifically can be deployed for serving a virtual DU or DUC at a cell site for distributed ram. Or it can be put in a local data center, but outside a main data center to support centralized ram. We'll get into it, which is where the really excitement gets is it's sled-based in its design. And so because of that, it enables us to provide both functionality for telecommunications. Could be network, could be enterprise edge as well as being designed to be configured to whatever that workload is, and be cost-optimized for whatever that work. >> Ah, you're killing us! Let's see. Show, show it to us. >> Actually this is where I have to hand it off to my colleague Heather. But what I really want to show you here is the flexibility that we have and the scalability. So, right here what I'm going to show you first is a one U sled. So I'll set that out here, and I'll let Heather tell us all about it. >> Yeah. So XR8000. Let's talk about flexibility first. So the chassis is a two U chassis with a hot swap shared power supply on the right. Within it there are two form factors for the sleds. What James brought out here, this is the one U form factor. Each sled features one node or one CPU first sled. So we're calling the one U the highest, highest density sled right? Cause you can have up to four one node one U sleds in the chassis. The other form factor is a two U sled, on the right here. And that's just really building on top of the one U sled that adds two PCIe sleds on top. So this is really our general purpose sled. You could have up to two of these sleds within the chassis. So what's really cool about the flexibility is you can plug and play with these. So you could have two one Us, two two Us, or mix and match of each of those. >> Talk about the catalyst to build this for telco and some of the emerging trends that, that you guys have seen and said this needs to be purpose-built for the telco. There's so much challenge and complexity there, they need this. >> Want me to take this? So actually that, that's a great question by the way. It turns out that the market's growing. It's nascent right now. Different telecommunication providers have different needs. Their workloads are different. So they're looking for a form factor like this that, when we say flexible, they need to be able to configure it for theirs. They don't all configure the same way. And so they're looking for something that they can configure to their needs, but they also don't want to pay for things that they don't need. And so that's what led to the creation of, of this device the way we've created it. >> How is it specific for edge use cases, though? We think of the edge: it's emerging, it's burgeoning. What makes this so (pause) specific to edge use cases? >> Yeah, let's talk about some of the the ruggedized features of the product. So first of all, it is short depth. So only 430 millimeters. And this is designed for extreme temperatures, really for any environment. So the normal temperatures of operating are negative five to 55, but we've also developed an enhanced heat sink to get us even beyond that. >> Dave: That's Celsius? >> Celsius. Thank you. >> Lisa: Right. So this will get us all the way down to negative 20 boot in operating all the way up to 65 C. So this is one of the most extreme temperature edge offerings we've seen on the market so far. >> And so this is all outside the data center, so not your typical data center server. So not only are we getting those capabilities, but half the size when you look at a typical data center server. >> So these can go into a place where there's a rack, maybe, but definitely not, not doesn't have to be raised for... >> Could be a cell side cabinet. >> Yeah. Okay. >> Heather: Yeah. And we also have AC and DC power options that can be changed over time as well. >> So what can you pack into that one one U sled in terms of CPU cores and memory, just as an example? >> Yeah, great. So, each of the sleds will support the fourth generation of Intel Sapphire Rapids up to 32 corp. They'll also be supporting their new vRAN boost SKUs. And the benefit of those is it has an integrated FEC accelerator within the CPU. Traditionally, to get FEC acceleration, you would need a PCIe card that would take up one of the slots here. Now with it integrated, you're freeing up a PCIe slot, and there's also a power savings involved with that as well. >> So talk about the involvement of, of the telco customer here and then design, I know Dell is very tight with its customers. I imagine there was a lot of communications and collaboration with customers to, to deliver this. >> Interesting question. So it turns out that early on, we had had some initial insight, but it was actually through deep engagement with our customers that we actually redesigned the form factor to what you see here today. So we actually spent significant amount of time with various telecommunication customers from around the world, and they had a very strong influence in this form factor. Even to the point, like Lisa mentioned, we ended up redesigning it. >> Do, do you have a sense for how many of these, or in what kinds of configurations would you deploy in like the typical BBU? So if we're thinking about radio access network literally tran- tower transmitter receiver... somewhere down there (pause) in a cabinet, you have one of these, you have multiple units. I know, I know the answer is "it depends". >> You are right. >> But if, but if someone tells you, well you know, we have 20, 20 cellular sites, and we need (pause) we're we're moving to an open model, and we need the horsepower to do what we want to do. I'm trying to, I'm trying to gauge like what, one of these, what does that, what does that mean? Or is it more like four of these? >> So that, so we'll go >> It depends? >> Yeah it depends, you're absolutely right. However, we can go right there. So if you look in the two U >> Yeah. >> we have three PCIe slots, you know, as Heather mentioned. And so let's say you have a typical cell site, right? We could be able to support a cell site that could have it could have three radios in the configuration here, it could have a, multiply by three, right? It could have up to 18 radios, and we could actually support that. We could support multiple form factors or multiple deployments at a particular cell site. It really then to your point, it does depend, and that's one of the reasons that we've designed it the way we have. For example, if a customer says their initial deployment, they only need one compute node because maybe they're only going to have, you know, two or three carriers. So then, there, you've got maybe six or eight or nine radios. Well then, you put in a single node, but then they may want to scale over time. Well then, you actually have a chassis. They just come in, and they put in a new chassis. The other beauty of that is, is that maybe they wait, but then they want to do new technology. They don't even have to buy a whole new server. They can update to >> Heather: Yeah. the newest technology, same chassis put that in, connect to the radios, and keep going. >> But in this chassis, is it fair to say that most people will be shocked by how much traffic can go through something like this? In the sense that, if a tower is servicing 'n' number of conversations and data streams, going through something like this? I mean somehow blow, it blows my mind to think of thousands of people accessing something and having them all wrapped through something like this. >> It, it'll depend on what they're doing with that data. So you've probably talked a lot about a type of radios, right? Are we going to be massive MIMO or what type of radio? Is it going to be a mix of 4G or 5G? So it'll really depend on that type of radio, and then where this is located. Is it in a dense urban environment, or is it in a rural type of environment at that cell site shelter, but out in a suburban area. So will depend, but then, that's the beauty of this is then, (pause) I get the right CPU, I get the right number of adding cards to connect to the right radios. I purchase whatever, what I need. I may scale to that. I may be (pause) in a growing part of the city, like where we're from or where I'm from or in San Diego where Heather's from where she's in a new suburban, and they put out a new tower and the community grows rapidly. Well then, we may, they may put out one and then you may add another one and I can connect to more radios, more carriers. So it really just comes down to the type and what you're trying to put through that. It could edit a stadium where I may have a lot of people. I may have like, video streaming, and other things. Not only could I be a network connectivity, but I could do other functions like me, multi-axis axon point that you've heard about, talked about here. So I could have a GPU processing information on one side. I could do network on the other side. >> I do, I do. >> Go for it >> Yeah, no, no, I'm sorry. I'm sorry. I don't want to, don't want to hog all of the time. What about expansion beyond the chassis? Is there a scenario where you might load this chassis up with four of those nodes, but then because you need some type of external connectivity, you go to another chassis that has maybe some of these sleds? Or are these self-contained and independent of one another? >> They are all independent. >> Okay. >> So, and then we've done that for a reason. So one of the things that was clear from the customers, again and again and again, was cost, right? Total cost of ownership. So not only, how much does this cost when I buy it from you to what is it going to take to power and run it. And so basically we've designed that with that in mind. So we've separated the compute and isolated the compute from the chassis, from the power. So (pause) I can only deal with this. And the other thing is is it's, it's a sophisticated piece of equipment that people that would go out and service it are not used to. So they can just come out, pull it out without even bringing the system down. If they've got multiple nodes, pull it. They don't have to pull out a whole chassis or whole server. Put one in, connect it back up while the system is still running. If a power supply goes out, they can come and pull it out. We've got one, it's designed with a power infrastructure that if I lose one power supply, I'm not losing the whole system. So it's really that serviceability, total cost of ownership at the edge, which led us to do this as a configurable chassis. >> I was just going to ask you about TCO reduction but another thing that I'm curious about is: there seems to be like a sustainability angle here. Is that something that you guys talk with customers about in terms of reducing footprint and being able to pack more in with less reducing TCO, reducing storage, power consumption, that sort of thing? >> Go ahead. >> You want me to take that one as well? So yes, so it comes at me, varies by the customer, but it does come up and matter of fact one- in that vein, similar to this from a chassis perspective is, I don't, especially now with the technology changing so fast and and customers still trying to figure out well is this how we're really going to deploy it? You basically can configure, and so maybe that doesn't work. They reconfigure it, or, as I mentioned earlier, I purchased a single sled today, and I purchased a chassis. Well then the next generation comes. I don't have to purchase a new chassis. I don't have to purchase a new power supply. So we're trying to address those sustainability issues as we go, you know, again, back to the whole TCO. So they, they're kind of related to some extent. >> Right. Right, right. Definitely. We hear a lot from customers in every industry about ESG, and it's, and it's an important initiative. So Dell being able to, to help facilitate that for customers, I'm sure is part of what gives you that competitive advantage, but you talked about, James, that and, and we talked about it in an earlier segment that competitors are coming by, sniffing around your booth. What's going on? Talk about, from both of your lenses, the (pause) competitive advantage that you think this gives Dell in telco. Heather, we'll start with you. >> Heather: Yeah, I think the first one which we've really been hitting home with is the flexibility for scalability, right? This is really designed for any workload, from AI and inferencing on like a factory floor all the way to the cell site. I don't know another server that could say that. All in one box, right? And the second thing is, really, all of the TCO savings that will happen, you know, immediately at the point of sale and also throughout the life cycle of this product that is designed to have an extremely long lifetime compared to a traditional server. >> Yeah, I'll get a little geeky with you on that one. Heather mentioned that we'll be able to take this, eventually, to 65 C operating conditions. So we've even designed some of the thermal solutions enabling us to go there. We'll also help us become more power efficient. So, again, back to the flexibility even on how we cool it so it enables us to do that. >> So do, do you expect, you just mentioned maybe if I, if I heard you correctly, the idea that this might have a longer (pause) user-usable life than the average kind of refresh cycle we see in general IT. What? I mean, how often are they replacing equipment now in, kind of, legacy network environments? >> I believe the traditional life cycle of a of a server is, what? Three? Three to five years? Three to five years traditionally. And with the sled based design, like James said, we'll be designing new sleds, you know, every year two years that can just be plugged in, and swapped out. So the chassis is really designed to live much longer than, than just three to five years. >> James: We're having customers ask anywhere from seven to when it dies. So (pause) substantial increase in the life cycle as we move out because as you can, as you probably know, well, right? The further I get out on the edge, it, the more costly it is. >> Lisa: Yep. >> And, I don't want to change it if I don't have to. And so something has to justify me changing it. And so we're trying to build to support that both that longevity, but then with that longevity, things change. I mean, seven years is a long time in technology. >> Lisa: Yes it is. >> So we need to be there for those customers that are ready for that change, or something changed, and they want to still be able to, to adopt that without having to change a lot of their infrastructure. >> So customers are going to want to get their hands on this, obviously. We know, we, we can tell by your excitement. Is this GA now? Where is it GA, and where can folks go to learn more? >> Yeah, so we are here at Mobile World Congress in our booth. We've got a few featured here, and other booths throughout the venue. But if you're not here at Mobile World Congress, this will be launched live on the market at the end of May for Dell. >> Awesome. And what geographies? >> Worldwide. >> Worldwide. Get your hands on the XR8000. Worldwide in just a couple months. Guys, thank you >> James: Thank you very much. >> for the show and tell, talking to us about really why you're designing this for the telco edge, the importance there, what it's going to enable operators to achieve. We appreciate your time and your insights and your show and tell. >> Thanks! >> Thank you. >> For our guests and for Dave Nicholson, I'm Lisa Martin. You're watching theCUBE live, Spain in Mobile MWC 23. Be back with our sho- day two wrap with Dave Valente and some guests in just a minute. (bright music)

>>Hi, everyone. Welcome to the Cube's presentation of the AWS startup showcase. This is season two, episode four of our ongoing series, where we're talking with exciting partners in the AWS ecosystem. This topic on this episode is cybersecurity detect and protect against threats. I have two guests here with me today from hunters, please. Welcome. Laal Asher Doan, the CMO and Oprah. Geier the VP of product management. Thank you both so much for joining us today. >>Thank you for having us, Lisa, >>Our pleasure. Laal let's go ahead and start with you. Give the audience an overview of hunters. What does it do? When was it founded? What's the vision, all that good stuff. >>So hunters was founded in 20 18 2. Co-founders coming out of unit 8,200 in the Israeli defense force, the founders and people in engineering and R and D are mostly coming from both offensive cybersecurity, as well as defensive threat hunting, advanced operations, or, or being able to see in response to advanced attack and with the knowledge that they came with. They wanted to enable security teams in organizations, not just those that are coming from, you know, military background, but those that actually need to defend day in and day out against the growing cyber attacks that are growing in sophistication in the numbers of attacks. And we all know that every organization nowaday is being targeted, is it run somewhere more sophisticated attacks. So this thing has become a real challenge and we all know those challenges that the industry is facing with talent scarcity, with lack of the knowledge and expertise needing to address this. >>So came in with this mindset of, we wanna bring our expertise into the field, build it into a platform into a tool that will actually serve security teams in organizations around the world to defend against cyber attacks. So born and raised in Tel Aviv became a global company. Recently raised a serious CEO of funding funded by the world's rated VCs from stripes, wild benches, supported by snowflake data breaks and Microsoft M 12 also as strategic partners. And we now have broad variety of customers from all industries around the world, from tech to retail, to eCommerce, to banks that we work closely with. So very exciting times, and we are very excited to share today how we work with AWS customers to support the environments. >>Yeah, we're gonna unpack that. So really solid foundation, the company was built on only a few years ago. Laal was there, why a new approach was there a compelling event? Obviously we've seen dramatic changes in the threat landscape in recent years, ransomware becoming a, when it happens to us, not if, but any sort of compelling event that really led the founders to go, ah, this new approach. We gotta go this direction. >>Absolutely. We've seen a tremendous shift of organizations from cloud adoption to adoption of more security tools, both create a scenario, which the tool sets that are currently being used by security organizations. The security teams are not sufficient anymore. They cannot deal with the plethora of the variety of data. They cannot deal with the scale that is needed. And the security teams are really under a tremendous burden of tweaking tools that they have in their environment without too much of automation with a lot of manual work processes. So we've seen a lot of points where the current technology is not supporting the people and the processes that need to support security operations. And with that offer and his product team kind of set a vision of what a new platform should come to replace and enhance what teams are using these days. >>Excellent. Oprah, that's a perfect segue to bring you into the conversation. Talk about that vision and some of those really key challenges and problems that hunters are solving for organizations across any industry. >>Yeah. So as Lial mentioned, and it was very rightful, the problem with the, with the SIM space, that's the, the space that we're disrupting is the well known secret around is it's a broken space. There's a lot of competitors. There's a lot of vendors out there. It's one of the most mature, presumably mature markets in cybersecurity. But it seems like that every single customer and organization we talk to, they don't really like their existing solution. It doesn't really fit what they need. It's a very painful process and it's painful all across their workflow from the time they ingest the data. Everybody knows if you ever had a SIM solution or a soft platform, just getting the data into your environment can take the most amount of your time. The, the, the lion share of whatever your engineers are working on will go to getting the data into the system. >>And then, then keeping it there. It's this black hole that you have to keep feeding with more and more resources as you go along. It's an endless task with a lot of moving pieces, and it's very, very painful before you even get a single moment of value of security use case from your product. That's a big, painful piece. What you then see is once they set it up, their detection engineering is so far behind the curve because of all the different times of things they need to take care of. It used to be limited attack surface. We all know the attack surface here today is enormous. Especially when you talk about something like AWS, there's new services, new things, all the time, more accounts, more things. It keeps moving a lot and keeping track of that. And having someone that can actually look into a new threat when it's released, look into a new attack service, analyze it, deploying the detections in time, test and tweaked and all those things. >>Most organizations don't, don't even how to start approaching this problem. And, and, and that's a big pain for them. When they finally get to investigating something, they lack the context and the knowledge of how to investigate. They have very limited information coming to them and they go on this hunting chase of not hunting the attackers, but hunting the data, looking for the bits and pieces they're missing to complete the picture. It's like this bad boss that gives you very little instructions or, or guidelines. And then you need to kind of try to figure out what is it that they asked, right? That's the same thing with trying to do triaging with very minimal context. You look at the IP and then you try to figure out, you look at the hash, you look at all these different artifacts and you try to figure out yourself, you have very limited insights. And the worst is when you're under the gun, when there's a new emerging threat, that happens like a log for shell. And now you're under the gun and the entire company's looking at you and saying, are we impacted? What's going on? What should we doing? So from, from start to finish, it's a very painful process that impacts everybody in the security organization. A lot of, a lot of cumbersome work with a lot of frustration >>And it's comp companies in any industry over don't have time. You talked about some of the, the time involved here in the lag, and there isn't time in the very dynamic threat landscape that customers are living in. Let's all question for you is your primary target audience, existing SIM customers, cause over mentioned the disruption of the SIM market. I'm just wanting to understand in terms of who you're targeting, what does that look like? >>Definitely looking for customers that have a SIM and don't like, it don't find that it helps them improve the security posture. We also have organizations that are young emerging, have a lot of data, a lot of tech companies that have grown in the last 10, 15 years, or even five years, we have snowflake as a customer. They're booming. They have so much data that going the direction of traditional tools to aggregate the logs, cross correlate them doesn't make any sense with the scale that they need. They need the cloud based approach, SaaS approach that is capable of taking care of the environment. So we both cater to those organizations that we're shifting from on-prem to cloud and need visibility into those two environments and into those cloud natives wanted the cloud don't want to even think of a traditional SIM. >>You mentioned snowflake. We were just at snowflake summit a couple of months ago. I think that was and tremendous company that massive growth, massive growth in data across the board though. So I'm curious, Oprah, if we go back to you, we can dig into some of these data challenges. Obviously data volume and variety is only gonna continue to grow and proliferate and expand data in silos is still a problem. What are some of those main data challenges that hunters helps customers to just eliminate? >>Definitely. So the data challenge starts with getting the right data in the fact that you have so many different products across so many different environments, and you need to try to get them in a, in some location to try to use them for running your queries, your rules, your, your correlation. It's a big prompt. There's no unified standard for anyone. Even if there was, you have a lot of legacy things on premises, as well as your AWS environment, you need to combine all these. You can keep things only OnPrem you can own. Mostly a lot of most organizations are still in hybrid mode. They have they're shifting most of the things to AWS. You still have a lot of things OnPrem that they're gonna shift in the next 3, 4, 5 years. So that hybrid approach is definitely a problem for gathering the data. And when they gather the data, a lot of the times their existing solutions are very cross prohibitive and scale prohibitive from pushing all the data and essential location. >>So they have these data silos. They'll put some of it there. Some of it here, some of them different location, hot storage called storage, long term storage. They don't really, they end up not knowing really where the data is, especially when they need it. The most becomes a huge problem for them. Now with analytics, it's very hard to know upfront what data I'll need, not tomorrow, but maybe in three months to look back and query making these decisions very hard. Changing them later is even harder. Keeping track of all these moving pieces. You know, you have a device, you have some vendor sending you some logs. They changed their APIs. Who's in charge of, of fixing it. Who's in charge of changing your schema. You move from one EDR vendor to the other. How are you making sure that you keep the same level of protection? All these data challenges are very problematic for most customers. The most important thing is to be able to gather as much data as possible, putting in a centralized location and having good monitoring in a continuous flow of, I know what data I'm getting in. I know how much I'm using, and I'm making sure that it's working and flowing. It's going to a central life central place where I can use it at any time that I want. >>We've seen. So sorry. Yes, please. We wanted to add on that. We've seen too much compromise on data that because of prohibitive costs, structure of tools, or because of, in inability to manage the scale teams are compromising or making choices and that paying a price of the latency of being able to then go search. If an incident happened, if you are impacted by something, it all means money and time at the end of the day, when you actually need to answer yourself, am I breached or not? We wanna break out from this compromise. We think that data is something that should not be compromised. It's a commodity today. Everything should be retained, kept and used as appropriately without the team needing to ration what they're gonna use versus what they're not gonna use. >>Correct. That's >>A great point. Go ahead. >>Yeah. And we've seen customers either having entire teams dedicated to just doing this and, or leveraging products and companies that actually build a business around helping you filter the data that you need to put in different data silos, which to me is, is shows how much problem pain and how much this space is broken with what it provides with customers that you have these makeshift solutions to go around the problem instead of facing it head on and saying, okay, let's, let's build something that you're put all your data as much as you want, not have to compromise insecurity. >>You guys both bring up such a great point where data and security is concerned. No business can afford to compromise. Usually compromise is a good thing, but in that case, it's really not companies can't afford that. We know with the, with the threat landscape, the risk, all of the incentives for bad actors that companies need to ensure that they're doing the right things in Aly manner. LA I'm curious, you mentioned the target markets that you're going after. Where are the customer conversations? Is this C conversation from a datasecurity perspective? I would, this is more than the, the CSO. >>It's a CSO conversation, as well as we, we talk on a daily basis with those that lead security operations, head of socks. Those that actually see how the analyst are being overworked are tired, have so many false positives that they need to deal with noise day in, day out, becoming enslaved with the tools that they need to work on and, and tweak. So we have seen that the ones that are most enlightened by a solution like hunters are actually the ones that have to stop reporting to them. They know the daily pain and how much the process is broken. And this is probably one of we, we all talk about, you know, job satisfaction or dissatisfaction, the greatest, the great resignation people are living. This is the real problem in security. And the, so is one of these places that we see this alert, fatigue, people are struggling. It's a stressful work. And if there is anything that we can do to offload the work that is less appealing and have them work on what they sign up for, which is dealing with real threat, solving them, instead of dealing with false positives, this is where we can actually help. >>Can you add a little bit on that? Laal and you mentioned the cybersecurity skills gap, which is massive. We talk about that a lot because it's a huge problem. How is hunters a facilitator of companies that might be experiencing that? >>Absolutely. So we come with approach of, we call it the 80 20 of detection and response. Basically there are about 80% probably. Whoa, it's actually something like 95% of the threats are shared across all organizations in the world. Also 80 to 90% of the environments are similar. People are using similar tools. They're on similar cloud services. We think that everything that goes around detection of threats around those common attacks, scenarios in common attack landscape should come out of the box from a vendor like hunters. So we automate, we write the rules, we cross correlate. We provide those services out of the box. Once you sign to use our solution, your data flows in, and we basically do the processing and the analysis of all the data so that your team can actually focus on the 20% or the, you know, the 5% that are very unique to your organization. >>If you are developing a specific app and you have the knowledge of about the dev SecOps that needs to take place to defend it. Great. Have your team focus on that? If you are a specific actor in a specific space and specific threats that are unique to you, you build your own detections into our tool. But the whole idea that we have, the knowledge, we see attacks across industries and across industries, we have the researchers and the capabilities to be on top of those things. So your team doesn't need to do it on a daily basis because new attacks come almost on a daily basis. Now we read them in the news, we see them. So we do it. So your team doesn't have to, >>And nobody wants to be that next headline where a breach is concerned. I'll close this out here with outcomes. I noticed some big stats on your website. I always gravitate towards that. What are some of the key outcomes that hunters customers are achieving and then specifically AWS customers? >>Absolutely. Well, we already talked a lot about data and being able to ingest it. So we give our customers the predictability, the ability to ingest the data, knowing what the cost is going to be in a very simple cost model. So basically you can ingest everything that you have across all it tools that you have in your environment. And that helped companies reduce up to 75% of the data cost. We we've seen with large customer how much it change when they moved from traditional Sims to using hunters specifically, AWS customers can actually use the AWS credits to buy hunters. If they're interested, just go to AWS marketplace, search for hunters and come to a website. You can use your credits for that. I think we talked also about the security burden. The time spent on writing rules plus correlating incidents. We have seen sometimes a change in, instead of investigating an incident for two days, it is being cut for 20 minutes because we give them the exact story of the entire attack. What are the involved assets? What are the users that are involved, that they can just go see what's happening and then immediately go and remediate it. So big shift in meantime, to detect meantime, to respond. And I'm sure often has a more kind of insights that he's seen with some of our customers around that. >>Yeah. So, so some, some great examples recently there. So there's two things that I've, I've been chatting to customers about. One thing they really get a benefit of is we talked, you talked about the, the, the prong with talent and where that really matters the most is that under the gun mode, we have a service that is, we see it as, as the, the natural progression of the service that we provide called team axon. What team axon does for you is when you are under the gun, when something like log for shell happens, and everybody's looking at you, and time is ticking. Instead of trying to figure out on yourself, team axon will come in, figure out the, the threat will devise a report for all the customers, run queries on your behalf, on your data and give it to you. Within 24 hours, you'll have something to show your CEO or your executive team, your board, even this is where we got impacted or not impacted. >>This is what we did. Here's the mitigation thing. Step that we need to take from world class experts that you might not get access to for every single attack out there that really helps customers kind of feel like they they're, they're safe. There's someone there to help them. There's a big broader there. I call it sometimes the bad signal when we need the most. The other thing is on the day to day, a lot of a lot of solution will, will, will kind of talk about out of the box security. Now, the problem with out of the box security is keeping an up to date. That's what a lot of people miss. You have to think that you installed a year ago, but security doesn't stay put, you need to keep updating it. And you need to keep that updated pretty, pretty frequently to, to stay ahead of the curve. >>If you, if you're behind couple of months on your security updates, you know, what happens, same thing with your, your stock platform or your SIM rule base. What the reason that customers don't update is because if they usually do, then it might blow up the amount of alerts they're getting, cuz they need to tweak them with the approach that we take, that we tested on our customer's data transparently for them and make sure to release them without false positives. We're just allowing them to push the updates transparently directly to their account. They don't need to do anything. And one customer, one of our biggest accounts, they have dozens of subsidiaries and multiple songs. And, and one of the largest eCommerce companies in the world and the person running security. He said, if I had to do what hunters gives me out of the box myself, I have to hire 20 people and put them to work eight for 18 months for what you give me out of the box. So for me, it's a first, that's huge, kinda what we give customers and the kind of challenges that we're able to solve for them. >>Big challenges laal and over, thank you so much for joining us on the cube today. As part of this AWS startup showcase, talking about what hunters does, why the vision and the value in it for customers, we appreciate your time and your insights. Thank you so much for having us, my pleasure for my guests. I'm Lisa Martin. Thank you for watching this episode of the AWS startup showcase. We'll see us in.

(upbeat music) >> Hi, everyone. Welcome to theCUBE's presentation of the AWS Startup Showcase. This is season two, episode four of our ongoing series, where we're talking with exciting partners in the AWS ecosystem. This topic on this episode is cybersecurity. Detect and protect against threats. I have two guests here with me today from Hunters. Please welcome Lital Asher-Dotan, the CMO. And Ofer Gayer, the VP of product management. Thank you both so much for joining us today. >> Thank you for having us, Lisa. >> Our pleasure. Lital, let's go ahead and start with you. Give the audience an overview of Hunters. What does it do, when was it founded, what's the vision? All that good stuff. >> So Hunters was founded in 2018. Two co-founders coming out of Unit 8200 in the Israeli Defense Force. The founders and our people in engineering and R&D are mostly coming from both offensive cybersecurity as well as defensive threat hunting, advanced operations, or being able to see and response to advance attack. And with the knowledge that they came with, they wanted to enable security teams in organizations, not just those that are coming from, you know, military background but those that actually need to defend day in and day out against the growing cyber-attacks that are growing in sophistication, in the numbers of attacks. And we all know that every organization nowaday is being targeted, is it ransomware, more sophisticated attacks. So this thing has become a real challenge. And we all know those challenges that the industry is facing with talent scarcity, with lack of the knowledge and expertise needed to address this. So came in with this mindset of we want to bring our expertise into the field, build it into a platform, into a tool that will actually serve security teams in organizations around the world to defend against cyber attacks. So born and raised in Tel Aviv, became a global company. Recently raised a serious CO funding. Funded by the world's greatest VCs, from Stripes, Wild Ventures, supported by Snowflake data breaks and Microsoft M12, also as strategic partners. And we now have broad variety of customers from all industries around the world, from tech to retail to e-commerce to banks that we work closely with. So very exciting times. And we're very excited to share today how we work with AWS customers to support the environments. >> Yeah, we're going to unpack that. So really solid foundation the company was built on, only a few years ago. Lital was there, why a new approach? Was there a compelling event? Obviously, we've seen dramatic changes in the threat landscape in recent years. Ransomware becoming a, when it happens to us, not if. But any sort of compelling event that really led the founders to go, "Ah! This new approach, we got to go this direction." >> Absolutely. We've seen a tremendous shift of organizations from cloud adoption to adoption of more security tools. Both create a scenario which the toolsets that are currently being used by security organizations, the security teams are not efficient anymore. They cannot deal with the plethora of a variety of data. They cannot deal with the scale that is needed. And the security teams are really under a tremendous burden of tweaking tools that they have in their environment without too much of automation, with a lot of manual work processes. So we've seen a lot of points where the current technology is not supporting the people and the processes that need to support security operations. And with that, Ofer, and his product team kind of set a vision of what a new platform should come to replace and enhance what teams are using these days. >> Excellent. Ofer, that's a perfect segue to bring you into the conversation. Talk about that vision and some of those really key challenges and problems that Hunters is solving for organizations across any industry. >> Yeah. So as Lital mentioned, it was very rightful. The problem with the SIM space, that the space that we're disrupting is the well-known secret around is it's a broken space. There's a lot of competitors. There's a lot of vendors out there. It's one of the most mature, presumably mature markets in cybersecurity. But it seems like that every single customer and organization we talk to, they don't really like their existing solution. It doesn't really fit what they need. It's a very painful process and it's painful all across their workflow from the time they ingest the data. Everybody knows if you ever had a SIM solution or a SOC platform, just getting the data into your environment can take the most amount of your time, the lion's share of whatever your engineers are working on will go to getting the data into the system, and then keeping it there. It's this black hole that you have to keep feeding with more and more resources as you go along. It's an endless task with a lot of moving pieces, and it's very very painful before you even get a single moment of value of security use case from your product. That's a big, painful piece. What you then see is, once they set it up, their detection engineering is so far behind the curve because of all the different times of things they need to take care of. It used to be a limited attack surface. We all know the attack surface here today is enormous, especially when you talk about something like AWS, there's new services, new things all the time, more accounts, more things. It keeps moving a lot, and keeping track of that and having someone that can actually look into a new threat when it's released, look into a new attack surface, analyze it, deploying the detections in time, test and tweak, and all those things. Most organizations don't even how to start approaching this problem, and that's a big pain for them. When they finally get to investigating something, there lacks the context and the knowledge of how to investigate. They have very limited information coming to them and they go on this hunting chase of not hunting the attackers but hunting the data, looking for the bits and pieces they're missing to complete the picture. It's like this bad boss that gives you very little instructions or guidelines, and then you need to kind of try to figure out what is it that they asked, right? That's the same thing with trying to do triaging with very minimal context. You look at the IP and then you try to figure out, you look at the Hash, you look at all these different artifacts and you try to figure out yourself. You have very limited insights. And the worst is when you're under the gun, when there's a new emerging threat that happens like a Log4Shell, and now you're under the gun and the entire company's looking at you and saying, "Are we impacted? What's going on? What should we doing?" So from start to finish, it's a very painful process that impacts everybody in the security organization. A lot of cumbersome work with a lot of frustration. >> And it's companies in any industry, Ofer, don't have time. You talked about some of the time involved here in the lag. And there isn't time in the very dynamic threat landscape that customers are living in. Lital, question for you, is your primary target audience existing SIM customers? 'Cause Ofer mentioned the disruption of the SIM market. I'm just wanting to understand in terms of who you're targeting, what does that look like? >> Definitely looking for customers that have a SIM and don't like it, don't find that it helps them improve the security posture. We also have organizations that are young, emerging, have a lot of data, a lot of tech companies that have grown in the last 10, 15 years, or even five years. With Snowflake as a customer, they're booming. They have so much data that going the direction of traditional tools to aggregate the logs, cross-correlate them doesn't make any sense with the scale that they need. They need the cloud-based approach, SaaS approach that is capable of taking care of the environment. So we both cater to those organizations that we're shifting from on-prem to cloud and need visibility into those two environments and into those cloud natives. Born to the cloud don't want to even think of a traditional SIM. >> You mentioned Snowflake. We were just at Snowflake Summit a couple of months ago, I think that was. And tremendous company that massive growth, massive growth in data across the board though. So I'm curious, Ofer, if we go back to you, if we can dig into some of these data challenges. Obviously, data volume and variety, it's only going to continue to grow and proliferate and expand. Data in silos is still a problem. What are some of those main data challenges that Hunters helps customers to just eliminate? >> Definitely. So the data challenge starts with getting the right data in. The fact that you have so many different products across so many different environments and you need to try to get them in some location to try to use them for running your queries, your rules, your correlation. It's a big prompt. There's no unified standard for anyone, even if there was, you would have a lot of legacy things on-premises, as well as your AWS environment. You need to combine all these. You can keep things only on-prem. You can own... Mostly a lot of, most organizations are still in hybrid mode. They have, they're shifting most of their things to AWS. You still have a lot of things on-prem that they're going to shift in the next 3, 4, 5 years. So that hybrid approach is definitely a problem for gathering the data. And when they gather the data, a lot of the times their existing solutions are very cost prohibitive and scale prohibitive from pushing all the data in essential location. So they have these data silos. They'll put some of it there, some of it here, some of that in a different location, hot storage, cold storage, long-term storage. They don't really, they end up not knowing really where the data is especially when they need it the most becomes a huge problem for them. Now with analytics, it's very hard to know upfront what data I'll need not tomorrow, but maybe in three months to look back and query. Making these decisions is very hard. Changing them later is even harder. Keeping track of all these moving pieces. You know, you have a device, you have some vendor sending you some logs, they changed their APIs. Who's in charge of fixing it? Who's in charge of changing your schema? You move from one EDR vendor to the other. How are you making sure that you keep the same level of protection? All these data challenges are very problematic for most customers. The most important thing is to be able to gather as much data as possible, putting it in a centralized location, and having good monitoring in a continuous flow of, I know what data I'm getting in. I know how much I'm using, and I'm making sure that it's working and flowing. It's going to a central place where I can use it at any time that I want. >> We've seen, if I can add- >> So, Lital- >> Sorry. >> Yes, please. >> You wanted to add on that? We've seen too much compromise on data that because of prohibitive costs, structure of tools, or because of inability to manage the scale, teams are compromising or making choices and are paying a price of the latency of being able to then go search if an incident happened, that if you are impacted by something. It all means money and time at the end of the day when you actually need to answer yourself, am I breached or not? We want to break out from this compromise. We think that data is something that should not be compromised. It's a commodity today. Everything should be retained, kept, and used as appropriately without the team needing to ration what they're going to use versus what they're not going to use. >> Correct (faintly speaking). >> That's a great point. >> Go ahead. >> Yeah. And we've seen customers either having entire teams dedicated to just doing this and, or leveraging products and companies that actually build a business around helping you filter the data that you need to put in different data silos, which to me is, shows how much problem, pain, and how much this space is broken with what it provides with customers that you have these makeshift solutions to go around the problem instead of facing it head on and saying, "Okay, let's build something that you're put all your data as much as you want, not have to compromise on security." >> You both bring up such a great point where data and security is concerned. No business can afford to compromise. Usually compromise is a good thing, but in that case, it's really not. Companies can't afford that. We know with the threat landscape, the risk, all of the incentives for bad actors that companies need to ensure that they're doing the right things in a timely manner. Lital, I'm curious, you mentioned the target markets that you're going after. Where were customer conversations? Is this a C-suite conversation from a data security perspective? I would this is more than the CISO. >> It's a CISO conversation, as well as we talk on a daily basis with those that lead security operations, head of SOCs. Those that actually see how the analyst are being overworked, are tired, have so many false positives that they need to deal with, noise day in, day out, becoming enslaved with the tools that they need to work on and tweak. So we have seen that the ones that are most enlightened by a solution like Hunters are actually the ones that have the SOC reporting to them. They know the daily pain and how much the process is broken. And this is probably one of the... We all talk about, you know, job satisfaction or dissatisfaction, the greatest, the great resignation, people are living. This is the real problem in security. And the SOC is one of these places that we see this alert, fatigue, people are struggling. It's a stressful work. And if there is anything that we can do to offload the work that is less appealing and have them work on what they sign up for, which is dealing with real threat, solving them, instead of dealing with false positives. This is where we can actually help. >> Can you add a little bit on that, Lital? And you mentioned the cybersecurity skills gap, which is massive. We talked about that a lot because it's a huge problem. How is Hunters a facilitator of companies that might be experiencing that? >> Absolutely. So we come with approach of, we call it the 80/20 of detection and response. Basically, there are about 80%, probably more, it's actually something like 95% of the threats are shared across all organizations in the world. Also, 80 to 90% of the environments are similar. People are using similar tools. They're on similar cloud services. We think that everything that goes around detection of threats, around those common attacks, scenarios in common attack landscape should come out of the box from the vendor like Hunters. So we automate, we write the rules, we cross-correlate. We provide those services out of the box once you sign in to use our solution. Your data flows in and we basically do the processing and the analysis of all the data, so that your team can actually focus on the 20%, or the 15, or the 5% that are very unique to your organization. If you are developing a specific app and you have the knowledge about the DevSecOps that needs to take place to defend it. Great, have your team focus on that. If you are a specific actor in a specific space and specific threats that are unique to you, you build your own detections into our tool. But the whole idea that we have the knowledge, we see attacks across industries and across industries we have the researchers and the capabilities to be on top of those things, so your team doesn't need to do it on a daily basis because new attacks come almost on a daily basis. Now, we read them in the news, we see them. So we do it, so your team doesn't have to. >> And nobody wants to be that next headline where a breach is concerned. Lital, close this out here with outcomes. I noticed some big stats on your website. I always gravitate towards that. What are some of the key outcomes that Hunters customers are achieving and then specifically AWS customers? >> Absolutely. Well, we already talked a lot about data and being able to ingest it. So we give our customers the predictability, the ability to ingest the data knowing what the cost is going to be in a very simple cost model. So basically you can ingest everything that you have across all IT tools that you have in your environment. And that helped companies reduce up to 75% of the data cost. We've seen with large customer, how much it change when they moved from traditional SIMs to using Hunters. Specifically, AWS customers can actually use the AWS Credits to buy Hunters if they're interested. Just go to AWS Marketplace, search for Hunters and come to a website, you can use your credits for that. I think we talked also about the security burden, the time spent on writing rules plus correlating incidents. We have seen sometimes a change in, instead of investigating an incident for two days, it is being cut for 20 minutes because we give them the exact story of the entire attack. What are the involved assets? What are the users that are involved, that they can just go see what's happening and then immediately go and remediate it. So big shift in meantime to detect meantime to respond. And I'm sure Ofer has a more kind of insights that he's seen with some of our customers around that. >> Yeah. So some great examples recently there. So there's two things that I've been chatting to customers about. One thing they really get a benefit of is we talked about the problem with talent. And where that really matters the most is that under the gun mode, we have a service that is, we see it as the natural progression of the service that we provide called Team Axon. What Team Axon does for you is when you're under the gun, when something like Log4Shell happens and everybody's looking at you, and time is ticking, instead of trying to figure out on yourself, Team Axon will come in, figure out the threat, will devise a report for all the customers, run queries on your behalf on your data, and give it to you within 24 hours. You'll have something to show your CEO or your executive team, your board even, this is where we got impacted or not impacted. This is what we did. Here's the mitigation thing, step that we need to take from world-class experts that you might not get access to for every single attack out there. That really helps customers kind of feel like they're safe. There's someone there to help them. There's a big brother there. I call it sometimes the Bat-Signal when we need it the most. The other thing is on the day-to-day, a lot of solution, we'll kind of talk about out-of-the-box security. Now, the problem with out-of-the-box security is keeping it up to date, that's what a lot of people miss. You have to think that you installed a year ago, but security doesn't stay put, you need to keep updating it. And you need to keep the updated pretty pretty frequently to stay ahead of the curve. If you're behind couple of months on your security updates, you know what happens. Same thing with your SOC platform on your SIM rule base. The reason that customers don't update is because if they usually do, then it might blow up the amount of alerts they're getting 'cause they need to tweak them. With the approach that we take that we tested on our customer's data transparently for them, and make sure to release them without false positives. We're just allowing them to push the updates transparently directly to their account. They don't need to do anything. And one customer, one of our biggest accounts, they have dozens of subsidiaries and multiple SOCs and one of the largest e-commerce companies in the world. And the person running security, he said, "If I had to do what Hunters gives me out of the box myself, I have to hire 20 people and put them to work for 18 months for what you give me out of the box." So for me, it's a very- >> That's huge. >> What we give customers and the kind of challenges that we're able to solve for them. >> Big challenges. Lital and Ofer, thank you so much for joining us on theCUBE today as part of this AWS Startup Showcase, talking about what Hunters does, why the vision and the value in it for customers. We appreciate your time and your insights. >> Thank you so much. >> For having us. >> My pleasure. For my guests, I'm Lisa Martin. Thank you for watching this episode of the AWS Startup Showcase. We'll see you soon. (cheerful music)

>>Hey everyone. Welcome back to the cube. Live in Las Vegas, Lisa Martin, with Dave Nicholson, we are covering AWS reinvent 2021. This was probably one of the most important and largest hybrid tech events this year with AWS and its enormous ecosystem of partners. We're going to be talking with a hundred guests in the next couple of days. We started a couple of days ago and about really the innovation that's going to be going on in the cloud and tech in the next decade. We're pleased to welcome Rick Tam Daniel's as our next guest VP of strategic ecosystems at Informatica. Rick. Welcome to >>The program. Thank you for having me. It's a, it's a pleasure to be back. >>Isn't it nice to be back in person? Oh, it's amazing. All these conversations you just can't replicate by video conferencing. Absolutely >>Great to reconnect with folks haven't seen in a few years as well. >>Absolutely. That's been the sentiment. I think one of the, one of the sentiments that we've heard the last three days, so one of the things thematically that we've also been hearing about in, in between all of the plethora of AWS announcements, typical reinvent is that every company has to become a data company, public sector, private sector, small business, large business. Talk to us about how Informatica and AWS are helping companies become data companies so that they don't get left behind. >>But one of the biggest things that we're hearing at reinvent is that customers are really concerned with data, fragmentation, data silos, access to trusted data, and how do they, how do they get that information to really affect data led transformation? In fact, we did a survey earlier in the year of chief, the chief data officers were found that up to 80, almost 80% of organizations had 50% or more of their data in hybrid or multi-cloud environments. And also a 79% are looking to leverage more than 100 data sources. And 30% are looking to leverage more than 1000 data sources. So Informatica we, with our intelligent data management cloud, we're really focused on enabling customers to bring together the data assets, no matter where they live, what format they're in, on-premise cloud, multi-cloud bringing that all together. >>Well, we sold this massive scatter 22 months ago now, right? Of everyone just, and the edge exploded and data exploded and volumes and data sources exploded hard for organizations to get their head around that, to go or that the data is going to be living in all these different places. You talked about a lot of customers and every industry being hybrid multi-cloud because based on strategy, based on acquisition, but to get their arms around that data and to be able to actually extract value from it fast is going to be the difference between those businesses that succeed and those that don't >>Absolutely. And our partnership with AWS, that's a long standing partnership and we're very much focused on addressing the challenges you're talking about. Uh, and in fact, earlier this year we announced our cloud first, our cloud native, uh, data governance and data catalog on AWS, which is really focused on creating that central point of trusted data access and visibility for the organization. And just today, we had an announcement about how we're bringing data democratization and really accelerating data democratization for AWS lake formation. >>What is, when you, when you, we talk about data democratization often, what does that mean to you? What does that mean to Informatica? How do you deliver that to customers so that they can really be able to extract as much value as they can? >>Yeah. So a great question. And really that whole data management journey is a big piece of this. So it starts with data discovery. How do I even begin to find my data assets? How do I get them from where they are to where they need to go in the cloud? How do I make sure they're clean, they're ready to use. I trust them. I understand where they came from. And so the solution that we announced today is really focused on how do we provide a business users with a self-service way of getting access to data lake data, sitting in Amazon S3 with lake formation governance, but doing it in a way that doesn't create an undue burden on those business users, around data compliance and data policies. And so what we've done is we brought our business user-friendly self-service experience an axon data marketplace together with AWS lake formation. >>So Informatica has had a long history in the data world. Um, I think of terms like MDM and ETL. Yes. Where does, where does Informatica is history dovetail with the present day in terms of cloud the con does the concept of extract translate load? I think that's what ETL stood for too many TLAs running as far as trying to transform, uh, w where does that play in today's world? Are you focused separately on cloud from on-premise data center or do you, or do you link the two? Yeah, >>So we focus on, uh, addressing data management, uh, when, no matter where the data lives. So on-premise cloud multi-cloud, uh, on our intelligent data management cloud platform is a, is the industry's first end-to-end cloud native as a service data management platform that delivers all those capabilities. I mentioned before, uh, to customers. So we can manage all those workloads that are distributed from a single cloud-based as a service data management platform. So >>The platform is, is as a service in the cloud, but you could be managing data assets that are in traditional on premises, data centers, the like, absolutely. >>Okay. >>So congratulations on the IPO. Of course we can't, we can't not talk to Informatica without that. I imagined the momentum is probably pretty great right about now when we think of AWS, I, when I think of AWS, I always think of momentum. We, I mean the, the volume of announcements, but also when I think about AWS, I think about their absolute focus on the customer, that working backwards approach from a partnership perspective. Is there alignment there? I imagine, like I said, with the IPO, a lot of momentum right now, probably a lot of excitement are, is infant medical also was focused and customer obsessed as AWS's. >>Yeah. So, um, first of all, thank you so much. Congratulations. Uh, so we had a very successful IPO last month. And in fact, just yesterday, our CEO I'm at Wailea presented our Q3 results, uh, which showcase the continued growth of our subscription revenue or cloud revenue. And in fact, our cloud revenue grew 44% year over year, which is really reflective of our big shift to being a cloud first company and also the success of our intelligent data management cloud platform. Right. And, and that platform, again, as I mentioned, it's spanning all those aspects of data management and we're delivering that for more than 5,000 customers globally. Uh, and just from an adoption perspective, we processed about 23 trillion transactions a month for customers in our cloud platform. And that's doubling every six to 12 months. So it's incredible amount of adoption. Some of the biggest enterprises in the world like Unilever, Sanofi folks like that are using the cloud is their preferred data management platform of choice in the cloud. >>Well, you know, of course, congratulations is in order for the IPO, but also really on what you just mentioned, the trajectory of where Informatica is going, because Informatica wasn't born yesterday. Right. And, uh, we shouldn't overlook the fact that there are challenges associated with moving from the world as it exists on premises for still 80% of it spend at least navigating that transition, going from private to public, getting the right kind of investment where people realize that cloud is a significant barrier to entry, uh, for, for a lot of companies. I think it's, it's, you know, you have a lot of folks cheering for you as you navigate this transition. >>Well, one thing I do I say is, yes, we have it in the business of data for a long time, but we also then the business of cloud quite a long time. So this is true. This is the 10th reinvent. This is also the ten-year anniversary of the Informatica AWS partnership, right? So we've been working in the cloud with AWS for, for that long innovating all of these different, different core services. So, um, and from that perspective, you know, I think we're doing a tremendous amount of innovation together, you know, solutions like when we talked about for lake formation, but we also announced today a couple of key programs that we partnered with AWS around, around modernization and migration, right? So that's a big area of focus as well is how do we help customers modernize and take advantage of all the great services that AWS offers? So that's how we announced our membership and what's called the workload migration program and also the data lead migrations program, which is part of the public sector focus at AWS as well. >>The station perspective that was talked a lot about by Adam yesterday. And we've talked about it a lot today, every organization needs to monitorize, even some of those younger ones that you think, oh, aren't, they already, you know, fairly modern, but where, where are your customer conversations happening from a modernization perspective is that elevated up the, the C stat that we've got to modernize our or our organization get better handle of our data, be able to use it more protected, secure it so that we can be competitive and deliver outstanding customer experiences. >>What happens is the pain points that the legacy infrastructure has from the business perspective really do elevate the conversation to the C-suite. They're looking at saying, Hey, especially with the pandemic, right? We have to transform our business. We have to have data. We have to have trust in data. How do we do that? And we're not going to get there >>On rigid on-premise infrastructure. We need to be in a cloud native footprint. And so we've been focused on helping customers get to those cloud native end points, but also to a truly cloud native data management, we talked about earlier can manage all those different workloads, right? From a single that SAS serverless type experience. Right? What have been some of the interesting conversations that you've had here? Again, we are in person yep. Fresh off the IPO, lots of announcements coming out. You guys made announcements today. What's been the sentiment from the, those customers and partners that you've talked about. >>Well, I'll give you guys actually a little sneak preview of another announcement we have coming tomorrow, uh, with our friends at Databricks. So we, uh, we are announcing a data, data democratization solution with Databricks accelerating some of the same, you know, addressing some of the same challenges we were talking about here, but in the data breaks in the Lakehouse environment. Um, so, so, but around that, and I had a great conversation with some partners here, some of the global system integrators, and they're just so happy to see that, right, because a lot of the infrastructure that's around data lakes are lake formation. It's pretty technical it's for a technical audience. And, and Informatica has really been focused on how do we expand the base of users that are able to tap into data and that's through no code experiences, right? It's through visual experiences. And we bring that tightly coupled together with the performance and the power and scale of platforms like Databricks and the AWS Redshift and S3, it's really transformative for customers. >>What are some of the things that here we are wrapping up the 10th, re-invent almost as tomorrow, but also wrapping up the end of 2021. What are some of the things that th th that there's obviously a lot of momentum with Informatica right now that from a partnership perspective, anything that you, you just gave us some breaking news. Thank you. We always love that. What are some of the things that you're looking forward to in 2022 that you think are really going to help Informatica customers just be incredibly competitive and utilizing data in the cloud on prem to their maximum? >>Well, I think as we go into the next year data complexity data fragmentation, it's gonna continue to grow. It's, it's, it's exploding out there. Uh, and one of the key components of our platform or the IDMC platform is we call it Clare, which is the industry first kind of metadata driven AI engine. And what we've done is we've taken the intelligence of machine learning and AI, and brought that to the business of data management. And we truly believe that the way customers are going to tame that data, they're going to address those problems and continue to scale and keep up is leveraging the power of AI in a cloud native cloud, first data management platform. >>Excellent. Rick, thank you so much for joining us today. Again, congratulations on last month, Informatica IPO, great solid, strong, deep partnership with AWS. We thank you for your insights and best of luck next year. >>Awesome. Thank you so much. Pleasure being here. Our >>Pleasure to have you for my co-host David Nicholson, I'm Martin. You're watching the cube, the global leader in live tech coverage.

>> Announcer: From around the globe, it's "theCUBE" with digital coverage of AWS "re:Invent" 2020. Sponsored by Intel, AWS and our community partners. >> Hi, everyone, welcome back to theCUBE's virtual coverage of AWS "re:Invent" virtual 2020. It's not an in-person event this year. It's remote, it's virtual, "theCUBE" is virtual and our guests and our interviewers will be remote as well. And so we're here covering the event for the next three weeks, throughout the next three cause we're weaving in commentary from "theCUBE", check out the cube.net and all of our coverage. And here at AWS we have special feature programming, we got a great segment here talking about big data in the cloud, governance, data lakes, all that good stuff. Rik Tamm-Daniels, vice-president strategic ecosystems and technology for Informatica, and Rick Turnock, head of enterprise data services, Invesco, customer of Informatica. Welcome to the cube. >> Hey John, thanks for having us. >> So Rik, with a K from Informatica, I want to ask you first, we've been covering the company journey for many, many years. Always been impressed with the focus on data and specifically cloud and all the things that you guys have been announcing over the years, have been spot on the mark. You know, AI with CLAIRE, you know, making things, cloud native, all that's kind of playing out now with the pandemic, "re:Invent", that's the story here. Building blocks with high level services, cloud native, but data is the critical piece again. More machine learning, more AI, more data management. What's your take on this year's "re:Invent". >> Absolutely John and again, we're always excited to be here at "re:Invent", we've been here since the very first one. You know, it's a deep talk to a couple of key trends there, especially the era of the global pandemic here. There's so many challenges that so many enterprises are experiencing. I think the big surprise has been, that has actually translated into a tremendous amount of demand for digital transformation, and cloud modernization in particular. So we've seen a huge uptake in our cloud relationships with AWS when it comes to transformational architecture solutions around data and analytics, and using data as a fundamental asset for digital transformation. And so some of those solution areas are things like data warehouse, modernization of the cloud, or end-to-end data governance. That's a huge topic as well for many enterprises today. >> Before coming into "re:Invent", I had a chance to sit down an exclusive interview with Andy Jassy. I just spoke with Matt Garman who's now heading up sales and marketing, who ran EC too. Rick, you're a customer of Informatica. Their big talking point to me and validation to the trends is, there's no excuse to go slow anymore because there's a reason to go fast cause there's consequences and the pandemic has highlighted that you got to move faster otherwise, you know, you're going to be on the wrong side of history and necessity is the mother of all invention. Okay, great. I buy that by the way. So I have no complaints on talking point there from Amazon Web Services. The problem is, you got to manage the data. (John chuckles) To go fast. The gas in the tank is data, and if it's screwed up, it's not going to go well, all right? So it's like putting gas in a car. So, this is where I see the data lake coming into the cloud and all the benefits and look at the successes of companies. The cloud is a real enabler. What's your take on this? The importance of data governance, because cloud scale is here, people want to go faster, data is like the key thing. >> Yeah. The data governance was a critical component when we started our enterprise data platform and looking at, you know, how can we build a modern-day architecture with scale, bringing our enterprise data, but doing it in a governed fashion. So, when we did it, we kind of looked at, you know, what are critical partners? How can we apply data governance and the full catalog capabilities of knowing what data's coming in, identifying it, and then really controlling the quality of it to meet the needs of the organization. It was a critical component for us because typically it's been difficult to get access to that right data. And as we look in the future and even current needs, we really need to understand our data and bring the right data in and make it easily accessible and governance, and quality of that is a critical component of it. >> I want to just follow up with that if you don't mind cause you know, I've done so many of these interviews, I've been on the block now 30 years in the industry, I've seen the waves come and go, and you see a lot of these mandates, you know, "Data governance, we're adding data governance." From the Ivory tower, or you hear, "Everything got to be a service." But when you peel back and look under the hood to make that happen, it's complicated. You've got to have put things in place and it's got to be set up properly, you got to do your work. How important it is to have... And well what's under the covers to this? Cause governance, yeah, it's a talking point, I get that. But to make it actually happen well, it's hard. >> We started really with the operating models from the start. So I kind of took over data governance seven years ago and had a governing global architecture that's been around for 40 years, and it was hard. So this was really our shot and time to get it right. So we did an operating model, a governance model, and it really ingrained it through the whole build and execution process. And so it was part with technology and it was foundational to the process to really deliver it. So it wasn't governance from a governance saying, it was really part of our operating model and process to build this out and really succeed at it. >> Rik, on the Informatica side, I got to get your take on the new solution you guys announced, "The Governed Data Lake", I think it was solution. Does this tie into that? Take a minute to explain the announcement, and how does this tie in? >> Yeah, absolutely John. So I think you take a step back, look at... We talked about some of the drivers of why companies are investing in cloud data lakes. And I think what comes down to is, when you think about that core foundation of data analytics, you know, they're really looking at, you know, how do we go ahead and create a tremendous leap forward in terms of their ability to leverage data as an asset. And again, as we talked about, one of the biggest challenges is trust around the data. And what the solution does though, is it really looks to say, "Okay, first and foremost, "let's create that foundation of trust "not just for the cloud data lake, "but for the entire enterprise. "To ensure that when we start to build this "new architecture, one, we understand the data assets "that are coming in at the very get-go." Right? It's much harder to add data governance after the fact, but you put it in upfront, you understand your existing data landscape. And once that data is there, you make sure you understand the quality of the information, you cleanse the data, you also make sure you put it under the right data management policies. So many policies that enterprises are subject to now like CCPA and GDPR. They have to be concerned about consumer privacy and being able as part of your governance foundational layer, to make sure that you're in compliance as data moves through your new architectures. It's fundamental having that end trust and confidence to be able to use that data downstream. So our solution looks to do that end-to-end across a cloud environment, and again, not just the cloud environment, but the full enterprise as well. One thing I do want to touch on if you don't mind is on the AI side of things and the tooling side of things. Because I think data governance has been around a while, as you said, it's not that it's a new concept. But how do you do it efficiently in today's world? >> John: Yeah. >> And this is where Informatica is focused on a concept of data 4.0. Which is the use of metadata and AI and machine learning and intelligence, to make this process much, much more efficient. >> Yeah that's a good point, Rik, from these two Rickes, I got to go, one's with a K, one with a C, and CK. So Rick, CK and from Invesco customer, I want to just check that with you because I was your customer of Informatica, by they brought up a good point about governance. And I saw this movie before, we've all seen this before, people just slap on solutions or tooling to a pre-existing architecture. You see that with security, you know, now it's, you can't have a conversation without saying, "Oh security's got to be baked in from the beginning." Okay cool, I get that. There's no debate there. Governance, same kind of thing, you know, you're hearing this over and over again, if you don't bake governance into the beginning of everything, you're going to be screwed. Okay? So how important is that foundation of trust for this peace. (Rick mumbling) >> It's critical and to do it at beginning, right? So you're profiling the data, you're defining entitlements and who has access to it, you're defining data quality rules that you can validate that, you define the policies, is there a PII data, all of that, as you do that from the start, then you have a well-governed and documented data catalog and taxonomy that has the policies and the controls in place to allow that to use. If you do it after the fact, then you're always going to be catching up. So a part of our process and policies and where the really Informatica tools delivered for us is to make it part of that process. And to use that as we continue to build out our data platform with the quality controls and all the governance processes built in. >> I got to ask on your journey, that's seven years ago, you took over the practice. You were probably right in the middle of the sea change when everyone kind of woke up and said, "Hey, you know, Amazon, you go back seven years, "look at Amazon where they were to where they are today." Okay? Significantly strong then, total bellwether now in terms of value opportunity. So, how did you look at the cloud migration? How do you think about the cloud architecture? Because I'm sure, and I'd love to get your story here about how you thought about cloud, in the midst of architecting the data foundational platform there. >> Yeah, we're a global company that had architecture, we grew it by acquisition. So a lot of our data architecture was on-prem, difficult really to pull that enterprise data together to meet the business needs. So when we started this, we really wanted to leverage cloud technology. We wanted a modern stack. We wanted scale, flexibility, agility, security, all the things that the cloud brought us too. So we did a search, and looking at that, and looked at competitors, but really landed on to Amazon just bought by core capabilities and scale they have innovation and just the services to bring a lot what we're looking at and really deliver on what we wanted from a platform. >> Why Informatica and AWS, why the combination? Can you share some of the reasons why you went with Informatica with AWS? >> Yeah, again, when we started this off, we looked at the competitors, right? And we were using IVQ. So we had an Informatica product on-prem, but we looked at a lot of the different governance competitors, and really the integrated platform that Informatica brings to us, what was the key deliverer, right? So we can really have the technical metadata with EDC and enterprise data client, catalog, scan our sources, our file, understanding the data and lineage of what it is. And we can tie that into axon and the governance tools to really define business costs returns. We were very critical of defining all our key data elements business glossary, and then we can see where that is by linking that to the technical metadata. So we know where our PII data, where are all our data and how it flows, both tactically and from a business process. And then the IDQ. So when we've defined and understand the data, we want to bring in the delight and how we want to conform it, to make it easily accessible, we can define data quality rules within the governance tool, and then execute that with IDQ, and really have a well-defined data quality process that really takes it from governance in theory to governance in really execution. >> That's awesome. Hey, you are using the data, you're using the cloud, you're getting everything you need out of it. That's the whole idea, isn't it? >> Yeah. >> That's good stuff, Rik at Informatica, tell us about what's going on, you mentioned data 4.0, I think people should pay attention to some of the interviews I've done with your team. They're online also, it's part of that next-gen, next level thinking. Here at "re:Invent", what should customers pay attention to, that you guys are doing? Great customer example here of cloud scale. What's the story for "re:Invent" this year for Informatica. >> But what John, it comes down to when customers think about their cloud journey, right? And the difference, especially with their data centric workloads and priorities and initiatives, all the different hurdles that they need to overcome. I think Informatica we're uniquely positioned to help customers address all those different challenges and you heard Rick speak about a whole bunch of those along the way. And I think particularly at "re:Invent", first of all, I just welcome folks to... They want to learn more about our data governance solution. Please come by our virtual booth. We also have a great interactive experience that encouraged folks to check out. One of the key components of our solution is our enterprise data catalog. And attendees at "re:Invent" can actually get hands on with our data catalog through the demo jam, the AWS demo jam as part of "re:invent". So I'd encourage folks to check that out as well, just to see what we're talking about yet actually. >> Awesome. Final question for you guys, as "re:Invent" is going on, a lot app stores are popping up, you seeing obviously the same trends, machine learning and you know, outpost is booming, so a cloud operations is clearly here, Rick from Invesco, what do you think the most important story is for your peers as they're here? It's a learning conference and you guys have seven years in the cloud working together with Informatica, in your opinion, what should people be paying attention to as they looked at this pandemic and what they got to get through? And then coming out of it with the growth strategy, it's all got to be more about the data, there's more data coming in, more sources, IoT data, certainly the work at home is causing these workloads, workplace, workflows, everything's changed, the future of work. What's your advice to peers out there on what to pay attention to and what to think about? >> We really started with a top-down strategy, right? To really the vision and the future. What do we want to get out of our data? Data is just data, right? But it's the information, it's the analytics, it's really delivering value for our clients, shareholders, and employees to really do their job, simplify our architecture. So really defining that vision of what you want and approach, and then executing on it, right? So how do you build it in a way to make it flexible and scalable, and how do you build an operating and governance model really to deliver on it because, you know, garbage in is garbage out, and you really got to have those processes, I think to really get the full value of what you're building. >> Get the data out there at the right place, at the right time and the right quality data. That's a lot more involved now and you need to be agile. And I think agile data is a way to go. Rick Turnock... >> And then with channels and capabilities that makes it easier, right? It makes it doable. And I think that's what cloud and the Informatica tools, right? Where in the past, you know, it was people hard coding and doing it right? The capability of that cloud and these tools give us makes it really achievable. >> You know, we have an old saying here in our CUBE team, you know, "If there's a problem, "you got to see if it's important, "and then look at the consequences "of not solving that problem, quantify the value of "solving or not solving that problem, "and then look and deploy solutions to do it." I think now with the data, you can actually do that and say, "This ain't quite the consequences of not doing this "or doing this, have a quantifiable value." I just loved that because it brings the whole ROI back to the table. And, you know, it's a dark art, it used to be, you mentioned the old days, you know, you got to do all this custom work, it was like a dark art. Oh yeah, the ROI calculation, payback. I mean, it was a moving train. That's the way it used to be. Not anymore. >> You got to do it to survive, really, if you're not doing it, you know, I don't know. >> Necessity is the mother of all inventions I think, now more than ever, data's going to be the key. Rik final word from Informatica. What should people pay attention to? >> Yeah, I mean, I think as you mentioned there, data is obviously a critical asset, right? And, and to your point with cloud, you can not only realize ROI quickly, but, you can actually iterate so much more quickly, where you can get that ROI immediately or you can validate that ROI, you can adjust your approach. But again, from an Informatica standpoint, we are seeing such a huge uptake in demand for customers who want to go to the cloud, who are modernizing. Every day we're investing heavily and how do we make sure that customers can get there quickly? They can maximize the ROI from their data assets, and we're doing it with all things, data management, from traditional data integration, all the way to the data governance, all the capabilities we talked about today. >> Yeah. Congratulations. That's the benefit of investing in a platform and having a set of out of the box tooling with SaaS, platform as a service, really it can enable success. And I think the pandemic is pretty obvious who's taking advantage of it, so congratulations and continued success. Thanks for coming on. Appreciate it. Rick Turnock, head of data service, enterprise data services at Invesco, customer of Informatica sharing his insight. Great insight there. Necessity is the mother of all inventions, baking it in from the beginning data governance foundational, it's not a bolt on, that's the message. I'm John Furrier with theCUBE. Thanks for watching. (soft music)

>> From theCUBE studios in Palo Alto in Boston, connecting with thought leaders all around the world, this a CUBE conversation. >> Hello, and welcome to this CUBE conversation, I'm John Furrier, host of theCUBE here, in our Palo Alto, California studios, here with our quarantine crew. We're getting all the remote interviews during this time of COVID-19. We've got two great remote guests here, Rachini Moosavi who's the Executive Director of Analytical Services and Data Governance at UNC Healthcare, and Sonya Jordan, Enterprise Analytics Manager of Data Governance at UNC Health. Welcome to theCUBE, thanks for coming on. >> Thank you. >> Thanks for having us. >> So, I'm super excited. University of North Carolina, my daughter will be a freshman this year, and she is coming, so hopefully she won't have to visit UNC Health, but looking forward to having more visits down there, it's a great place. So, thanks for coming on, really appreciate it. Okay, so the conversation today is going to be about how data and how analytics are helping solve problems, and ultimately, in your case, serve the community, and this is a super important conversation. So, before we get started, talk about UNC Health, what's going on there, how you guys organize, how big is it, what are some of the challenges that you have? >> SO UNC Health is comprised of about 12 different entities within our hospital system. We have physician groups as well as hospitals, and we serve, we're spread throughout all of North Carolina, and so we serve the patients of North Carolina, and that is our primary focus and responsibility for our mission. As part of the offices Sonya and I are in, we are in the Enterprise Analytics and Data Sciences Office that serves all of those entities and so we are centrally located in the triangle area of North Carolina, which is pretty central to the state, and we serve all of our entities equally from our Analytics and Data Governance needs. >> John: You guys got a different customer base, obviously you've got the clinical support, and you got the business applications, you got to be agile, that's what it's all about today, you don't need to rely on IT support. How do you guys do that? What's the framework? How do you guys tackle that problem of being agile, having the data be available, and you got two different customers, you got all the compliance issues with clinical, I can only imagine all the regulations involved, and you've got the business applications. How do you handle those? >> Yeah, so for us in the roles that we are in, we are fully responsible for more of the data and analytics needs of the organization, and so we provide services that truly are balanced across our clinician group, so we have physicians, and nurses, and all of the other ancillary clinical staff that we support, as well as the operational needs as well, so revenue cycle, finance, pharmacy, any of those groups that are required in order to run a healthcare system. So, we balance our time amongst all of those and for the work that we take on and how we continuously support them is really based on governance at the end of the day. How we make decisions around what the priorities are and what needs to happen next, and requires the best insights, is really how we focus on what work we do next. As for the applications that we build, in our office, we truly only build analytical applications or products like visualizations within Tableau as well as we support data governance platforms and services and so we provide some of the tools that enable our end users to be able to interact with the information that we're providing around analytics and insights, at the end of the day. >> Sonya, what's your job? Your title is Analytics Manager of Data Governance, obviously that sounds broad but governance is obviously required in all things. What is your job, what is your day-to-day roles like? What's your focus? >> Well, my day-to-day operations is first around building a data governance program. I try to work with identifying customers who we can start partnering with so that we can start getting documentation and utilizing a lot of the programs that we currently have, such as certification, so when we talk about initiatives, this is one of the initiatives that we use to partner with our stakeholders in order to start bringing visibilities to the various assets, such as metrics, or universes that we want to certify, or dashboards, algorithm, just various lists of different types of assets that we certify that we like to partner with the customers in order for them to start documenting within the tools, so that we can bring visibility to what's available, really focusing on data literacy, helping people to understand what assets are available, not only what assets are available, but who owns them, and who own the asset, and what can they do with it, making sure that we have great documentation in order to be able to leverage literacy as well. >> So, I can only imagine with how much volume you guys are dealing from a data standpoint, and the diversity, that the data warehouse must be massive, or it must be architected in a way that it can be agile because the needs, of the diverse needs. Can you guys share your thoughts on how you guys look on the data warehouse challenge and opportunity, and what you guys are currently doing? >> Well, so- >> Yeah you go ahead, Rachini. >> Go ahead, Sonya. >> Well, last year we implemented a tool, an enterprise warehouse, basically behind a tool that we implemented, and that was an opportunity for Data Governance to really lay some foundation and really bring visibility to the work that we could provide for the enterprise. We were able to embed into probably about six or seven of the 13 initiatives, I was actually within that project, and with that we were able to develop our stewardship committee, our data governance council, and because Rachini managed Data Solutions, our data solution manager was able to really help with the architect and integration of the tools. >> Rachini, your thoughts on running the data warehouse, because you've got to have flexibility for new types of data sources. How do you look at that? >> So, as Sonya just mentioned, we upgraded our data warehouse platform just recently because of these evolving needs, and like a lot of healthcare providers out there, a lot of them are either one or the other EMRs that are top in the market. With our EMR, they provide their own data warehouse, so you have to factor almost the impact of what they bring to the table in with an addition to all of those other sources of data that you're trying to co-mingle and bring together into the same data warehouse, and so for us, it was time for us to evolve our data warehouse. We ended up deciding on trying to create a virtual data warehouse, and in doing so, with virtualization, we had to upgrade our platform, which is what created that opportunity that Sonya was mentioning. And by moving to this new platform we are now able to bring all of that into one space and it's enabled us to think about how does the community of analysts interact with the data? How do we make that available to them in a secure way? In a way that they can take advantage of reusable master data files that could be our source of truth within our data warehouse, while also being able to have the flexibility to build what they need in their own functional spaces so that they can get the wealth of information that they need out of the same source and it's available to everyone. >> Okay, so I got to ask the question, and I was trying to get the good stuff out first, but let's get at the reality of COVID-19. You got pre-COVID-19 pandemic, we're kind of in the middle of it, and people are looking at strategies to come out of it, obviously the world will be changed, higher with a lot of virtualization, virtual meetings, and virtual workforce, but the data still needs to be, the business still needs to run, but data will be changing different sources, how are you guys responding to that crisis because you're going to be leaned on heavily for more and more support? >> Yeah it's been non-stop since March (laughs). So, I'm going to tell you about the reporting aspects of it, and then I'd love to turn it over to Sonya to tell you about some of the great things that we've actually been able to do to it and enhance our data governance program by not wasting this terrible event and this opportunity that's come up. So, with COVID, when it kicked off back in March, we actually formed a war room to address the needs around reporting analytics and just insights that our executives needed, and so in doing so, we created within the first week, our first weekend actually, our first dashboard, and within the next two weeks we had about eight or nine other dashboards that were available. And we continuously add to that. Information is so critical to our executives, to our clinicians, to be able to know how to address the evolving needs of COVID-19 and how we need to respond. We literally, and I'm not even exaggerating, at this very moment we have probably, let's see, I think it's seven different forecasts that we're trying to build all at the same time to try and help us prepare for this new recovery, this sort of ramp up efforts, so to your point, it started off as we're shutting down so that we can flatten the curve, but now as we try to also reopen at the same time while we're still meeting the needs of our COVID patients, there's this balancing act that we're trying to keep up with and so analytics is playing a critical factor in doing that. >> Sonya, your thoughts. First of all, congratulations, and action is what defines the players from the pretenders in my mind, you're seeing that play out, so congratulations for taking great action, I know you're working hard. Sonya, your thoughts, COVID, it's putting a lot of pressure? It highlights the weaknesses and strengths of what's kind of out there, what's your thoughts? >> Well, it just requires a great deal of collaboration and making sure that you're documenting metrics in a way where you're factoring true definition because at the end of the day, this information can go into a dashboard that's going to be visualized across the organization, I think what COVID has done was really enhanced the need and the understanding of why data governance is important and also it has allowed us to create a lot of standardization, where we we're standardizing a lot of processes that we currently had in correct place but just enhancing them. >> You know, not to go on a tangent, but I will, it's funny how the reality has kind of pulled back, exposed a lot of things, whether it's the remote work situation, people are VPNing, not under provision with the IT side. On the data side, everyone now understands the quality of the data. I mean, I got my kids talking progression analysis, "Oh, the curves are all wrong," I mean people are now seeing the science behind the data and they're looking at graphs all the time, you guys are in the visualization piece, this really highlights the need of data as a story, because there's an impact, and two, quality data. And if you don't have the data, the story isn't being told and then misinformation comes out of it, and this is actually playing out in real time, so it's not like it's just a use case for the most analytics but this again highlights the value of proposition of what you guys do. What's your personal thoughts on all this because this really is playing out globally. >> Yeah, it's been amazing how much information is out there. So, we have been extremely blessed at times but also burdened at times by that amount of information. So, there's the data that's going through our healthcare system that we're trying to manage and wrangle and do that data storytelling so that people can drive those insights to very effective decisions. But there's also all of this external data that we're trying to be able to leverage as well. And this is where the whole sharing of information can sometimes become really hard to try and get ahead of, we leverage the Johns Hopkins data for some time, but even that, too, can have some hiccups in terms of what's available. We try to use our State Department of Health and Human Services data and they just about updated their website and how information was being shared every other week and it was making it impossible for us to ingest that into our dashboards that we were providing, and so there's really great opportunities but also risks in some of the information that we're pulling. >> Sonya, what's your thoughts? I was just having a conversation this morning with the Chief of Analytics and Insight from NOA which is the National Oceanic Administration, about weather data and forecasting weather, and they've got this community model where they're trying to get the edges to kind of come in, this teases out a template. You guys have multiple locations. As you get more democratized in the connection points, whether it's third-party data, having a system managing that is hard, and again, this is a new trend that's emerging, this community connection points, where I think you guys might also might be a template, and your multiple locations, what's your general thoughts on that because the data's coming in, it's now connected in, whether it's first-party to the healthcare system or third-party. >> Yeah, well we have been leveraging our data governance tool to try to get that centralized location, making sure that we obtain the documentations. Due to COVID, everything is moving very fast, so it requires us to really sit down and capture the information and when you don't have enough resources in order to do that, it's easy to miss some very important information, so really trying to encourage people to understand the reason why we have data governance tools in order for them to leverage, in order to capture the documentation in a way that it can tell the story about the data, but most of all, to be able to capture it in a way so that if that person happened to leave the organization, we're not spending a lot of time trying to figure out how was this information created, how was this dashboard designed, where are the requirements, where are the specifications, where are the key elements, where does that information live, and making sure we capture that up front. >> So, guys, you guys are using Informatica, how are they helping you? Obviously, they have a system they're getting some great feedback on, how are you using Informatica, how is it going, and how has that enabled you guys to be successful? >> Yeah, so we decided on Informatica after doing a really thorough vetting of all of the other vendors in the industry that could provide us these services. We've really loved the capabilities that we've been able to provide to our customers at this point. It's evolving, I think, for us, the ability to partner with a group like Prominence, to be able to really leverage the capabilities of Informatica and then be really super, super hyper focused on providing data literacy back to our end users and making that the full intent of what we're doing within data governance has really enabled us to take the tools and make it something that's specific to UNC Health and the needs that our end users are verbalizing and provide that to them in a very positive way. >> Sonya, they talk about this master catalog, and I've talked to the CEO of Informatica and all their leaders, governance is a big part of it, and I've always said, I've always kind of had a hard time, I'm an entrepreneur, I like to innovate, move fast, break things, which is kind of not the way you work in the data world, you don't want to be breaking anything, so how do you balance governance and compliance with innovation? This has been a key topic and I know that you guys are using their enterprise data catolog. Is that helping? How does that fit in, is that part of it? >> Well, yeah, so during our COVID initiatives and building these telos dashboards, these visualizations and forecast models for executive leaders, we were able to document and EMPower you, which we rebranded Axon to EMPower, we were able to document a lot of our dashboards, which is a data set, and pretty much document attributes and show lineage from EMPower to EDC, so that users would know exactly when they start looking at the visualization not only what does this information mean, but they're also able to see what other sources that that information impacts as well as the data lineage, where did the information come from in EDC. >> So I got to ask the question to kind of wrap things up, has Informatica helped you guys out now that you're in this crisis? Obviously you've implemented before, now that you're in the middle of it, have you seen any things that jumped out at you that's been helpful, and are there areas that need to be worked on so that you guys continue to fight the good fight, come out of this thing stronger than before you came in? >> Yeah, there is a lot of new information, what we consider as "aha" moments that we've been learning about, and how EMPower, yes there's definitely a learning curve because we implemented EDC and EMPower last year doing our warehouse implementation, and so there's a lot of work that still needs to be done, but based on where we were the first of the year, I can say we have evolved tremendously due to a lot of the pandemic issues that arised, and we're looking to really evolve even greater, and pilot across the entire organization so that they can start leveraging these tools for their needs. >> Rachini you got any thoughts on your end on what's worked, what you see improvements coming, anything to share? >> Yeah, so we're excited about some of the new capabilities like the marketplace for example that's available in Axon, we're looking forward to being able to take advantage of some of these great new aspects of the tool so that we can really focus more on providing those insights back to our end users. I think for us, during COVID, it's really been about how do we take advantage of the immediate needs that are surfacing. How do we build all of these dashboards in record-breaking time but also make sure that folks understand exactly what's being represented within those dashboards, and so being able to provide that through our Informatica tools and service it back to our end users, almost in a seamless way like it's built into our dashboards, has been a really critical factor for us, and feeling like we can provide that level of transparency, and so I think that's where as we evolve that we would look for more opportunities, too. How do we make it simple for people to get that immediate answers to their questions, of what does the information need without it feeling like they're going elsewhere for the information. >> Rachini, thank you so much for your insight, Sonya as well, thanks for the insight, and stay safe. Sonya, behind you, I was pointing out, that's your artwork, you painted that picture. >> Yes. >> Looks beautiful. >> Yes, I did. >> You got two jobs, you're an artist, and you're doing data governance. >> Yes, I am, and I enjoy painting, that's how I relax (laughs). >> Looks great, get that on the market soon, get that on the marketplace, let's get that going. Appreciate the time, thank you so much for the insights, and stay safe and again, congratulations on the hard work you're doing, I know there's still a lot more to do, thanks for your time, appreciate it. >> Thank you. >> Thank you. >> It's theCUBE conversation, I'm John Furrier at the Palo Alto studios, for the remote interviews with Informatica, I'm John Furrier, thanks for watching. (upbeat music)

(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 2019. I'm your host Rebecca Knight along with my co-host John Furrier. We are joined by Adam Mariano, he is the Vice-President Health Informatics at HighPoint Solutions. Thanks for coming on theCUBE! >> Thank you for having me. >> So tell our viewers a little bit about HighPoint Solutions, what the company does and what you do there. >> Sure, HighPoint is a consulting firm in the Healthcare and Life Sciences spaces. If it's data and it moves we probably can assist with it. We do a lot of data management, we implement the full Infomatica stack. We've been an Infomatica partner for about 13 years, we were their North American partner of the year last year. We're part of a much larger organization, IQVIA, which is a merger of IMS quintiles, large data asset holder, big clinical research organization. So we're very much steeped in the healthcare data space. >> And what do you do there as Vice President of Health and Formatics? >> I'm in an interesting role. Last year I was on the road 51 weeks. So I was at over a hundred facilities, I go out and help our customers or prospective customers or just people we've met in the space, get strategic about how they're going to leverage data as a corporate asset, figure out how they're going to use it for clinical insight, how they're going to use it for operational support in payer spaces. And really think about how they're going to execute on their next strategy for big data, cloud strategy, digital re-imaginment of the health care space and the like. >> So we know that healthcare is one of the industries that has always had so much data, similar to financial services. How are the organizations that you're working with, how are they beginning to wrap their brains around this explosion of data? >> Well it's been an interesting two years, the last augur two years there isn't a single conversation that hasn't started with governance. And so it's been an interesting space for us. We're a big MDM proponent, we're a big quality proponent, and you're seeing folks come back to basics again, which is I need data quality, I need data management from a metadata perspective, I need to really get engaged from a master data management perspective, and they're really looking for integrated metadata and governance process. Healthcare's been late to the game for about five or six years behind other industries. I think now that everybody's sort of gone through meaningful use and digital transformation on some level, we're now arcing towards consumerism. Which really requires a big deep-dive in the data. >> Adam, data governance has been discussed at length in the industry, certainly recently everyone knows GDPR's one year anniversary, et cetera, et cetera. But the role of data is really critical applications for SAS and new kinds of use cases, and the term Data Provisioning as a service has been kicked around. So I'd love to get your take on what that means, what is the definition, what does it mean? Data Provisioning as a service. >> The industry's changed. We've sort of gone through that boomerang, alright, we started deep in the sort of client server, standard warehouse space. Everything was already BMS. We then, everybody moved to appliances, then everybody came back and decided Hadoop, which is now 15 year old technology, was the way to go. Now everybody's drifting to Cloud, and you're trying to figure out how am I going to provision data to all these self-service users who are now in the sort of bring your own tools space. I'd like to use Tablo, I'd like to use Click. I like SAS. People want to write code to build their own data science. How can you provision to all those people, and do so through a standard fashion with the same metadata with the same process? and there isn't a way to do that without some automation at this point. It's really just something you can't scale, without having an integrated data flow. >> And what's the benefits of data provisioning as a service? What's the impact of that, what does it enable? >> So the biggest impact is time to market. So if you think about warehousing projects, historically a six month, year-long project, I can now bring data to people in three weeks. In two days, in a couple of hours. So thinking about how I do ingestion, if you think about the Informatica stack, something like EDC using enterprise data catalog to automatically ingest data, pushing that out into IDQ for quality. Proving that along to AXON for data governance and process and then looking at enterprise data lake for actual self-service provisioning. Allowing users to go in and look at their own data assets like a store, pick things off the shelf, combine them, and then publish them to their favorite tools. That premise is going to have to show up everywhere. It's going to have to show up on AWS, and on Amazon, and on Azure. It's going to have to show up on Google, it's going to have to show up regardless of what tool you're using. And if you're going to scale data science in a real meaningful way without having to stack a bunch of people doing data munging, this is the way it's going to have to go. >> Now you are a former nurse, and you now-- >> I'm still a nurse, technically. >> You're still a nurse! >> Once a nurse, always a nurse. Don't upset the nurses. >> I've got an ear thing going on, can you help me out here? (laughter) >> So you have this really unique vantage point, in the sense that you are helping these organizations do a better job with their data, and you also have a deep understanding of what it's like to be the medical personnel on the other side, who has to really implement these changes, and these changes will really change how they get their jobs done. How would you say, how does that change the way you think about what you do? And then also what would you say are the biggest differences for the nurses that are on the floor today, in the hospital serving patients? >> I think, in America we think about healthcare we often talked about Doctors, we only talk about nurses in nursing shortages. Nurses deliver all the care. Physicians see at this point, the way that medicine is running, physicians see patients an average two to four minutes. You really think about what that translates to if you're not doing a surgery on somebody, it's enough time to talk to them about their problem, look at their chart and leave. And so nursing care is the point of care, we have a lot of opportunity to create deflection and how care is delivered. I can change quality outcomes, I can change safety problems, I can change length of stay, by impacting how long people keep IVs in after they're no longer being used. And so understanding the way nursing care is delivered, and the lack of transparency that exists with EMR systems, and analytics, there's an opportunity for us to really create an open space for nursing quality. So we're talking a lot now to chief nursing officers, who are never a target of analytics discussion. They don't necessarily have the budget to do a lot of these things, but they're the people who have the biggest point of control and change in the way care is delivered in a hospital system. >> Care is also driven by notifications and data. >> Absolutely. >> So you can't go in a hospital without hearing all kinds of beeps and things. In AI and all the things we've been hearing there's now so many signals, the question is what they pay attention to? >> Exactly. >> This becomes a really interesting thing, because you can get notifications, if everything's instrumented, this is where kind of machine learning, and understanding workflows, outcomes play a big part. This is the theme of the show. It's not just the data and coding, it's what are you looking for? What's the problem statement or what's the outcome or scenario where you want the right notification, at the right time or a resource, is the operating room open? Maybe get someone in. These kinds of new dynamics are enabled by data, what's your take on all this? >> I think you've got some interesting things going on, there's a lot of signal to noise ratio in healthcare. Everybody is trying to build an algorithm for something. Whether that's who's going to overstay their visit, who's going to be readmitted, what's the risk for somebody developing sepsis? Who's likely to follow up on a pharmacy refill for their medication? We're getting into the space where you're going to have to start to accept correlation as opposed to causation, right? We don't have time to wait around for a six month study, or a three year study where you employ 15,000 patients. I've got three years of history, I've got a current census for the last year. I want to figure out, when do I have the biggest risk for falls in a hospital unit? Low staffing, early in their career physicians and nurses? High use of psychotropic meds? There are things that, if you've been in the space, you can pretty much figure out which should go into the algorithm. And then being pragmatic about what data hospitals can actually bring in to use as part of that process. >> So what you're getting at is really domain expertise is just as valuable as coding and wrangling data, and engineering data. >> In healthcare if you don't have SMEs you're not going to get anything practical done. And so we take a lot of these solutions, as one of the interesting touch points of our organization, I think it's where we shine, is bringing that subject matter expertise into a space where pure technology is not going to get it done. It's great if you know how to do MDM. But if you don't know how to do MDM in healthcare, you're going to miss all the critical use cases. So it really - being able to engage that user base, and the SMEs and bring people like nurses to the forefront of the conversation around analytics and how data will be used to your point, which signals to pay attention to. It's critical. >> Supply chains, another big one. >> Yeah. >> Impact there? >> Well it's the new domain in MDM. It's the one that was ignored for a long time. I think people had a hard time seeing the value. It's funny I spoke at 10 o'clock today, about supply chain, that was the session that I had with Nathan Rayne from BJC. We've been helping them embark on their supply chain journey. And from all the studies you look at it's one of the easiest places to find ROI with MBM. There's an unbelievable amount of ways- >> Low hanging fruit. >> $24.5 billion in waste a year in supply chain. It's just astronomical. And it's really easy things, it's about just in time supplies, am I overstocking, am I losing critical supplies for tissue samples, that cost sometimes a $100,000, because a room has been delayed. And therefore that tissue sits out, it ends up expiring, it has to be thrown away. I'll bring up Nathan's name again, but he speaks to a use case that we talked about, which is they needed a supply at a hospital within the system, 30 miles away another hospital had that supply. The supply costs $40,000. You can only buy them in packs of six. The hospital that needed the supply was unaware that one existed in the system, they ordered a new pack of six. So you have a $240,000 price that you could have resolved with a $100 Uber ride, right? And so the reality is that supply could have been shipped, could have been used, but because that wasn't automated and because there was no awareness you couldn't leverage that. Those use cases abound. You can get into the length of stay, you can get into quality of safety, there's a lot of great places to create wins with supply chain in the MDM space. >> One of the conversations we're having a lot in theCUBE, and we're having here at Informatica World, it centers around the skills gap. And you have a interesting perspective on this, because you are also a civil rights attorney who is helping underserved people with their H1B visas. Can you talk a little bit about the visa situation, and what you're seeing particularly as it relates to the skills gap? >> We're in an odd time. We'll leave it at that. I won't make a lot of commentary. >> Yes. >> I'm a civil rights and immigration attorney, and on the immigration side I do a lot of pro bono work with primarily communities of color, but communities at risk looking to help adjust their immigration status. And what you've had is a lot of fear. And so you have, well you might have an H1B holder here, you may have somebody who's on a provisional visa, or family members, and because those family members can no longer come over, people are going home. And you're getting people who are now returning. So we're seeing a negative immigration of places like Mexico, you're seeing a lot of people take their money, and their learnings and go back to India and start companies there and work remotely. So we're seeing a big up-tick in people who are looking for staffing again. I think the last quarter or so has been a pretty big ramp-up. And I think there's going to continue to be this hole, we're going to have to find new sources of talent if we can't bring people in to do the jobs. We're still also, I think it just speaks to our STEM education the fact that we're not teaching kids. I have a 28 year old daughter who loves technology, but I can tell you, her education when she was a kid, was lacking in this technology space. I think it's really an opportunity for us to think about how do we train young people to be in the new data economy. There's certainly an opportunity there today. >> And what about the, I mean you said you were talking about your daughter's education. What would you have directed her toward? What kinds of, when you look ahead to the jobs of the future, particularly having had various careers yourself, what would you say the kids today should be studying? >> That's two questions. So my daughter, I told her do what makes you happy. But I also made her learn Sequel. >> Be happy, but learn Sequel. >> But learn sequel. >> Okay! >> And for kids today I would say look, if you have an affinity and you think you enjoy the computer space, so you think about coding, you like HTML, you like social media. There are a plethora of jobs in that space and none of them require you to be an architect. You can be a BA, you can be a quality assurance person, you can be a PM. You can do analysis work. You can do data design, you can do interface design, there's a lot of space in there. I think we often reject kids who don't go to college, or don't have that opportunity. I think there's an opportunity for us to reach down into urban centers and really think about how we make alternate pathways for kids to get into the space. I think all the academies out there, you're seeing rise, Udemy, and a of of these other places that are offering academy based programs that are three, six months long and they're placing all of their students into jobs. So I don't think that the arc that we've always chased which is you've got to come from a brand named school to get into the space, I don't think it's that important. I think what's important is can I get you the clinical skill, so that you've understood how to move data around, how to process it, how to do testing, how to do design, and then I can bring you into the space and bring you in as an entry level employee. That premise I think is not part of the American dream but it should be. >> Absolutely, looking for talent in these unexpected places. >> College is not the only in point. We're back to having I think vocational schools for the new data economy, which don't exist yet. That's an opportunity for sure. >> And you said earlier, domain expertise, in healthcare as an example, points to what we've been hearing here at the conference, is that with data understanding outcomes and value of the data actually is just as important, as standing up, wrangling data, because if you don't have the data-- >> You make a great point. The other thing I tell young people in my practice, young people I interact with, people who are new to the space is, okay I hear you want to be a data scientist. Learn the business. So if you don't know healthcare get a healthcare education. Come be on this project as a BA. I know you don't want to be a BA, that's fine. Get over it. But come be here and learn the business, learn the dialogue, learn the economy of the business, learn who the players are, learn how data moves through the space, learn what is the actual business about. What does delivering care actually look like? If you're on the payer side, what does claims processing look like from an end to end perspective? Once you understand that I can put you in any role. >> And you know digital four's new non-linear ways to learn, we've got video, I see young kids on YouTube, you can learn anything now. >> Absolutely. >> And scale up your learning at a pace and if you get stuck you can just keep getting through it no-- >> And there are free courses everywhere at this point. Google has a lot of free courses, Amazon will let you train for free on their platform. It's really an opportunity-- >> I think you're right about vocational specialism is actually a positive trend. You know look at the college University scandals these days, is it really worth it? (laughter) >> I got my nursing license through a vocational school originally. But the nursing school, they didn't have any technology at that point. >> But you're a great use case. (laughter) Excellent Adam, thank you so much for coming on theCUBE it's been a pleasure talking to you. >> Thank you. >> I'm Rebecca Knight for John Furrier. You are watching theCUBE. (techno music)

>> From Palo Alto, California, it's theCUBE, covering the Conference Board's Sixth Annual Innovation Master Class. (fast techno music) >> Hey, welcome back everybody. Jeff Frick here with theCUBE. We are at the Innovation Master Collab at Xerox PARC. It's put on by the Conference Board, a relatively small event, but really, a lot of high-caliber individuals giving really great presentations. And we're excited about our next guest, he kicked the whole thing off this morning, and we could go for hours. We won't go for hours, we'll go about 10 minutes. But Peter Coffee, he's the VP of Strategic Research for Salesforce. Been there a long time, but you were a media guy before that for many, many years? So Peter, great to see you. >> It's good to be with you, thanks. >> So, you talk about so many things. So many things in your opening statement, and I have a ton of notes. But let's just jump into it, I think. One of the big things is you know, the future happens faster than we expect it. And we as humans have a really hard time with exponential growth, because it's not built that way. That's the way things move. >> So how do you as a businessperson kind of deal with that reality? Because the issue is you're never going to be ready for when they come. >> Yeah, well, it's not just humans as individuals, but the institutions and processes we've built. If you look at the process of getting a college degree, it's really seriously misaligned with the timeframe of change. By the time you're a senior, half of the subject matter in your field may be new since your freshman year, and conversely four years after you've graduated, perhaps a third of what you were taught will no longer be considered to be current information. Someone at Motorola once said, "a batch process "no matter how much you accelerate it "doesn't become a continuous flow process". You have to rethink what does a continuous flow look like, and that's useful conversation to have getting back to your actual opening question. When we're talking with customers, we say what are your unvoiced assumptions about the manner in which you have succession of technology, succession of product, and so on? Can we try to see what it would look like if that were a continuous process and not a project process? Many of our partners will tell us that their most difficult conversations with their customers are about getting away from a project mentality, a succession of Big Bang changes, into a process in which transformation is a way of life and not a bold initiative that will take a big sigh of relief and congratulate yourself on having transformed. No, dude, you've gotten your running shoes tied now you can begin to run. But now the hard part begins. >> Right, and the sun comes up tomorrow and you start to run again. You talked on big shifts count on new abundance and use horsepower. >> George Gilder's phrase, "errors are punctuated "by a dramatic change from a scarcity "to an abundance" so for example, horsepower or bandwidth or intelligence. >> So now we're coming into the era of massive big data we are asymptotically approaching free compute, free storage, and free networking. So how do you get business leaders to kind of rethink in an era where they have basically infinite resources, and it always goes back, so what would you build then? Because we're heading that way even if we're not there today. >> A Jedi mind trick that I often use with them is to say, let's not talk about the next couple of quarters, I want you to imagine the next Winter Olympics. When they light the torch four years from now I want you to try to visualize the world you're pretty sure you'll be living in four years from now and work backwards from that and say well if we all agree that within four years that's going to get done, well there's some implications about things we should be doing now and some things that we should stop doing now if we know that four years from now, the world is going to look like this. It helps free your mind from the pressures of incremental improvement and meeting next quarterly goals. And instead saying, ya know, that's not going to be a thing in four years and we should stop getting better at doing something that's simply not going to be relevant in that short of a time. >> So hard though, right? Innovators still, I mean, that's the classic conundrum especially if it's something that you have paying customers and you're driving great revenue to, it's hard to face the music that that may not be so important down the path. >> The willingness to acknowledge that someone will disrupt you, so it might as well be you, you might as well disrupt yourself, the conversation was had with IBM back in the days of the IBM PC, that they thought that that might be a quarter of a million machines they would sell, but whatever you do, don't touch the bread and butter of the 3270 terminal business, right? And they did not ultimately succeed in visualizing the impact of what they had done. Ironically, because they didn't think it was that important, they opened all the technology, and so things like Microsoft becoming what it is and the fact that the bios was open and allowed the compatibles industry like Compact to emerge was a side effect of IBM failing to realize how big of a door they were opening for the world. You can start off a spinoff operation. At Salesforce we have a product line called Essentials which is specifically tasked with create versions of Salesforce that are packaged and priced and supported in a way that's suitable to that small business. And that way you can kind of uncouple from that Clayton Christensen innovators dilemma thing by acknowledging it's a separate piece of the business, it can be measured differently, rewarded differently, and it's going to convey itself maybe even through a genuinely different brand. This is an example that was used once with Disney which when it decided it wanted to get away from family and children's entertainment, and start making movies aimed at more adult audiences, fine, they created the Touchstone brand so they could do that without getting in the way of, or maybe even polluting, a brand that they spent so much time building. So branding is important. A brand is a set of promises, and if you want to make different promises to different people, have a different brand. >> Right, so I'm shifting gears 'cause you touched on so many great things. A really popular thing that's going on now is the conversion of products to services. And repackaging your product as a service. And you talked about the don't taze me bro story which has so many elements of fun and interesting but I thought the best part of it, though, was now they took it to the next step. And we're only a stones throw away from Tesla, a lot of innovation but I think one of the most kind of not reported on benefits of these connected devices and a feedback loop back to the manufacturer is how people are actually using these things, checking in from home, being able to do these updates. And you talk about how the TASER company now is doing all the services, it's not even a service, it's a process. I thought it's awesome. >> Taking a product and selling it at a subscription price does not turn it into a service, even though some people will say, well see now we're moving to a services model. If you're still delivering a product in a lumpy, change-it-every-couple-of-years way, you haven't really achieved that transformation. So you have to go back into more of a sense of I mean, look at the expectation people have of the apps on their smartphones, that they just get better all the time, that the update process is low-burden, low-complexity, low-risk, and you have to achieve that same fluidity of continuous improvement. So that's one of the differences. You can't just take the thing you sell, bill for it on a monthly subscription, and think that you achieved that transition. The thing that they folks who were once TASER and now are Axon, of which TASER is a sub-brand, they managed to elevate their view from the device in a police officer's hand to a process of which that device is a part. Which is the incident that begins, is concluded, results in a report, maybe results in a criminal prosecution, and they broadened the scope of the Axon services package to the point that now it is selling the proposition of increased peace officer productivity rather than merely the piece of hardware that's part of that. So being able to zoom out and really see the environment in which your product is used, and this relates to yet another idea which is that people are saying you got to think outside your box. It doesn't help if you get outside your box, but all of the people with whom you might want to collaborate are all still inside their boxes. And so you may actually have to invest in the transformation and interface development of partners or maybe even competitors, and isn't that a wild idea. Elon Musk at Tesla open sourced a lot of their technology with the specific goal of growing that whole ecosystem of charging stations and other things so Tesla could be a great success. And the comment that I once made is it doesn't help if you're a perfect drop of artisanal oil in a world of water. You have to make the world capable of interacting with you and supporting you if you really want to grow. Or else you're an oddity, you're Betamax, which might have been technically superior but by failing to really build the ecosystem around it, wound up losing big time to VHS for a while. I may have to explain to all of your viewers under the age of 30 what VHS and Betamax even mean. >> I was sellin' those, I could tell you the whole Panasonic factory optimization story, which is whole 'nother piece of that puzzle. So that's good, so I'm going to shift gears again. >> You have to look a big perspective, you have to be prepared to forget that your excellence is your product, and start thinking of that as just the kernel of what needs to be your real proposition which is the need you meet, the pain you address, the process of which you become an inseparable part instead of a substitutable chunk of hardware. >> Well and I think too it's embracing the ongoing relationship as part of the process, versus selling something to your distribution and off it goes you cash the check and you build another one. >> Well that's another aspect, we've got whole industries where there's been a waterfall model. Automobiles were a particular example. Where manufacturers wholesaled cars to distributors who gave them the small markup to dealers who owned the buyer customer. And dealers would be very hostile to manufacturers trying to get involved in that relationship. But now because of the connected vehicles the manufacturer may know things about the manner of use of the vehicle and about the preliminary engagement of the prospective buyer with the manufacturers website. And so improving that relationship from a futile model, or a waterfall model, into a collaborative model is really necessary if all these great digital aspects are to have any value. >> Right, right, right. And as a distribution of information that desire to get a level of knowledge is no longer the case, there's so much more. >> Well it's scary how easy it is to do it wrong. IDC just did a study about the use in retail banking of technology like apps and websites. Which that industry was congratulating itself on adopting in ways that reduce the cost of things like bank office hours. And yet J.D. Power has found that the result is that customers no longer see differentiation among banks, are less loyal, more easily seduced by $50 to open a new bank account with direct deposit. And so innovation's a vector, and if you aim it at cost reduction, you'll get one set of results. And if you aim it at customer satisfaction improvement, you'll innovate differently, and ultimately I think much more successfully. >> Right, right, so we're almost out of time here. I want to go down one more path with you which I love. You talked a lot about visualization, you brought up some old NOPs, really talked about context, right? In the right context, this particular visualization is of value. And there's a lot of conversation about visualization especially with big data. And something I've been looking for, and maybe you've got an answer is, is there a visualization of a billion data point dataset that I can actually look at the visualization and see something, and see the insight. 'Cause most of the ones we see that are examples, they're very beautiful and there's a lot of compound shapes going on, but to actually pinpoint an actionable something out of that array, often times I don't see, I wonder if you have any good examples that you've seen out there where you can actually use visualization to drive insight from a really, really big dataset. >> Well if a big data exercise produces a table of numbers, then someone's going to have to apply an awful lot of understanding to know which numbers look odd. But a billion points, to use your initial question, well what is that? That's an array that's 1,000 by 1,000 by 1,000. We look at 1,000 by 1,000 two-dimensional screens all the time, visualizing a three-dimensional 1,000 by 1,000 cube is something we could do. And if there is use of color, use of motion, superposition of one over another with highlighting of what's changed, what people need most is for their attention to be drawn to what's changing or what's out of a range. And so it's tremendously important that people who are presenting the output of a big data exercise go beyond the high-resolution snapshot, if you will, and construct at least some sense of A B. Back in the ancient days of astronomy, they had a thing called the Blink Camera which would put two pictures side-by-side and simply let you flip back-and-forth between the images, and the human eye turned out to be amazingly good. There could be thousands of stars in that picture, the one dot that's moving and represents some new object, the one dot that suddenly appears, the human brain is very good at doing that. And there's a misperception that the human eye's just a camera. The eye does a lot of pre-processing before it ever sends stuff to the brain. And understanding what human vision does, it impressed the heck out of me the first time I had a consultation on the big data program at a university where the faculty waiting to meet with me turned out to be from the schools of Computer Science, Mathematics, Business, and Visual Arts. And having people with a sense of visual understanding and human perception in the room is going to be that critical link between having data and having understanding of opportunity threat or change. And that's really where it has to go. So if you just ask yourself, how can I add an element of color, or motion, or something else that the human eye and brain have millennia of evolution to get good at detecting, do that. And you will produce something that changes behavior and doesn't just give people facts >> Right, right. Well, Peter, thank you for taking a few minutes. We could go on, and on, and on. >> Happy to do chapters two, three, and four any time you like, yeah. >> We'll do chapter two at the new tower downtown. >> Any old time, thanks so much. >> Thanks for stoppin' by. >> My pleasure. >> He's Peter, I'm Jeff, you're watching theCUBE. We're at the Master Innovation Class at Xerox PARC put on by the Conference Board. Thanks for watching. (fast techno music)

(ambient soft rock music) - First, GDPR is probably the best representation of really good, stringent, proper consumer privacy data controls that exist. So even if you're not compelled to abide by GDPR, it's a great road map and it's a great model to follow 'cause it's just good data discipline. We also have the good fortune at Informatica that some of the leading healthcare organizations in the country are our customers and they happen to have footprints in Europe, and so they do in fact have a GDPR challenge. Do I have a patient from the EU that's coming to my U.S. based facility? Do I have a U.S. based patient that's in a EU facility? Do I have an EU licensed provider? Right, the complexity of the GDPR challenge for some of our U.S. based healthcare customers is pretty involved and they're acutely aware of it. So I don't think there's been anything like GDPR in terms of data protection that's existed in healthcare. - GDPR by the way is a data problem. So GDPR is not necessarily a compliance security problem because you want to understand which data path to boundaries, who's accessing it, true data problem. So today, I mean in fact at Informatica you have customers like PayPal talking about their journey with us on GDPR. So you begin with the catalog and then we have three products that help in the GDPR journey, the catalog, Secure@Source, and the Data Governance Axon product. And again, each company's GDPR implications are slightly different and companies like I said like PayPal are using our products to run the GDPR activity right now. So we're seeing that going through the roof and in fact one of the big use cases for catalog has been in the context of governance and GDPR. - With the introduction of GDPR this year really brings a spotlight onto all the data privacy issues that we have to deal with around the world, but I think we have a fundamental problem with security which is it's still this baked on, add on, a thing that's applied to your applications and instead we actually need to look at programming languages in the apps that you write as being security-proof from the very beginning and that's gonna require a programming language to do that at the lowest level and an OS as well. - How is Ballerina handling that? They doing it up front, what's the-- - Our approach to it is that we assume all data is tainted and that the developer has to explicitly say this is safe data to avoid intrusion attacks on that. So the compiler will actually reject any code that is not explicitly given that task. - Very simply, what does GDPR promise, right? It's restoring the fundamental rights of data subjects in terms of their ownership of their data and the processing of their data and the ability to know how that data is used at any point in time. Now imagine if you're a data scientist and you could for a problem that you're trying to solve have the same kind of guarantees. You know all about the data, you know where it resides, you know exactly what it contains. They are very similar. They both are asking for the same type of information. So in a sense if you solve the GDPR problem well, you have to really understand your data assets very well and you have to have it governed really well which is exactly the same need for data scientists. So in a way, I see them as, you know, they're twins. Separated at some point, but.

>> Announcer: Live from Las Vegas, it's theCUBE! Covering Informatica World 2018. Brought to you by Informatica. >> Hello, everyone, welcome back. This is theCUBE's exclusive coverage of Informatica World 2018. It's our fourth year covering Informatica on the front lines. Every year it gets bigger and bigger. I'm John Furrier, the host of theCUBE, with Peter Burris, my co-host, with some, chief analyst at Wikibon and SiliconANGLE on theCUBE. Our next guest is theCUBE alumni Amit Walia, who's been on many times, even before he was president. Now he's the president of products and strategic ecosystems for Informatica. Great to see you, great to have you on. Congratulations on your keynote. Thanks for stopping by. >> Thanks, John, glad to be here. Always good to be back. >> You're super, well, I love talking with you because one, you know, the business is growing. You've been in the product side, you guys are all great product folks. And this, they're shipping products. It's not like it's, like, vaporware. It's, like, great stuff. Now Azure deal was announced. But now the timing of the data play with Switzerland, we talked about this fabric, better time than ever. This year, you got data lakes turned into data swamps last year. This year it's about governance and catalog. Good timing. What's your assessment? Give us your point of view from the keynote, timing, product. >> Well, I mean, I think you're exactly right. We see that it's a unique time, and it was building over the last couple of years. So, you know, we have this phrase that this is a data 3.0 world where data has become its own thing. It's no more captive to an application or a database. Those days are gone. And I think in data 3.0 world, I think we talked about it this morning in my keynote, that, you know, customers have to step back and think differently. You can't just do the same old things and expect to be different, and especially as they're driving digital transformations. So we introduced this concept of system thinking 3.0, where as you're thinking about a data, you have to think about it as a platform. A nimble platform, not a ERP-ish platform. Think of it at scale. It's doubling every year. >> Yeah. >> Think of it metadata in, metadata out. Let AI assist you. You know, you've got to have, we as humans are just going to be swamped with so much data we can't process it. And last, very important thesis, as you all know, is that governance, security, and privacy have to be design principles. They cannot be an afterthought. >> Last year you announced CLAIRE AI component of the system. >> Amit: Yeah. >> How has that evolved this year? I mean, I know it was a strategic centerpiece for you guys. Obviously the catalog is looking really strong right now, a lot of buzzing to show around the enterprise catalog. Where is the AI, the CLAIRE piece fitting in? Can you just give us the update on CLAIRE? >> Well, CLAIRE's come a long way. Basically part of every product we have. So it manifests itself probably most holistically in the catalog, but whether in the data lake, it's in the context of surfacing data, discovering data, giving recommendations of data to an analyst in a very business user context, all in the context of an MBM, giving you relationship discovery of, let's say, John, who you are, into who you are. So it is in Secure@Source helping anomaly detection happen. So CLAIRE has now made its way into every product. But as you said, the one product where it basically surfaces itself in its full bloom is the catalog, which, by the way, has been the fastest growing product in Informatica's history. One year since launch, it has just gone, taken off. >> Well, presumably there's a relationship. Sorry, John. Presumably there's relationship there. Catalogs have been around for years, but they've been very, very difficult to build and sustain and maintain. CLAIRE presumably is providing a capability that removes a lot of the drudgery associated with catalogs, and that's one of the things that's making it possible. Have I got that right? >> No, yeah, absolutely. And actually, building the new catalog also has been a hard thing. So in some ways building it for scale has been a massive common sense problem that we've been solving for the last three, four years. You know, collecting metadata across the full enterprise is a non-trivial activity, so it was never done across the enterprise ever. If you remember when I was here last time, our vision for the catalog was very simple. We want to be the Google for enterprise data... >> Peter: Yeah. >> ...through metadata. >> And that's what we were able to do through the catalog. But as you rightfully said, it's very hard to consume it if you don't write AI to help it. That's where CLAIRE made a very big road. So the UI's very straightforward. It's a Google UI, and any business user can, with the help of CLAIRE, start using it. >> But it persists. >> Yes. >> So unlike just putting a search term in and getting a page of stuff back, a catalog has to persist. >> Has a persistence, exactly. >> And so describe, now that you have that in place with CLAIRE, as John asked, where does it go? >> Solving use cases. Actually, I'll give you a little preview. Tomorrow I do the closing keynote, and usually what I do, the closing keynote is all about features. So actually, it's a whole demo on CLAIRE where we're taking CLAIRE to the whole next level. As a great example, you know, building data supply chains, you know, it's a manual activity that you have to do. With the help of the catalog, we actually understand the system architecture. So if you want to add new sources of data or change anything you want to do, you don't have to go through those steps again. We will service it to you and we'll tell you what to do. In fact, tomorrow I'll show what we call a self-integrating system. It'll happen by itself. You have to just go and say whether I agree or not agree and the machine learns. Next time it gets smarter and smarter. Or in the context of governance. If a new policy comes up in an enterprise, the biggest challenge is how do I even know what the impact of the new policy is? Look at GDPR right now. So with the help of CLAIRE, we can understand across the entire enterprise what would be the impact of that policy across different functions and what the gaps are. Those are the kind of places we are taking CLAIRE towards more bigger business-driven initiatives. In fact, tomorrow there'll be a whole demo on that one. >> I mean, GDPR is interesting because it really exposes who's ready. >> Yeah. >> Who has had invested their, the engineering in data, understands the data. So that's clear. We're seeing some, and it's also a shot across the bow of companies saying, look, you got to think strategically around your data. We talk about this all the time with you guys, so it's not new to us, but it is new to the fact that some people are right now sitting there going, oh no, I need to do something. >> Amit: Yeah. >> How is Informatica going to help me if I have a GDPR awakening of, oh man, I got to do something. >> You know, GDPR... >> Do I just call you up and do the, roll in the catalog? Do I... >> That's a great place to begin, by the way. So GDPR, by the way, is a data problem. So GDPR is not necessarily a compliance/security problem, because you want to understand which data pass through boundaries, who's accessing it. It's a true data problem. So today, I mean, in fact, at Informatica World, we have customers like PayPal talking about their journey with us on GDPR. And so you begin with the catalog, and then we have three products that help in the GDPR journey, the catalog, Secure@Source, and the Data Governance Axon product. And again, each company's GDPR implications are slightly different, and companies, as I said, like MasterCard, like PayPal, that are using our products to run their GDPR activity right now, it's a... So we are seeing that going through the roof. And in fact, one of the big use cases for catalog has been in the context of governance and GDPR. >> I want to talk about the trends on, that are impacting you guys. Again, I was saying earlier that it's a tailwind for you guys. The timing's perfect. Multi-cloud, hybrid cloud. I'd say hybrid cloud's probably in its second year, maybe third year hype, but now multi-cloud is real. You have announced a Azure relationship. You guys have a growing ecosystem opportunity. >> Amit: Yeah. >> How are you guys looking at it? 'Cause it's really emergent. It's happening right now. How are you guys targeting the ecosystem, whether it's business development partnerships, joint product development go to market, and/or on the business side? What's the orientation, what's the posture? Are you guy taking a certain approach, expecting certain growth? What's the update on the ecosystem, the global partner landscape? >> You know, the way we think about ourselves is that we've been the Switzerland of data always. And customers, actually, I always say it's always customer-backed. >> John: Yeah. >> If you solve for the customer, everything goes good. Customers expect us to do that. And customers are going to be in a heterogeneous world. Nobody's going to ever pick one stack. You know, you all know, right, there are customers who are still, larger devices still running mainframe for some processing, and they are already using new platforms for IoT, so they have to somehow manage this entire transition, and there will be multi-cloud, cloud hybrid world. So they naturally expect us to be a Switzerland of data across the board, and that's our overall strategy. We will always be there for them. In that context, we work with, we have learned the art of working with their ecosystem. >> John: Yeah. >> So you saw Azure today, and we are very close partners of hundreds of customers. Amazon, hundreds of customers. Google's coming up. So those are common. So we, Adobe, tomorrow you'll have Adobe. >> John: So you're cool with all the cloud players. >> And, you know, I always look at it this way. If you solve for the customer, everybody will work with you, and I think we're doing meaningful work. So that's helping our strategy. But what we have done two very different things with that. We've gone deep in terms of product integration. I mean, you saw today. We are making it easy from a customer experience point of view to get these jobs done, right? If you are spinning up a data warehouse in the cloud, you don't want to repeat the mistakes of the last 20 years. So now it's five clicks, you should be good to go. >> John: Yeah. >> That's an area we've invested a lot to make sure that those experiences are a lot simpler and easier and very native. >> We had Bruce Chizen on earlier. He was implying that you guys have significant R&D, and he was trying to get me to get you the number. I think it was on Twitter. I think I'll ask Neal. I think he's out there already. But it's not so much the numbers. It's about the investment and the mindset you guys have for R&D. I know you had, went with a private equity company. >> Amit: Yes. >> We talked about that. >> You guy are growing. >> So this is a growth company. >> Amit: Yeah. >> You need R&D. >> Absolutely. >> What is the priority? How are you looking at that? How would you talk to the industry and customers about your R&D priorities? >> Well, I think we've been very blessed, and I think our investors, and I think Bruce, when we sit in a board meeting, you know, we always joke around. They have never skimped on investing in products. And I think that we've been, our belief is that we are the innovation leader in our markets. There is a massive opportunity in front of us to obviously capitalize on, and the only way you do it where you innovate, and innovate means we invest. And I tell you we've been very fortunate that the investment in products has continuously increased every year. I mean, this year, forget just the products and technologies. We made, John, double digit million dollar investments in building a brand-new hosting architecture across the world, in Americas, NMEI and APJ, and we benchmarked ourselves against the Amazons and the Azures of the world, not our competitors. So not just products, but taking the cloud infrastructure across the globe, most secure, most... >> So your own infrastructure. >> Absolutely. >> Well, I mean, we run our own stuff. >> Yeah. >> But we leverage both AWS and Azure in that context. But our goal is that we can be in the countries because data should not leave some of those countries. We comply to the biggest regulations. So we've made lots of investment, and hence we can also innovate and get into new product categories. I mean, you see we have a whole new cloud architecture out there. Catalog, security, these are all brand new markets that actually, some of them have all come out since we went private. Actually more innovation has come out of Informatica since we went private than in the three years previous to going private. >> So, you know, let's play a game. Let's say that the catalog, doing very well. Let's say that you, working with Microsoft, working with AWS, you're actually successful at establishing a standard... >> Amit: Yeah. >> ...for how we think about data catalogs in a hybrid, multi-cloud world. Combine that with R&D and products. If you have, in a data-first world, where the next generation of applications are going to be data-first, that catalog gives you an inside edge to an enormous number of new application forms. >> Amit: Yeah. >> How far does Informatica go? >> Well, that's a great question. I mean, I think, I generally believe that in some ways, we are barely scratching the opportunity in front of us. I mean, none of us have seen where this world will go. I mean, who would have imagined, think of all the trends that have happened. Look at the world of social, where it has brought us to bear. I generally think that, look, each company that I talk to, each customer I talk to, and I talk to hundreds of customers across the earth, they all want to become a tech company. They all want to be an Amazon or a Google. And they realize that they will not become an Amazon Google by replicating them. The best way they can become an Amazon Google is to figure out all of the data they have and start using it, right? >> Institutionalizing their work around their data. >> Exactly. So that's where the catalog becomes very handy. It's a great first step to begin that. And in that context, there are Fortune 5000, there's Fortune 10,000, there are mid-market customers. I think we have just literally scratched the surface of that. >> Do you envision catalog-driven applications... >> Amit: Oh, absolutely. >> ...that get into, with the Informatica brand on them? >> Oh, so we actually have, so a great point. We actually made the catalog rest API-driven. So there are customers who are building their applications on the catalog. In fact, I'll give you a preview of that tomorrow. I'll show a demo where Cognizant took our catalog, took CLAIRE within the catalog, used Microsoft's chatbot to create a complete third-party custom application called the Data Concierge, where you can go ask for data. So it's Microsoft chatbot, our CLAIRE engine, and a custom app written by... So the world where I see is that it will be, that is a central nervous system of the platform, and enough custom apps will be written in time. >> It's a real enabler. So I got to ask, and I know we got not a lot of time left, I mean, but I want to get thoughts on cloud native. >> Amit: Yeah. >> 'Cause you have, with containers, you don't have to kill the old to bring in the new. And what you guys are doing is with on-prem and some of the coolness, ease of use around getting the data kind of cataloged in with the metadata, you're enabling potentially developers. Where does this lead us with containers, microservices, service meshes, 'cause that's right around the corner. >> It's happening as we speak. I mean, so we rewrote the cloud platform as I just talked about. It's completely microservices-based, completely. We had to, we had a whole cloud platform. We basically said we're going to rewrite the whole thing. Microservices-based. And it's containerized. So the idea is that A, microservices give you agility, as we all very well know. We can innovate a lot faster. And with the help of containers, you can just rapidly scale, I mean, rapidly deploy. You can test. Dev becomes a whole lot easy. The, I mean, today's cycle is so short. Customers want to do things rapidly. So we are just really helping them be able to do that. >> So you see the data actually being an input into the development process... >> Oh, absolutely. >> ...via microservices and your service mesh. >> I mean, if you don't do that, you don't know what you're building. >> It's going to be a data-first world. My, going back to my point, I think there's an opportunity for you guys to then go to the marketplace with some thought leadership about what does it mean to build data-first applications. Historically we start with a process and we imagine what the data structure's going to look like, we put it in the database, and then there's all the plumbing about interaction and integration. You guys are saying get your data assets, get your data objects rendered inside the catalog and think about the new ways you can put them to work, and you think of your code... >> Amit: Yeah. >> ...as the mechanism by which that happens. >> Flips everything on its ear. >> Amit: Yeah. >> It's a data-first world, and a data-first approach to building applications seems like it's an appropriate next conversation. >> That, I agree with that, and that's a big opportunity, and obviously there's a task at hand to make sure we can help educate everyone to get there. And I think, you know, it'll take some time, but of course that's the, anything which is easy is not interesting. It's a hard problem that where you basically, you solve and you kind of make it a big industry. >> I mean, it's great to see you. We feel like we've been following the journey of the success of you guys. We've been talking, go back four years. >> Amit: Yeah. >> You can go back to thecube.net, look at the tape. You can see the conversations. You guys stayed on task. Great product team, very, you guys are kicking some butt out there. Congratulations. Final question for you. Put you on the spot. Biggest surprise this year for you. What's, obviously the catalog, you mentioned it's been taking off. What surprised you? Anything jump out in terms of successes, speed bumps in the road, architecture trends? What's the big surprise? >> You know, I think I'm actually very warmed up by seeing, I talked about the day zero. You know, it is a data-driven world where we see so many customers looking to come here. We've become the biggest data conference of the industry. In fact, we were reflecting, Informatica World has become the biggest accumulation of people who think data-first. And I think that has been more than any technology. To me, at the end of the day, look, as much technology will come and stay, I'm a big believer it's people that make the difference. >> John: Yeah. >> And I've been seeing all of those people here, seeing them make contributions, learn, and drive change has been my biggest, not only a positive surprise, but biggest, you know, gratification that I've seen at Informatica World. >> And the emphasis of not having such a big hype. I mean, getting excited about new technology is one thing, but the rubber's got to hit the road. You've got to have real performance, real software... >> Yeah. >> ...real results. >> 'Cause the pressure of scale fast, time to market... >> ...all that stuff. >> Right. >> Congratulations, great to see you. Amit Walia, president here at Informatica on products and strategic ecosystems. I'm sure he's going to continue to be busy over the next year when we see him certainly at our next theCUBE event. Amit, great to see you. I'm John Furrier, Peter Burris, live here at Informatica World 2018. It's the largest data-first conference on the planet We'll be right back with more after this short break. (musical sting)

>> Announcer: Live from San Francisco, it's The Cube covering Informatica World 2017, brought to you by Informatica. >> Hey, welcome back, everyone. Live here in San Francisco for Informatica World 2017. This is The Cube's exclusive coverage. I'm John Furrier with SiliconANGLE and The Cube. My co-host, Peter Burris with Wikibon Research. Our next guest, Justin Donlon, the Business Applications Manager, Carbonite; a customer of Informatica, welcome to The Cube. >> Thanks, it's great to be here. >> So you've done a lot of interesting things. We were just talking before you came on camera. >> Yeah. >> Really hard. Moving to the cloud was really easy. >> Right, it helped us big time. >> So tell us about some of the interesting things you've got going on. >> Okay, well, this is a great use-case which we've been speaking about here at Informatica World. We sell through a number of distributors and through probably 8000, 9000 partners, but two of our distributors. We didn't have an e-comm way of interacting with him so we built up this manual, semi-manual process. We actually called it the manual, automated, auto-process. (laughing) That's what we called it. So we built up this process and we just thought we can't keep going like this. We had received a purchase order in email, send it over to sales ops then open it, validate it , does this make sense? They agree, sign it off, pass it onto finance. Finance would open it, say, "yep, makes sense," key it into our great playing system, (mumbles), pass it on to provisioning. This is for a SaaS product that we sell. It's just not scalable at all. >> John: A lot of touch points through there-- >> Too many touch points and a delay for something that should be instant. So we spoke to these distributors and said, "What do you have, what can we do?" We didn't have any options for API integration, so they said, "Well, we've got EDI," so we said, "Okay, first question, what does that stand for?" (laughing) 'Cause we were a cutting-edge company, you know and everything that we do is kind of, >> So 1980s. >> Yeah, I know. Kind of bleeding into it. so we kind of did our homework a little bit and found out what EDI is electronic-- >> John: Where do we sign up for it? >> Yeah, Electronic Data Interchange and then we said, "How are we going to do this?" We kind of looked around a little bit, spoke to our partners at Informatica and I said, "You know, we've got a EDI-capability in the cloud." So we said, "Great, let's do a POC," so we did that POC, banged it together pretty quickly, which is the beauty of a SaaS offering, or the beauty of the cloud, and as we were building this up, we were working with our counterparts at these distributors. These guys who lived and breathed EDI for all their partners and at some point, I just thought you know, we're building this thing up, I don't have anything to compare it to. How do we know if we're even building the right thing? We're just going on what we think seems to be making sense so I phoned him up one day and I said, "Listen, would you mind just taking an hour "and let me walk through what we're building here? "Let me just show you what we're building. "See if it makes any sense." And so he said, "Sure, I'll be happy to do that." He knows EDI back to front and as you mentioned just now it's a very complex, very in-depth, old-school kind of system, old-school, we're processing transactions. I showed him what we'd built out and (mumbles) leveraged Informatica, Salesforce as a front-end. There's a really, really kind of bolted on solution, but we managed to put it together in a few months. I showed him each part and at some point, or at many points, I was waiting for him to interrupt and say, "Well, hang on a second, why are you doing that?" But he didn't, he was silent through everything. So I thought, "Okay, what have we done here?" And so I turned it over to him and I said, "What do you think, is this okay? "Are we doing the right thing?" And he paused for a second and then he said, "Yeah," he says, "this is actually quite an elegant solution "that you've built out in a few months. "This is what has taken us 10 years to mature into." >> John: He was mad! >> I think he was a little mad and for me, it was just a big sigh of relief as I thought, "Okay, we're actually are on track," and we've actually been able to do something really quickly and elegantly through a SaaS product, through these cloud offerings. >> That's a great use case of Informatica. You've taken something that's hard and cloud made it easy for you to do and you had no baggage. In this case, it was a green field for you. What other end-to-end examples are you guys working on because data is now going end-to-end and sometimes it's multi-vendor, of course, but cloud's going to help you. You got there, anything you got else going on? Into any IOT, big data stuff you happening? >> IOT, well, more especially, big data is becoming more and more important to us. As we've kind of grown through our consumer business, Carbonite started out as a consumer product, and as well over one and a half million consumer subscribers and is moved into the very small business, then into this kind of SMB space and a little bit into the enterprise space, and as we've been doing that, we need to understand what we're doing, especially at very small business through the enterprise space. We've acquired these companies. One of the key things we need to do as we acquire companies is identify opportunities for cross-sell and for up-sell, and in order for to do that, we've got to get that data into one repository where we can figure it out pretty quickly. So that's a huge initiative at Carbonite at the moment is building out our data vault and our data legs and getting some accurate and good data governance as we fee this data into these data vaults with our analytics team. >> Peter: That's on the operational side? >> Yeah, that's on the operational side. >> So what Carbonite does is as a service to your customers, which is, I'm not going to say it's standard, but it's some really value-complex, complex things that you do. Has the engineering that you've done there informed the process by which you're starting to re-engineer in your digital footprint on the operations side? >> I know that there are conversations that kind of happened between engineering on the product side and the analytic side, but I think we'd love to see more of that discussion happening. Often what happens in any company, I think, is that you get the silos as we know, but the more that we can facilitate these discussions, I think the better it will be for us. >> Peter: So as you look at the Informatica Tool Care, the presence of, where are you starting, where do you anticipate you're going to use more of some of these tools, whether it's Power Center or MDM, et cetera, as you try to do this, as you try to replicate the experience you just had with EDI and the cloud transaction manager? >> That's a really good question. We've used application integration, so real-time application integration, which is a tool called ICRT. We've used Informatica Cloud Services, which is kind of batch-transferring of information to and fro. We've just, with EDI, implemented B-to-B gateway, which is for that connectivity with partners. And I think one of the key things for us moving forward is going to be data governance. As we have these different sources and different companies coming in, we've got to make sure that we govern and steward and ship it, and can I say sheriff, the data into its rightful homes accurately. We're trying to do that at the moment and we're doing it through spreadsheets and SharePoint and Lucidcharts and diagrams and Visio. One of the tools which I saw, which is an Informatica acquisition, Informatica Axon is a data governance tool. It doesn't store any data, but it just helps you manage and control your data. I think that's going to be crucial for any company which is working at amalgamating systems and data from various sources. >> John: What's the biggest challenge with data integration? One of the things, this is, companies have different views of the problem and opportunity. What's the biggest challenges that people have? >> You know, this is going to sound silly, but one of the biggest challenges that we have right now is just defining our data, defining what this term means. Even just this week, we've got one term, Sale Type, and still we're trying to figure out exactly what that means. That's one field that we want to be able to present to the business and we're still saying, "Hang on a second, what about this scenario?" I think that's the biggest deal is just to have a uniform definition of your different metrics and KPIs and attributes across the business. >> If you do that, you're going to first, you got to find the sources, you got to understand the degree to which synonyms are or are not synonyms, and then you got to go through the social engineering of getting people to agree so it is clear, for example. Do you see that as a facilitator for this process? >> I think it will be, I definitely think that will be, especially with the self-discovery or the intelligence structure discovery. I think that's going to be an exciting thing to see. >> I really like that intelligence structure discovery. That is just, that's not available in today's market. >> Yeah, that's right, but I think we've stepped away from that, I really do think so. >> You guys are. >> Yeah. And as an industry I think we are, with Informatica, partnering with Informatica. >> With Informatica, how are you guys working through (mumbles), you guys as a customer? What specifically are you guys doing with them? Sounds like that EDI thing is an enabler. What else are you working with them on? Share some specific-- >> Yeah, that's right. It's still, at this stage, it's kind of the, it's all cloud. We don't have any on-prem Informatica, so it's all the cloud stuff, and we use it extensively for our cloud systems, our cloud business applications: Markelo, Salesforce, Zuora, NetSuite. Those are the four big ones that we're using and those are the same (mumbles), I guess. So we're using Informatica to bridge the gap between these different systems a lot and so that's our kind of bread and butter with Informatica at the moment. >> John: How about developers onsite for data and dealing with data? How do you guys organize staff and skillsets? Is it mostly engineering? Is there data analysts, data science, how do you guys? >> Yeah, good question. We've got engineering, which kind of sits on the product. Then we've got IT business applications, which is where I fit in, and that's a combination of kind of business analysts as well as developers who build out this, a lot of the systems, and then we have an analytics team. The VP of analytics with Advanced Analytics, analytics platform, Data Lake, Data Vault, and so with those are the three big groups that we look at where Informatica splits across the different groups. >> Now you guys are pretty solid with Informatica, happy with them? >> Yes, very much so. >> Yeah, we've got a great partnership with them. Every time we've bought, it's not because it's been a hard sell. (mumble), We've said, "Okay, we need that," "and this is what we need." >> John: So not a hard sell. How long you been a customer, just curious? >> Almost three years. >> John: So you're not legacy Informatica. You're not locked in? >> No, I'm not, I've never even seen the on-prems. I've never even seen Power Santa, I hope to never see it. I'm not interested. >> You're cloud-native? >> Cloud, cloud first. That's right. >> How 'about you guys, multiple clouds? What kind of clouds (mumbles) do you guys have? >> With Informatica? >> No, for you guys. >> For us-- >> Salesforce, Markelo. >> Those are the things, all those business applications. Salesforce, Markelo, a little bit of hybrid stuff. We've got our own on-premz-- Do you have your own data center? >> We do have, as Carbonite? >> Yeah. >> Absolutely (talking over each other) Our customers data. >> Would you put that in the cloud, customer data? >> Yeah, that is, in fact, moving to the cloud. >> John: Alright, you are. >> Yeah. >> But under your control. It's your, effectively it's your cloud. So as you think about working with Markelo, Salesforce, Zoira, remmember the last one you mentioned, Oh, NetSuite >> Netsuite. >> As you look at those four, everybody, everybody is, all these SaaS companies are making, have a realization that if I can get the data, then I get the customer. Are they starting to make it more or less easy for you to perform these integrations across how they handle things? Where do you think their willingness to expose their APIs, get more information about the metadat, et cetera, is going so you can do a more effective job of bringing it together and creating derivative value out of these very rich, cloud-based applications? >> I think that's an excellent question. And for me as somebody who is not a developer, but as for me as somebody who's very very interested in moving and lending and transferring and transforming data, I have to rely on a tool like in Informatica because I don't want to go digging in the bowels of NetSuite to try and pull data out. I don't even want to have to write an API core. I honestly don't want to do that and I don't really want my team to be doing that. I want to be able to point Informatica at a system and say what have we got, so for me that's crucial. So I think that's where the partnership between a Salesforce and Informatica, I'm relying on that and I think that those sources, like the NetSuite and the Salesforce, I think they're going to continue to hopefully have this really good open partnership with these middleware or these integration tools. We have to have that. If we don't have that, we're stuck. The same people are going to start breaking into Salesforce and breaking into NetSuite to get the data 'cause we're going to get it one way or the other. >> Justin, great success story. I'd love to hear the cloud, need it being, you know, taking advantage of Informatica, really highlights that they've got the modern approach. Appreciate you coming out. Justin Donlon, Carbonite Applications Manager. This is The Cube with coverage of Informatica World 2017. More live coverage here after the short break. Stay with us. (innovative tones)

[Announcer] Live from San Francisco, its theCUBE, covering Informatica World 2017. Brought to you by Informatica. (upbeat music fades) Okay, welcome back everyone. We are live in San Fransisco for Informatica World 2017. This is theCUBE's exclusive coverage, two days. We're on day two, meeting all the top executives, customers, sentures, system integrators, all the best guests here at Informatica World. Part of Informatica's three year coverage with theCUBE. I'm John Furrier with Peter Burris. Our next guest is Bala Kumaresan, who's the senior vice president and general manager of data security for Informatica, formally in charge of engineering, been in R and D, super technical, knowledgeable. Thanks for spending the time to come on theCUBE, appreciate it. >> Thank you. We get to ask you all the tough questions under the hood. What's in the engine of innovation. >> Absolutely. >> Peter: First question, the innovation engine for Informatica, what is it? Describe it quickly. So, the innovation engine of Informatica is entirely metadata driven. It's a data centric metadata driven engine. We call this concept CLAIRE. (John chuckles) It's EI driven, and in a sense, in order for you to make better decisions, you really need to look at your metadata. You really need to-- One of the most important things in security, which actually, current traditional systems lag behind, is the lack of data centricity, resulting in lack of accuracy. If you really want highest time-to-value, and the ability to respond quickly, you really need to be smart enough. Not only out-of-the-box accuracy, but also a period of time, learn, and look into the inputs that are specific to your ecosystem. Specific to that particular environment, and be able to provide actionable insights. Actionability... Actionability without accuracy is basically disaster. >> One of the big drivers in today's market is some of the penalties around governance. Okay, so, there's um, what do you call, G... >> Peter: Oh, GDRP? >> GDRP >> Bala: GDPR! GDPR. >> GDPR, and then Europe is different than North America, but bottom line is you get penalized. There's a risk management piece around the governance, but that's if you've been hacked, so lets talk about the security is fundamental to governance. They play hand in hand. What bet did you guys make on security, and what should people watching know about what Informatica's doing with respect to security, data security? >> I think, great point. General data protection regulation at Europe, that's a regulation that's actually going to go effective May 2018. It's going to be, like, 4% of your annual revenues are going to be the fines in case for every non-compliance and so on. So, we believe that part of the problem that exists today, with or without GDPR, GDPR is today, tomorrow it could be something else, is that lack of versatility, lack of versatility. The entire traditional data security is all about perimeter. You secure the perimeter, and everybody inside the perimeter is trusted. I was just telling, where trust begins, vulnerability seeps in. (Peter chuckles) So you really need to trust and verify. And, what are you protecting? You're really protecting data, so insights into the data is super critical. Our investment on secular source is centered around the Informatica Metadata Company, and insights into the data, how to you translate that into a security prospective. That is precisely what we have done. So, what kind of data you have? Classify the data. How is it being used, where are all that is present, who the users are. Everything is changing. >> So data is the fundamental centroid for security, because perimeter's gone, right? I mean, you got the cloud. I mean, not gone, but its not the fundamental-- >> It becomes the primary citizen in a security regime. >> Yes, yes. So... >> Well said. >> Absolutely. It doesn't matter where your data is. It could be in your relational databases, it could be in the cloud, it could be in your big data systems. It does not matter. It's all about data. Let me give a couple of examples as to the problems that exist today. Once you are inside the perimeter, and you are an authorized user, you pretty much are a trusted person, and then nobody is monitoring your behavior. Are you still the same person, or has somebody hacked into your account? Or did the person turn into... Did his role shift? None of that is being-- So, basically, two main things we are delivering part of our innovation. Role-based access control. It's not user, user... Identity based access control, it is actually role-based access control. If your role is in a IT, versus if your role is a development organization, You, within a company, could move but your privileges actually should be based on the role. That's number one. The second thing is that, look, you... Let's say you have access to all the sales force, because you are a sales force, you're actually part of our sales team. You typical patterns are that you're look at 10 records, 20 records a day, even though you have access to the million records, right? But, the base line and the behavior changes. They're actually indicate something. So this is part of trust and verify. You trust a person, but you also need to verify. Keep up with the changes, and that's fundamental to the data centric security. >> I want to amplify a piece of that, and tell me if I'm so appropriately. Role based security, I would actually ask, are we going to move to something we might call context based security, where context is what do you do. The role is part of what you do. So it says, what do you do, and who are you, and how are you doing it. So that's number one, and number two is, how does this relate back to some of the metadata initiatives that you guys have, where increasingly, some of the most crucial metadata will be the metadata that's ultimately used to put bounds on how the data gets employed. >> Let me answer that question in three different dimensions. Number one, yes. Absolutely. Role is part of the context. It's not the entire the entire context, but role is part of the context. >> Peter: Correct. >> Any protection, and any access to the protected information needs to be role based. Number two, the data context that we have in our product, where we go and catalog and classify all the data, that is very much used in prioritizing. For example, an alarm that goes on in a school during the school hours versus an alarm that goes on in a junkyard. They're both alarms. Today most of the traditional security actually kind of categorizes them as similar. An alarm went off. But, are they the same? No, they are not. So that's where the second level of the context. The third level of the context is in terms of the real... Basically, third level of the context is actually, what do you need to be in compliance with. What kind of usage is allowed? It's actually nothing to do with that particular usage itself, its actually got to do with a whole bunch of other safeguards that you need to manage. That's where our central policy management comes in the picture. So with these three contexts, the business context, the user context, and the category or the classification of the data context, it is totally-- >> All that has to be part of the security regime. >> Absolutely. That's actually, the metadata that we have, which drives those accurate decisions, accurate decisions for prioritization as well as detection, and the right protection. >> So here's a question, then. Again, I'm going to test this on you. Historically people have separated data, data sec-- metadata, data security. In the future, how do we keep those separate? We have to start seeing how they come together, right? >> I think, fantastic, fantastic question. Our view is that data governments is about... The governance actually has a slice across many dimensions. One of them is the data stewardship, the provenance, and the quality of the data, and so on. The other part is actually about data security governance, in terms of what kind of safeguards the role based access control. Really, what kind of risks that you are entitled to and, how are you managing the risks. So, that's our views. So, when we look at metadata, the metadata is actually driving multiple decisions. One of them is quality. The other one is risk. The other one is protection. So, we see this as a unifier bringing things together. Informatica is uniquely positioned with our Axon, EAC, and Secure@Source products. In fact, one of the things that we are announcing in Informatica World is actually about our GDPR bundle, because GDPR is actually about, as much about data governance as about privacy, and also it is about policy driven data protection. >> Well, privacy, policy, inform. The governance regime. You can't separate. It's not just about compliance, and I'll give you-- I'm going to test one more thing on you. At some point in time, as we think about digital business and the idea that a digital business is defined more by its use of data assets. Otherwise its just a business, and we want to protect our data. We're also worried about how we share our data, and how others share data with us. We want to make sure that we are not inappropriately exploiting somebody else's data because we don't want to create a billion dollar business that fundamentally, upon inspection, was predicated on the misappropriation of somebody else's data. >> Absolutely. You are touching upon the consent, and the consent control, and what kind of validations we have in place to evaluate... This might not be popular. What I'm going to say is not necessarily popular, right? I think it goes back data ethics, as well. I think companies consider customer data, partner data as their asset. They, 20 years, 30 years of how the data's been used, I think the realization is going to sink in. The realization is already sinking in with respect to the ethics, with respect to the trust-- >> John: That it's not their data. >> It's not their asset. >> What's sinking in is it's not their data assets. >> Its not their data. They are, in fact... They are, in fact, obligated. They're, in fact, supposed to use that with care. They're, in fact, accountable for that data. So, while regulations are starting to put those things in place, with GDPR being one and then every other... Geography is going to come up with its own set of modifications similar to that. I think this is a fantastic opportunity for companies to go to that higher order, and really start to think this as, why they are ethical. What is the ethics that they want to put in place, above and beyond what the regulations talk about. I think Informatica is uniquely positioned with our metadata driven strategy, with our metadata cloud engine which is driving solutions across quality, governance, and security as well as constant control over-- Yeah. >> Well let me make one more point on that. It comes back to this fundamental notion of your brand is the promise you're making to the marketplace. What you just described will have more impact on company brands in 10 years, and probably even five years, than the characteristics of the products they sell very often. >> Absolutely. If I'm an investor, I'm thinking about reputation. What is the company's reputation? What kind of pull effect the reputation has towards expanding the business. That is where the ethics, actually, is in higher order of existence. Where, people want to partner with you. People what to do business with you, and I think that's actually where we can be very helpful. I mean, there're already intelligent solutions, use them intelligently. >> Its interesting you bring up data ethics, because I wanted to jump in on that, because if digital transformation, if we believe that its happening, and of course everyone's talking about business transformation, which is the outcome of digital transformation, ethics transforms too, digitally. >> Bala: Digitally, yes. >> So, where is, in your mind, the ethics with data? Is there, I mean there's articles that's thought leadership around it, but, is it actually in use. Do actually people have data ethics in your opinion? Is this something that's talked about but not walked? Your thoughts on that, reactions that-- >> I think it's an evolving concept. So far, companies have been taking advantage of the data. The evolving concept is going to catch on. It is actually catching on. Analysts are actually talking about it. I think we are thinking about it. We are thinking about what we are building is actually kind of going to help customers go there. But I want to also separate it. There is actually something that is at a higher level of existence versus what is really, absolutely necessary and need it today? Policy driven data protection while we are able to standardize the policies across the enterprise, across all your data silos. That is super critical, to get the immediate problem resolved while we can start to build on that's access towards the ethics. >> This economy's a scale. You can't just jump the data ethics and be ethical. You got to, you got to build your way up. Have a trajectory and tract record of foundational-- >> Here's what I say John, and Bala, you know, tell me if you think I'm wrong, but... >> Make sure you say if you think he's wrong. >> Yeah, please do, cause I have been wrong in the past. You said something very interesting. You said, "Yeah, everybody's talking about data, >> Data ethics. or additional business. And that's just it. They're doing it, but they're not doing plan-fully, because we often don't understand exactly what it is, and the process of thinking though the ethics is crutial to informing that planful approach to thinking about digital business. At least, that's my perspective. What do you think about that, Bala? >> I think the versability. The versability at the board level, the versability at the senior exec's level, as to where you stand. What is your risk? What is your compliance scorecard? Do you have a plan in place where there's an informed remediation plan? Did we actually allocate sufficient budget? Its not about budget justification, its actually about did you allocate budget for this risk. Also, do we have systems in place that are continuously assessing and reassessing to basically drive towards risk correction and towards maintaining the compliance. Those are key, and I think that addresses what you are saying, and I think I agree with you. >> So, lets take this very practically. If you look at the industry, you see companies like Apple and Microsoft being very clear about how they're going to use their customer's data. >> John: Facebook? (John laughs) >> You see Facebook and Google being less clear about how they're use your data. You see Amazon right in the middle, and people wondering which way they're going to go. This is a huge issue. Not to talk about it's security level, but just overall business model. This is going to have an enormous impact on a global basis of how we think about digital business and the role data's going to play in creating new shareholder customer value-- >> If data's the new gold, so here's my take on this. Love to get the reaction. If data's the new oil, if data's the new gold, the new heartbeat, whatever metaphor you use. If its the new gold, let's just say its the gold. That's valuable. So, the value will shift to whoever has the data. Someone's going to wake up and say, hey wait a minute. That's my data. And I think you're starting to see that a little bit with Facebook certainly. Less Google because the utility is pretty well intergraded, but at some point the utility value has to be greater than than the value of the data gold, if you will, cause otherwise, I will demand the data back. So I think there's end user, or the primary use of the data, the primary user of data-- >> This is a very coarse view, but I wonder if Uber right now is wondering how they could've used data security different, relative to the 200 million, what ever it is, lawsuit that Waymo's bought against them. So this issue of ethics and the role the data's going to play is going to have enormous implications-- >> John: Love that conversation on the eithics side. >> Yeah, I think actually if you look at the way companies use data, and then the way you lay out in terms of where different companies are, that is actually a spectrum of how you could question them. One is actually how they can help the consumer. That's something that we all love. And then there's an absolute exploitation. >> John And Peter: Yes. And then there is something in the middle, and ethics is actually not about exploitation. Ethics is actually about keeping people informed. Letting them know exactly-- >> John: Transparency. >> Transparency, and-- >> John] There's always an underbelly everywhere. >> Peter: Well, you can a bad ethics. (Bala laughs) >> All those bad actors out there. Okay, we got to wrap it up. I want to get one quick comment from Bala. Obviously, I can't help but jump to blockchain when I start thinking about security. Thoughts on blockchain. How's that going to be relevant, if any. Obviously, supply chain. You're seeing some indications there. Blockchain has a potential mechinism-- >> The blockchain technology is very compelling. It has the integrity. Its basically... One of the things that I've always talked about with my team and in general for prag development is that security has always been in the past, as an afterthought. As something that sits outside, and if you were to go back and design some of the systems that we built in the last 20, 25 years, with so much emphasis on privacy and compliance and security and protecting breach, wouldn't security be built in, part of the design? Part of the code. >> John: The primary (John laughs) >> part of the design. Right? So, very appealing from that point of view. The applicability of blockchains today is mostly around transactional ledgers and... basically transfer of value, and so on. I think one of the, you know-- It also has, it also comes with certain baggage. The blockchain remembers everything. You know, (John laughs) So, let me zero in on... I think everybody's trying to figure out how to actually apply blockchain beyond the traditional, beyond the ledger and so on. I think it's going to have a place. Its going to have a place in... We're already starting to see that some applications where shot-dam contracts like, for example, you're doing a building contract that is a supplier, that is actually a valuer, and it is a project. It exists for a temporary period and it goes away. All of the coordinating parties are coordinating with confidence. They're sharing and colliaberating with confidence. Blockchain actually gives them confidence, because it has-- >> So it's relevant, but it's emmerging. Still at, not, it's early innings-- >> It's relevant. It's emerging. We are very closly looking at it. I think we already have a play there, where one of the main and most important things that blockchains mean is that... Identity. As a unique identity. If you look at some of the old prducts... Customer 360, its all abnout quality of customer data. Data quality for customer data, right? There, perhaps, is a way for us to integrate the blockchain. The other place where we are already looking at is can we consume the information in the blockchain to enhance our metadata? Of course we can. >> Peter: Yeah. (Peter laughs) >> So, those are two low hanging fruits, and of course we'll keep it... We'll stay-- >> We'll have to get you down to our studio in Palo Alto. We'll do a whole segiment on unpacking blockchain. I love blockchain. I think, my personal belief is yeah, there's some low hanging fruit that'll use-cases, but if theirs money to be had in reconfiguring parties working together to create wealth-- I have some crazy thoughts on this, actually. (laughter) So we can not stipulate, because-- >> John: You're definitely coming to Palo-- We're going to go to where you are! >> Did we run out of time, or-- >> John: We're running out of time. Let's follow up Bala. Great conversation. Great fireside. Show's like a fireside chat. That was phenomoneal. Thanks for sharing the data and the insight. We're live here in San Fransisco for Informatica World 2017. More exclusive coverage from theCUBE. I'm John Furrier with Peter Burris, after this short break. Stay with us. (upbeat music)

>> Narrator: Live from San Francisco, it's the Cube. Covering Informatica World 2017. Brought to you by Informatica. (futuristic electronic music) >> Welcome back, everyone. We're here live in San Francisco. This is the Cube's exclusive coverage of Informatica World 2017. I'm John Furrier looking to angle the Cube. My co-host, Peter Burris, head of research for SiliconANGLE media, also general manager of Wikibon.com. Our next guest is Albrecht Powell who's the enterprise information management global lead at Accenture Analytics. Welcome to the Cube. >> Thanks very much. Good to be here today. >> John: See you're sporting the sideways A, not to be confused with siliconANGLE red A, which is the other way around. Great to have you on. >> That would be the accent on the future. (laughing) Our moniker. >> So, um. Great to have you on. Center analytics. A lot of people may or may not know-- huge investment in data science. You guy's are doing a lot of work, and integrating in with customers. Not just on the management consulting side, but, you know, a lot of the architecture, a lot of the delivery-- You essentially manage services across the board. >> Albrecht: Oh yeah. >> There's a lot of architecture going on, so I got to ask you about the data powered enterprise vision that you have, because that's the theme that you guys have. What does that mean, first of all? And how does it relate to Informatica World, and ultimately the customers just trying to get to the Cloud, lower their costs, increase their top line. What's the digital transformation connection? >> Boy, lots of questions in there. So, you know, to us, in the digital revolution that's happening right now, the expectations on companies are just growing exponentially. You've got customers, you've got shareholders, business partners. You've got stockholders that all have so much more insight on companies. They want more, and they're putting so many demands on companies today. So, it's causing disruption in the industry. We all know about the Uber's. We all know about going from print media to digital media. But you've got companies like John Deere; they sell tractors, right? But they're moving toward a platform based company now, where they're now working with farmers, they're working with agriculture, helping to support. So, when you've got that as a different business model, you've got that coupled with the explosion in data. So, you know, the statistics-- Amazon, I think it took six years to get their first trillion. Now it's you know, the next trillion they got in one year. By the year, I think 2020, 1.7 megabytes of data is going to be created per person per second. These are staggering numbers. And when you put those two together, I personally think that the next big wave, the next big value proposition for clients, is going to be data, and harnessing the power of that. When I look back over my 28 year career, I go back to the ERP days. That was the big wave. Right? You had to be on Oracle or SAP or PeopleSoft or JD Edwards. I think right now, we're just starting in this phenomenal wave of opportunity. >> You mentioned re-platforming, or platform approach. The word re-platforming is an industry buzzword. But that really is an impact to IT, business operations, and personnel, and ultimately the business model! I mean, this is like a serious impact. >> It really is, and that is where this data powered enterprise comes in. We're trying to work with our clients to figure out how to harness this value proposition, unlock the data that they've got stuck in their systems, the dark data wherever it may be, and unleash that and try to gain business insights from that. >> Alright. Take us through the playbook, because okay-- I buy it. I see the train coming down the tracks that is really high speed. I bet I got to move to the new model. You look at Amazon, it's a great proof point. Hockey sticks since 2010. No doubt about it. Just one tell sign. I want to move. Now, I got to be careful, if I move too fast I get over my ski's, or over-rotate-- whatever metaphor you want to use, but how do I get there? What are you guys doing with clients and what's the strategy? Playbook. >> You know, the biggest thing we try and do is the relationships we have with clients are long term, trust based relationships. And when we go in, we're not selling a product. We're trying to help them drive business value. So, what we typically do around the data space is help them figure out what's the strategy, what's the vision, where do they want to go? They may think they need a data quality solution, an MDM solution. But you know, we come in and we talk to them and we realize: what are you trying to get out of it? Where do you want to go? And lay out a vision, a set of guiding principles. And that framework often times help them drive within the next one-two years, a much more sustainable set of growth as opposed to trying to do a point solution. So typically, we'll start there. But, you know, we'll also come in if they're hemorrhaging, if they're bleeding, if they've got major problems. Or, if they're trying to hit a strategic adjective, procurement spend analytics, or growth, or disruption in the market. Those are the type of things that we'll come in and talk to them about to start with. >> Is there a mindset-- obviously, there's a mindset shift. But given that, certainly if the certain room's on fire, you take care of those first. I get the critical piece of it, 'cause sometimes it is mission critical right out of the gate. But, is there an architectural mindset? Is it a building blocks approach? Has there been a shift in how to deploy and iterate through, in an agile way, that you've seen a pattern that's emerged? >> I mean obviously Cloud is big with everybody today, and the hype out there is everybody's moving everything to Cloud. And in reality, a lot of our clients-- They've invested a lot in these data centers, so they're reticent to make the leap. So, we're working with them to help, and Informatica has been phenomenal with some of the tools and solutions that they have to help them pull over to you know, Cloud based solutions. And you know, most of our clients right now, they have a hybrid architecture. They're moving in that way. They've got some stuff that they want to keep close and tight, they've got some stuff that they want to move. But between OpenSource with the new subscription models-- For instance, and Informatica has. It's a game changer for our clients. Because now, they're able to get solutions up faster, quicker, and we do a lot of work with our liquid studios to help them pile at those type of solutions. >> But it's still got to be in service to some outcome, or to some idea? >> Albrecht: Absolutely. >> So, that suggests that one of the challenges that people have been having in the big data universe is this disconnect between what we want to do, and implementing a dupe on a cluster. And that notion of how do we actually introduce some of the concepts of design into that process so that we can see realistically, and practically, and in a way that executed, a process to go from the idea down to the actual implementation? So, use cases are a big issue. Getting developers more involved and active is a big issue. But, what is the role of design in this process? >> So one of the things that we've shifted to is we have a set of innovation centers, where we'll bring clients in, and we might start with a workshop or two, right? To talk to them about the capabilities. But very quickly we evolve that into design thinking sessions, to really draw out what's the real challenge they're trying to find? Because half the time, they think they know what the problem is, but they really don't, and we help them uncover that. And then, from a design standpoint, we do a lot more prototyping now, where we'll go through and actually build in a matter of weeks, a real time capability that they can go take and run with. We have this thing called the Accenture Insights Platform, where we've negotiated with a lot of partners, such as Informatica, to have their tools, their software, in a hot, ready Cloud-based environment, where again, in the matter of a couple of weeks, we can stand something up, and they can see it, they can touch it. It's no longer the big capital investments to go start these type of projects. >> But it has to again, be something that people can touch and can play with. >> Albrecht: Exactly. >> And start themselves, to start saying, "Well, yes, "it works here. It doesn't work here." So they can start iterating on it. It's a way of increasing the degree to which iteration is the dominant feature of how things roll out. Ties back to the use case. As you guys think about the tooling that's available, from Informatica and elsewhere, how does the tooling-- Is the tooling robust enough at this point to really support that process, or is there still some holes we have to fill? >> Yeah, you know, I almost feel like the technology is there, right? We can do so much. The challenge that I run into when I meet with the C-suite-- I always ask the question, "What's your holy grail question?" If you knew this piece of information, how would that be a game changer? Eight times out of ten, I hear, "If I knew sales by quarter by region, "and that is was accurate, "I could really do something." It's like, that's not your question. The question should be: Who should I acquire? When is a customer going to walk out of the store? What's the weather going to be? What's the minimum amount of water I need to put in a plant for it to grow? You, know, in a drought situation. And those are the kind of questions that we are trying to draw out from our clients. And again, these design thinking sessions help us drive to that. >> John: Is that liquid studio's and the innovation centers the same thing? You mentioned liquid studios. What is that? Real quick. >> They are. So, again the whole idea behind these studios is that instead of doing, you know, starting with a massive project, or driving a massive five year RFP for a program. Again, get it in a liquid fashion; very agile, very prototypical, you know, build something. >> John: Very fluid. (laughs) >> Exactly right. And so that they can see, touch, feel, and manipulate these things. And then from there, they may want to scale that up. And you know, they may do it themselves. Often times, they'll partner with us to do it. >> You're partnering in the real time requirements definition of what they're trying to do. >> Albrecht: Correct. >> Well, it must be organized. I saw on Twitter that Accenture received the Informatica Ecosystem Impact Award last evening. Congratulations. >> Albrecht: Thank you very much, I appreciate that. Very excited. >> Where did that come from, and why is it important to you guys? Obviously, the recognition with Informatica, you guys are doing well with them. >> Now, Informatica is a very strong strategic partner of ours. I mean, we've worked with them for the last 18 or so years. I personally been involved with them the whole time. The company has vision, you know, when you talk to Anel, you talk to Ahmet, who was just on-- The vision that they have for their products, they know where they want to go. The reinvention that they've done here with the new branding, and the new marketing-- A lot of our clients had traditionally thought of them as more the power center, and more the-- >> John: The plumbing. >> Exactly. >> John: I'll say it. >> And we keep challenging them. It's like, you know, why aren't you bigger? Why isn't everybody using you? Because I think the tool set is robust enough right now. And again, it's finding these use cases to be able to apply this. >> Well, they made a big bed. The joke in silicon valley right now, in infrastructure companies, is that plumbers are turning into machinists, as kind of an analogy. But now with machine learning, you're starting to see things that they've made a bed on that's flowering, and it's important. And I think they made some good bets. They'll be on the right side of history, in my opinion. But I want to ask you a personal question, because you know, you mention waves. You mention the ERP waves and the software wave of the mini computer, which then became local area networks, inter-networking, et cetera. Basically the premise of what IT has turned into. With now, the disruption that's going on, how is it different? Because Informatica seems to be on that same software cycle in a new way. What is different about this new world order that's different than those days, the glory days, of rolling out SAP implementations, or Oracle ERP and CRM's. Shorter time cycles. What are the things that you're seeing that are key things that customers should pay attention to, they need to avoid, and things they should double down on, relative to this new wave of software? And how does Informatica fit into all that? >> Sure. The ERP wave was critical. It was the way to get everything under one umbrella. Very important, right? But today, the idea of single instance, companies can't keep up. They can't do that. So it's the nimble, it's the agile. I'm really excited about Informatica is that they've got the end to end solution, which is phenomenal, but they've also got the piece parts. And there's a lot of our clients that you know, they're trying to integrate multiple ERP systems together, they're trying to integrate multiple platforms, so MDM is becoming much more important today. Data governance. Absolutely critical out there. They've had a gap, frankly, in data governance for years. And yeah their acquisition, their AXON tool-- Again, it's a game changer out there and a lot of our clients are aggressively looking at that, and trying to do that. >> Paul: How does it change the game for some of your clients? Give an example. You don't have to name the customer, but in the use case basis. >> Everybody needs, you know. We talk about the need for governance, right? And it comes into whether it's paper based, whether it's automation-- Some way to get processes standardization and so forth around governance, and get people accountable. The tools that have been out in the market-- There are some that are good, but they're not integrated. There's no interoperability between them. And what I like about AXON now is they can sell it as a single point solution. Great way to get in the door of a client. But, they can also then integrate that with all of the other platform pieces that Informatica has, and that tie is really powerful. >> Well, governance also plays a role when you think about, for example, the idea that we want greater distribution of data-- Data is going to be more distributed. We want some visibility into that data through metadata, and (mumbles) talked about that. But, we heard from healthcare conversation this morning, and others, that one of the big barriers is, do I have access? Do I have rights? Do I have privileges to this data? And governance has to follow that process where people know in advance: What rights do I have? What access do I have? Am I using it properly? Am I breaking rules? That notion of governance can't just be centered on compliance and regulation, it has to be moved into more of an asset management approach. Do you agree? >> Right. Agreed. And the way we look at governance, it's expanding now. It's not the traditional data-owner, data-steward, data-operator any more. >> Yeah, it's not the central group. It's a corporate set of responsibilities. >> Right. And we're rolling governance now out to the end-user. So, how they are looking at data and interacting with data. Because data, now, it's a utility. It is something that everybody touches, everybody uses, not just an IT thing anymore. When you take that, and again you take the expanse of that into security. You know, as you talked about-- Secured source for example. The play in tying the two of those together. Very powerful solution. And even within Accenture, you know, we're tying our data, our governance, our security practices, much more tightly together as a single, unified solution. >> John: How does the AI machine learn, 'cause we hear in Claire their new interface, see LX out there, and Amazon. I mean Google I/O's announcing neural nets that train computers! Certainly it's a lot of buzzwords out there. Does that make the master data management, and the MDM, and the data quality more relevant? Or less relevant? >> I think just as relevant as it's always been. There's a lot of people that sit and say that the traditional data stuff is a commodity now. And again, machine learning is absolutely essential, AI. We need that because we're scaling so much bigger out in industry today. But, MDM is not going away. The integration between platforms, the need for good data quality. And I think, we almost took a shift in the industry to the buzzwords. Right? It's all about big data and AI and everything, and in some ways we almost left the traditional behind. And now we're coming back to realizing that you need good data to power the different data sources you've got, the big data and everything else, that then needs to be scaled, and that's where the machine learning-- >> And freed up for developers who have a DevOps mindset don't want to get into the nuances of being a data wrangler. >> Well, the patterns of data usage are going to be important, thinking about MDM. Because at the end of the day, you're not going to have copies of everything. >> No. >> You're going to have relationships, increasingly. >> Right. >> Peter: And MDM has to be able to capture that, too. >> Exactly. >> Alright, final question I have to ask you, what's the future for you guys? What do you guys see? 'Cause you guys always got the top brains in the industry working on things. what is Accenture's view of the future? What's the most important things coming down after this wave? Or is this wave just multiple sets, and to your clients, what are the top three things, or top things that you guys see as future waves or items that you're working on? >> You know, again, this data wave right now-- Again, it's the most exciting time that I've ever had in the career. And I see the growth that we're doing. And you know at Accenture, we have a lot of investment in research and development, we've got a team of data scientists that's out trying to mine data, figure out, you know, what the insights are that are out there. The liquid studios that we're pulling together. And, you know, as we talk to our clients, it's all about the art of the possible. It's not so much trying to sell a tool or solution. That's obviously important. But, where can we take you? What are the things that the industry hasn't thought of yet that we can take you as a company and help you disrupt into a new business market? >> Re-imagining the future. Thanks for coming, Albrecht. Appreciate it. Albrecht Powell with Accenture Analytics. Exciting this time in the industry-- I would agree data is certainly intoxicating at one level, but really great value opportunity. Thanks for coming on the Cube, and sharing the data with us as we analyze. Here on the Cube, more great coverage after this short break. At Informatica World 2017, I'm John Furrier, Peter Burris. We'll be right back with more. (futuristic electronic music)