>> Live from New York, it's theCUBE covering theCUBE New York City 2018. Brought to you by SiliconANGLE Media and its ecosystem partners. (techy music) >> Welcome back to the Big Apple, everybody. This is theCUBE, the leader in live tech coverage. My name is Dave Vellante, I'm here with my cohost Peter Burris, and this is our week-long coverage of CUBENYC. It used to be, really, a big data theme. It sort of evolved into data, AI, machine learning. Ronan Schwartz is here, he's the senior vice president and general manager of cloud, big data, and data integration at data integration company Informatica. Great to see you again, Ronan, thanks so much for coming on. >> Thanks for inviting me, it's a good, warm day in New York. >> Yeah, the storm is coming and... Well, speaking of storms, the data center is booming. Data is this, you know, crescendo of storms (chuckles) have occurred, and you guys are at the center of that. It's been a tailwind for your business. Give us the update, how's business these days? >> So, we finished Q2 in a great, great success, the best Q2 that we ever had, and the third quarter looks just as promising, so I think the short answer is that we are seeing the strong demand for data, for technologies that supports data. We're seeing more users, new use cases, and definitely a huge growth in need to support... To support data, big data, data in the cloud, and so on, so I think very, very good Q2 and it looks like Q3's going to be just as good, if not better. >> That's great, so there's been a decades-long conversation, of course, about data, the value of data, but more often than not over the history of recent history, when I say recent I mean let's say 20 years on, data's been a problem for people. It's been expensive, how do you manage it, when do you delete it? It's sort of this nasty thing that people have to deal with. Fast forward to 2010, the whole Hadoop movement, all of a sudden data's the new oil, data's... You know, which Peter, of course, disagrees with for many reasons. >> No, it's... >> We don't have to get into it. >> It's subtlety. >> It's a subtlety, but you're right about it, and well, maybe if we have time we can talk about that, but the bromide of... But really focused attention on data and the importance of data and the value of data, and that was really a big contribution that Hadoop made. There were a lot of misconceptions. "Oh, we don't need the data warehouse anymore. "Oh, we don't need old," you know, "legacy databases." Of course none of those are true. Those are fundamental components of people's big data strategy, but talk about the importance of data and where Informatica fits. >> In a way, if I look into the same history that you described, and Informatica have definitely been a player through this history. We divide it into three eras. The first one is when data was like this thing that sits below the application, that used the application to feed the data in and if you want to see the data you go through the application, you see the data. We sometimes call that as Data 1.0. Data 2.0 was the time that companies, including Informatica, kind of froze and been able to give you a single view of the data across multiple systems, across your organization, and so on, because we're Informatica we have the ETL with data quality, even with master data management, kind of came into play and allowed an organization to actually build analytics as a system, to build single view as a system, et cetera. I think what is happening, and Hadoop was definitely a trigger, but I would say the cloud is just as big of a trigger as the big data technologies, and definitely everything that's happening right now with Spark and the processing power, et cetera, is contributing to that. This is the time of the Data 3.0 when data is actually in the center. It's not a single application like it was in the Data 2.0. It's not this thing below the application in Data 1.0. Data is in the center and everything else is just basically have to be connected to the data, and I think it's an amazing time. A big part of digitalization is the fact that the data is actually there. It's the most important asset the organization has. >> Yeah, so I want to follow up on something. So, last night we had a session Peter hosted on the future of AI, and he made the point, I said earlier data's the new oil. I said you disagreed, there's a nuance there. You made the point last night that oil, I can put oil in my car, I can put oil in my house, I can't do both. Data is the new currency, people said, "Well, I can spend a dollar or I can spend "a dollar on sports tickets, I can't do both." Data's different in that... >> It doesn't follow the economics of scarcity, and I think that's one of the main drivers here. As you talk about 1.0, 2.0, and 3.0, 1.0 it's locked in the application, 2.0 it's locked in a model, 3.0 now we're opening it up so that the same data can be shared, it can be evolved, it can be copied, it can be easily transformed, but their big issue is we have to sustain overall coherence of it. Security has to remain in place, we have to avoid corruption. Talk to us about some of the new demands given, especially that we've got this, more data but more users of that data. As we think about evidence-based management, where are we going to ensure that all of those new claims from all of those new users against those data sources can be satisfied? >> So, first, I truly like... This is a big nuance, it's not a small one. (laughs) The fact that you have better idea actually means that you do a lot of things better. It doesn't mean that you do one thing better and you cannot do the other. >> Right. I agree 100%, I actually contribute that for two things. One is more users, and the other thing is more ways to use the data, so the fact that you have better data, more data, big data, et cetera, actually means that your analytics is going to be better, right, but it actually means that if you are looking into hyperautomation and AI and machine learning and so on, suddenly this is possible to do because you have this data foundation that is big enough to actually support machine learning processes, and I think we're just in the beginning of that. I think we're going to see data being used for more and more use cases. We're in the integration business and in the data management business, and we're seeing, within what our customers are asking us to support, this huge growth in the number of patterns of how they want the data to be available, how they want to bring data into different places, into different users, so all of that is truly supporting what you just mentioned. I think if you look into the Data 2.0 timeframe, it was the time that a single team that is very, very strong with the right tools can actually handle the organization needs. In what you described, suddenly self-service. Can every group consume the data? Can I get the data in both batch and realtime? Can I get the data in a massive amount as well as in small chunks? These are all becoming very, very central. >> And very use case, but also user and context, you know, we think about time, dependent, and one of the biggest challenges that we have is to liberate the data in the context of the multiple different organization uses, and one of the biggest challenges that customers have, or that any enterprise has, and again, evidence-based management, nice trend, a lot of it's going to happen, but the familiarity with data is still something that's not, let's say broadly diffused, and a lot of the tools for ensuring that people can be made familiar, can discover, can reuse, can apply data, are modestly endowed today, so talk about some of these new tools that are going to make it easier to discover, capture, catalog, sustain these data assets? >> Yeah, and I think you're absolutely right, and if this is such a critical asset, and data is, and we're actually looking into more user consuming the data in more ways, it actually automatically create a bottleneck in how do I find the data, how do I identify the data that I need, and how am I making this available in the right place at the right time? In general, it looks like a problem that is almost unsolvable, like I got more data, more users, more patterns, nobody have their budget tripled or quadrupled just to be able to consume it. How do you address that, and I think Informatica very early have identified this growing need, and we have invested in a product that we call the enterprise data catalog, and it's actually... The concept of a catalog or a metadata repository, a place that you can actually identify all the data that exists, is not necessarily a new concept-- >> No, it's been around for years. >> Yes, but doing it in an enterprise-unified way is unique, and I think if you look into what we're trying to basically empower any user to do I basically, you know, we all using Google. You type something and you find it. If you're trying to find data in the organization in a similar way, it's a much harder task, and basically the catalog and Informatica unified, enterprise-unified catalog is doing that, leveraging a lot of machine learning and AI behind the scenes to basically make this search possible, make basically the identification of the data possible, the curation of the data possible, and basically empowering every user to find the data that he wants, see recommendation for other data that can work with it, and then basically consume the data in the way that he wants. I totally think that this will change the way IT is functioning. It is actually an amazing bridge between IT and the business. If there is one place that you can search all your data, suddenly the whole interface between IT and the business is changing, and Informatica's actually leading this change. >> So, the catalog gives you line-of-sight on all, (clears throat) all those data sources, what's the challenge in terms of creating a catalog and making it performant and useful? >> I think there are a few levels of the challenge. I chose the word enterprise-unified intelligent catalog deliberately, and I think each one of them is kind of representing a different challenge. The first challenge is the unified. There is technical metadata, this is the mapping and the processes that move data from one place to the other, then there is business metadata. These are the definition the business is using, and then there is the operational metadata as well, as well as the physical location and so on. Unifying all of them so that you can actually connect and see them in one place is a unique challenge that at this stage we have already completely addressed. The second one is enterprise, and when talking about enterprise metadata it means that you want all of your applications, you want application in the cloud, you want your cloud environment, your big data environment. You want, actually, your APIs, you want your integration environment. You want to be able to collect all of this metadata across the enterprise, so unified all the types, enterprise is the second one. The third challenge is actually the most exciting one, is how can you leverage intelligence so it's not limited by the human factor, by the amount of people that you have to actually put the data together, right? >> Mm-hm. >> And today we're using a very, very sophisticated, interesting logarithm to run on the metadata and be able to tell you that even though you don't know how the data got from here to here, it actually did get from here to here. >> Mm-hm. >> It's a dotted line, maybe somebody copied it, maybe something else happened, but the data is so similar that we can actually tell you it came from one place. >> So, actually, let me see, because I think there's... I don't think you missed a step, but let me reveal a step that's in there. One of the key issues in the enterprise side of things is to reveal how data's being used. The value of data is tied to its context, and having catalogs that can do, as you said, the unified, but also the metadata becomes part of how it's used makes that opportunity, that ability to then create audit trails and create lineage possible. >> You're absolutely right, and I think it actually is one of the most important things, is to see where the data came from and what steps did it go to. >> Right. >> There's also one other very interesting value of lineage that I think sometimes people tend to ignore is who else is using it? >> Right. >> Who else is consuming it, because that is actually, like, a very good indicator of how good the data is or how common the data is. The ability to actually leverage and create this lineage is a mandatory thing. The ability to create lineage that is inferred, and not actually specifically defined, is also very, very interesting, but we're now doing, like, things that are, I think, really exciting. For example, let's say that a user is looking into a data field in one source and he is actually identifying that this is a certain, specific ID that his organization is using. Now we're able to actually automatically understand that this field actually exists in 700 places, and actually, leverage the intelligence that he just gave us and actually ask him, "Do you want it to be automatically updated everywhere? "Do you want to do it in a step-by-step, guided way?" And this is how you actually scale to handle the massive amount of data, and this is how organizations are going to learn more and more and get the data to be better and better the more they work with the data. >> Now, Ronan, you have hard news this week, right? Why don't you update us on what you've announced? >> So, I think in the context for our discussion, Informatica announced here, actually today, this morning in Strata, a few very exciting news that are actually helping the customer go into this data journey. The first one is basically supporting data across, big data across multi-clouds. The ability to basically leverage all of these great tools, including the catalog, including the big data management, including data quality, data governance, and so on, on AWS, on Azure, on GCP, basically without any effort needed. We're even going further and we're empowering our user to use it in a serverless mode where we're actually allowing them full control over the resources that are being consumed. This is really, really critical because this is actually allowing them to do more with the data in a lower cost. I think the last part of the news that is really exciting is we added a lot, a lot of functionality around our Spark processing and the capabilities of the things that you can do so that the developers, the AI and machine learning can use their stuff, but at the same time we actually empower business users to do more than they ever did before. So, kind of being able to expand the amount of users that can access the data, wanting a more sophisticated way, and wanting a very simple but still very powerful way, I think this is kind of the summary of the news. >> And just a quick followup on that. If I understand it, it's your full complement of functionality across these clouds, is that right? You're not neutering... (chuckles) >> That is absolutely correct, yes, and we are seeing, definitely within our customers, a growing choice to decide to focus their big data efforts in the cloud, it makes a lot of sense. The ability to scale up and down in the cloud is significantly superior, but also the ability to give more users access in the cloud is typically easier, so I think Informatica have chosen as the market we're focusing on enterprise cloud data management. We talked a lot about data management. This is a lot about the cloud, the cloud part of it, and it's basically a very, very focused effort in optimizing things across clouds. >> Cloud is critical, obviously. That's how a lot of people want to do business. They want to do business in a cloud-like fashion, whether it's on-prem or off-prem. A lot of people want things to be off-prem. Cloud's important because it's where innovation is happening, and scale. Ronan, thanks so much for coming on theCUBE today. >> Yeah, thank you very much and I did learn something, oil is not one of the terms that I'm going to use for data in the future. >> Makes you think about that, right? >> I'm going to use something different, yes. >> It's good, and I also... My other takeaway is, in that context, being able to use data in multiple places. Usage is a proportional relationship between usage and value, so thanks for that. >> Excellent. >> Happy to be here. >> And thank you, everybody, for watching. We will be right back right after this short break. You're watching theCUBE at #CUBENYC, we'll be right back. (techy music)

>> Announcer: Live from San Francisco, it's the Cube. Covering Informatica World 2017, brought to you by Informatica. >> Okay, welcome back, everyone. We're here live in San Francisco for Informatica World 2017. This is the Cube, a flagship program. We go out to the events and extract the signal from the noise. I'm John Furrier, the host of the Cube. Our next guess is Lima Rice, who's the chief data officer Global Enterprise Data Analytics for Allegis Group. Salema, welcome to the Cube. >> Thank you. >> So you won the Informatica Innovation Award Monday night. Congratulations. >> Salema: Thank you. >> You're also a chief data officer, so we love to have conversations with because really, what does that mean? (laughing) You're the chief of everything now. Data's at the center, you're like the heart surgeon of the organization. What was the award for? Tell us a little bit about Allegis Group. >> Sure. So the award was really about how we're innovating with data. So for us, it's really about using data as an asset and how we really want to transform our company the way that we transformed the industry almost 30 years ago. So we've really partnered with Informatica to build out our Master Data Management, data as a service, data quality, everything that would help us to find the right person for the right position at the right time. >> Talk about what you guys do at Allegis Group and how it fits into your parent company. A lot of folks, you guys are very large, but tell us a little bit about your firm. >> Sure. So Allegis Group is the largest talent solution company in the world, largest privately held one. We have almost 450,000 contract employees worldwide. We have over 500 offices in 53 countries that we service. Our two flagship companies are Tech Systems and Aerotech, which make up probably a little over 75% of our organization. >> So you guys match talent that's in your network with opportunities that they are fit for. >> That's correct, for most of the operating. For Tech Systems and Aerotech, which makes up that large portion, that's exactly what they do. Then we have service organizations and we have managed service programs and vendor management solutions and other operating companies that service other types of industries. >> You mentioned as we were getting started that you use data as a competitive strategy weapon, if you will, key asset. >> Absolutely. >> I kind of weaved in competitive strategy. If you're doing well, it's also competitive strategy. >> Right. >> If you're successful. That's the key conversation here at Informatica World this year and in the industry worldwide as they look at the assets differently. It's not just an accounting thing. Most CFOs know where the plant and equipment are, the depreciation schedule, itemization schedule, all that stuff is kind of like in Financial 101. Data now is coming in as an asset where sometimes they don't even know where the data is, that's one problem. How are you looking at that? Because take us through what that means to make data as the asset, and how do you wrangle it in, how do you get your hands on it so to speak, metaphorically speaking, and then, also, how do you deploy it as an asset? How does it get paid back to the company? >> So that's a lot of questions in there. I'll start with, we believe that being able to ingest any data from anywhere in any format and use that in order to enable our producers which are our recruiters and our account managers to make better, faster decisions and really reduce our risk is a way that we can help produce and make quality, fact-based decisioning. So it all starts with great quality data. When you think about the journey that somebody goes through of getting a job, there's probably not, maybe two other times in your life that are more traumatic, right? So, birth, death, and you know? >> John: I know. >> Getting married, maybe? >> John: That too. >> And changing careers, right? So we try to use data and we try to make the best out of each situation so that people feel like they're really becoming part of our Allegis family and not just taking a job. >> Or a piece, a resume that's on file so to speak. >> Salema: That's right. >> Take us through an example of a use case that someone could relate to with you guys or applying data and the benefit to you guys and your customer. >> So at any given time, we have roughly 55 million resumes that we're parsing through and trying to identify and make the perfect search and match for our customers. And that's really the core part of our business. >> 55 million. >> 55 million resumes. (chuckling) So within that search and match process, it's really important that my team help enable that search and match team with good quality data so that, when you think about, if you have bad data, you're going to make bad decision matching rules. And so the better quality the data, the better we can help that team. >> I mean, everyone's had an experience where they've gotten an email or something where you can see some sort of form was inserted Dear Placeholder, my name, they didn't insert my name. That's just a random example, but that's the kind of example where it's not personalized. It's not a fit for me. I'm like, hey, I'm a machine, you're talking to me, I'm a person, I instantly delete it if it's not already in my spam folder. >> Right. >> Similarly with your, it's a high touch and again, it's intimate-- >> Very much so. >> Very intimate to the user. How will you guys doing that personalization and what's the data angle on that? >> That's very important to us, actually. So when our founders created the company almost 30 years ago, they made three promises. They made a promise to the customer that they would work harder than any other vendor ever worked for them. They wouldn't stop until they filled that rack. To the consultants coming in, they made a promise that they'd never just sling their resumes. That they would get to know them intimately. They would find out their likes, their dislikes, what are things that they want to do to make a life? And then to the people working in-house, they promised that if you would work harder than you ever thought was possible, the company would pour into them and those three things are still the core value of what we do today. So while our competition looks very different today than it used to, I mean, for probably 20 years our competition looked exactly like us. The same model, the same comp model, everything. Until about four years ago, and we started seeing competition that had no brick and mortar, that has no recruiters. We have 25,000 recruiters, we have 500 offices. >> Where was the competition going? All online automated? >> They're going algorithm, so they're going bionic recruitment. The thing for us is that that relationship is what really sets us apart. The relationship means that much to us that we want to use data to enable our recruiters and enable our producers so that they can become more talented advisors and career coaches. >> You know, there's two things that jump in my head. One is, you don't want to be a slave to the algorithm. >> That's right. >> Or slave to process, you want the process to work for you. >> Absolutely. >> The second one is, we always talk about the start-up community and growing companies is that you always hear people, "Oh, he and she is a good fit." You know, being a good fit for a job really is key because you could be in a job and be unhappy and no one wins. >> That's right. >> So getting the fit is critical. So you guys are using humans with machines-- >> That's right. >> Together so you're making the data work for the human process which is a hybrid. >> That's right. We look at it as we use data to have a competitive advantage by empowering our producers and really using that combination of human touch and technology to deliver the best customer experience. >> Okay, talk about the marketplace. As you look back, and you notice your Informatica customer, we'll get to that in a second, but there's a lot of solutions out there. People are peddling software. You got to be kind of a skeptic, but you don't want to miss the wave. >> Salema: That's right. >> The data wave, that that's something you obviously as a Chief Data Officer. So you got to squint through the BS of the fog or the smokescreens that are out there. How do you tell, well first of all, what is the current landscape from your perspective? What's the right solutions that you see emerging out of this new modern era of data at the center? With software, with algorithms, and obviously mixed with humans. What's the big industry trend that you like, and what don't you like? >> Yeah, I love what Informatica's doing. I love that they're combining the best of artificial intelligence and machine learning into every application that they create. That's really critical to us, and I think to every company is we always say as we're teaching our children, if you learn from your own mistakes, you'll be smart. But if you can learn from the mistakes of others, you're going to be a genius. Well, when we make mistakes, if our applications can learn from them, but what if those applications can learn from all the customers and from the information that they're putting in? So Informatica embedding AI with Claire now, I think is genius. I think that it's going to set them apart and really set their customers apart. So that's why we like partnering with them. >> You mentioned data quality. It's one of my favorite topics, and I always talk about dirty data, it's bad for you. Clean data, good data, is really instrumental. >> Salema: That's right. >> How are you guys refreshing the data? Someone from Informatica was on, talking about heartbeat of data as the, but also that implies the heart is a critical organ so you need a surgeon for that, heart surgery. But sometimes, data hygiene. You need a data hygienist. So there's a spectrum of data interaction points. What's your thoughts on data quality? What are the key things you keep on top of to keep the data high quality? >> It's really important to us. We use, so if you think about one of the things that makes a great match for somebody, it's about the proximity to your position. So making sure that the addresses are clean. We use Informatica's data as a service. And we do all world geo lat long, and we do Address Doctor and address verification. Email verification is big in our business. Phone number cleansing, and then just overall making sure that we have a single golden record. If you think about somebody like me, I started with the company in 1998 as a consultant. So being out there as a consultant for 23 years and then coming in-house, all of my data from my maiden name still exists in our systems. So really, it's about not just cleansing good to bad, but making sure that you're creating that golden record of a person so somebody on LinkedIn might just put their first initial or on any third party system and knowing that those are all still the same person and making sure that we're connecting the right people is really important to us. >> You bring up such good points I don't even think about. Most people don't think about. But one of the most satisfying things about a job is the commute. I live in the Bay Area here. (laughing) If I'm in East Bay and I've got to go to Palo Alto, that's a nightmare. But that depends on the opportunity, right? So that's a blend. And the other one is the role of new data. So you mentioned LinkedIn. So LinkedIn seems to be a contextual resume, and in short term social network, which they're doing a decent job with. But that's more data. Reputation's super important in the world you're in. >> That's right, right. >> How are you guys looking at that? Because I can see how you guys got the blend of machines and humans, that's nice. Business philosophy's awesome. How do you guys get more reputation data points, too? Look for those blind spots. >> Sure. Well one of the things we do is by taking the person's information. One of the things that I think sets us apart from our competition is that we actually have the actuals. So if somebody, how they performed, how long they performed on a position for a lot of our consultants, that's information that we've had in our systems for 20, 30 years. So having the actual data to compare against what people are saying now makes a big difference. It's something our competition can't go out and buy. >> Yeah, it's interesting. It's just so interesting a world you're in. You're like in the cross hairs of a lot of moving waves. Look at the HR world is changing significantly from the world I live in in tech, for instance, has been a big thing and making sure people are being promoted. And the old way of doing HR is like, processes are kind of broken but the tools are available. So there's a whole dynamic going on in the future of work that's overlaying on top of your job. How are you dealing with that? >> It's very difficult. We use a lot of natural language processing and machine learning algorithms to really look at people and almost in some ways predict their level of thought leadership. So it's not enough any more to say, "I have those skills." It's can they do more than the skill we're hiring for and are they really going to be able to come in here and be that curious person, that problem solver, right? We can teach people tools. How do you teach somebody to be a problem solver? >> I can almost imagine Claire and some of these automated intelligences, I call it AIs. To me, it's automated intelligence. AIs don't really exist, I mean Google's probably about. Neural networks that teach neural networks, c'mon. >> Salema: Right. >> That's 1980s. But the augmentation is the key, and you think about what you're doing is you almost want the system to be working for the user. So instead of HR, you flip it around. So the HR should be notified that, "Hey, Salema needs a promotion right now. "She's peaked, she's been growing." Now new openings are coming up. Rather than trying to have the review, have the end user fill out their performances, having an ongoing performance track is probably pretty key. >> Yeah, it's something that we look at in our applicant tracking systems and how we keep track of the people that are out there working for our clients and the feedback that we get. Survey information is really important to us, both from our customers and from our consultants. So we use that to help them grow, and I mentioned earlier, one of the things that we tried really hard is coming to work for Allegis is about coming to work for a family where you're not just making a living, but you're making a life. >> Alright, final question, well, two final questions. But I'll get your thoughts on the show, that's a little bit of an easier question. The pointed question here, relative to what you're doing is, the world now with Cloud and data is about scale. And one of the things that's interesting about what you guys are doing at your work is it's pretty large scale. You mentioned 55 million people and beyond that. A lot of folks have to operate now at a higher level of scale. >> Yeah. >> What's your advice to other practitioners out there that have to start thinking differently in terms of order of magnitude scale. Just mindset, what advice would you share with folks on the scale question? >> I would say collect the data. Collect all the data you create as an organization. Collect everything, and then over time, connect it. Connect the dot. I often say collect it and we'll connect it. And I think that start small, right? I mean, when you don't want to boil the ocean, but collecting the data with the tools that we have today with the big data appliances, we use Cloudera, Informatica, by bringing all of that data into our enterprise data hub, then as those business problems exist and we can slowly start to help the organization by being those problem solvers. >> Awesome, great success story. Final question, word for you is, what's the show like? For the folks watching? What's the experience like, what's the vibe? >> Salema: At Informatica World? >> Informatica World here in San Francisco? >> It's been amazing. It's full of energy like the opening yesterday had my heart racing. It's really been a great event. It's a lot smaller than some of the ones that I think people are accustomed to coming to. And because of that, you get more of that personal touch. The classrooms aren't so big that you can't do a question and answers. >> John: It's very intimate. You get to meet the executives, they're very transparent. >> Yeah, absolutely. And really just see where it's going. And this isn't the kind of thing where you're seeing something that's going to be here years from now. You're seeing what's going to be released weeks from now. >> You're happy with Informatica? They've done a good job with the product? >> Absolutely. I love Informatica. I love our partnership with them. I mentioned for me, it's about, they have a seat at our table, and they help us solve problems and things where we didn't think they were possible, and they really help us identify what those things are and how we can resolve them. >> What do you think about their transformation? >> I love it. I absolutely love it. I love all of the buzz words around here, and I even love the new logo. I think it's great, it's full of energy. >> John: Salema Rice, thanks so much for spending the time here. >> Absolutely. >> Inside the Cube, sharing her experiences as an industry practitioner also large scale. Really using data as an asset, that is the theme here. And of course, we believe at the Cube. We're very data-driven as well, software-defined. And that's the future. Salema, thank you so much, it's the Cube. More live coverage here in San Francisco with the Cube after this short break. I'm John Furrier, stay with us.

>> 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)

>> Narrator: Live from San Francisco, it's theCUBE, covering Informatica World 2017, brought to you by Informatica. (driving techno music) >> Hey, welcome back everyone. Live here in San Francisco, Informatica World 2017, this is theCUBE's exclusive coverage from SiliconANGLE Media. I'm John Furrier, host of theCUBE, with my co-host Peter Burris, head of research at SiliconANGLE Media, also General Manager of wikibon.com, doing all the cutting edge research on data, data value, what's it mean, cloud, etc. Check it out at wikibon.com. Next guest is Suresh Menon, who's the SVP and General Manager of Master Data Management Informatica. The key to success, the central brains. MDM, great, hot area. Suresh, thanks for coming on theCUBE. Appreciate it. >> Thank you for having me. >> So, MDM has been in almost all the conversations we've had, some overtly and some kind of implied through... Take a minute to describe what you're managing and what the role is in that data fabric, in that Data 3.0 vision, why Master Data Management is so important. >> Right, if you think about Master Data Management, there are two ways to look at it. The first one would be in terms of MDM, let's follow the definition. Master Data is really about all the business critical entities that any organization is, you know, should be concerned about. So if you think about customers and products, that's the two most critical ones, and that's really where Master Data Management began. But then you should also think about employees, locations and channels, suppliers, as all being the business critical entities that every organization should care about. Master Data Management is about making sure that you have the most trusted, authoritative and consistent data about these entities, which can then fuel the rest of your enterprise. MDM has been used in the past to fulfill certain specific business objectives or outcomes, such as improving customer centricity, making sure that you're onboarding suppliers with a minimal amount of risk, and also to make sure that your products as being described and syndicated out to the web are done in the most efficient manner. >> You guys have the Industry Perspective Monday night. What was the insight from the industry? I mean, how was the industry... I know Peter's got a perspective on this. He thinks there's opportunity, big time, to reposition kind of how this is thought, but what's the industry reaction to MDM? >> The industry reaction is renewed excitement in MDM. MDM started off about 10 years ago. A lot of early adopters were there. And as is usual with a lot of early adopters, there was a quick dip into the cycle of disillusionment. What you've seen over the last couple of years and the excitement from Monday is the resurgence about MDM, and looking at MDM as being a force of disruption for the digital transformation that most organizations are going through, and actually being at the center of that disruption. >> Well it's interesting, I almost liken this to... I'm not a physicist, I wish I was, perhaps... Physics encounters a problem, and then people look at this problem and they say "Oh my goodness, that's, how are we going to solve that?" And then somebody says "Oh, I remember a math technique that I can apply to solve this problem and it works beautifully." I see MDM almost in the same situation. Oh, we've got this enormous amount of data. It's coming from a lot of different sources. How do we reconcile those all those sources? Oh, what a... oh, wait a minute. We had this MDM thing a number of years ago. How about if we took that MDM and tried to apply it to this problem, would it work? And it seems to fit pretty nicely now. Do you agree with that? >> I agree with that. There's also a re-defninition of MDM. Because sometimes when you look at what people think about, "Oh, that was MDM from seven years ago. How does that apply to the problems I'm dealing with today, with IoT data, social network data, interaction data that I need to make sense of. Wasn't MDM for the structured world and how does it apply for the new world?" And this is really the third phase of MDM, going from batch analytics, fueling old real-time applications, whether it was marketing, customer service and so on. And now, providing the context that is necessary to connect dots across this billions and billions of data that is coming in, and being able to provide that insight and the outcome that organizations are hoping to achieve by bringing all this together. >> You mentioned... I just want to jump in for a second, cause you mentioned unstructured data and also the speed of data, getting the value. So data as a service, these trends are happening, right? The role of data isn't just, okay, unstructured, now deal with it. You've got to be ready for any data injection to an application being available. >> Suresh: Yes. >> I mean, that's a big fact too, isn't it? >> Absolutely, and organizations are looking at what used to be a batch process that could run overnight, to now saying "I'm getting this data in real time and I need to be able to act on it right now." This could be organizations saying, "I'm using MDM to connect all of this interaction data that's coming in, and being able to make the right offer to that customer before my competition can." Shortening that time between getting a signal to actually going out and making the most relevant offer, has become crucial. And it also applies to other things such as, you identify risk across any part of your organization, being able to act upon that in real time as opposed to find out later and pay the expense. >> I know this is not a perfect way of thinking about it, but perhaps it will be a nice metaphor for introducing what I'm going to say. I've always thought about MDM as the system of record for data. >> Suresh: Yes. >> Right? And as we think about digital business, and we think about going after new opportunities and new types of customers, new classes of products, we now have to think about how we're going to introduce and translate the concepts of design into data. So we can literally envision what that new system of record for data is going to look like. What will be the role of MDM as we start introducing more design principles into data? Here's where we are, here's where we need to be, here's how we're going to move, and MDM being part of that change process. Is that something you foresee for MDM? >> Absolutely, and also, the definition of... MDM in the past used to be considered as, let's take a small collection of slowly changing attributes, and that's what we master for through the course of time. Instead now, MDM is becoming in this digital age, as you're bringing in tens of thousands of attributes even about a customer and a supplier, MDM being part of that process that can grow, and at the same time, those small collection of attributes important as a kernel inside of this information, it's that kernel that provides the connection, the missing link, if you will, across all of these. And absolutely, it's a journey that MDM can fuel. >> We think that's crucially important. So for example, what we like to say is we can demarcate the industry. We think we're in the middle of a demarcation point, I guess I should say. Where for the first 50 years we had known process, unknown technology. Now we're looking at known technology generally speaking, but extremely unknown process. Let me explain what I mean by that. We used to have very stylized, as you said, structured data. Accounting is a stylized data form, slow moving changes etc. And that's what kind of MDM was originally built for, to capture that system of record for those things. Now we're talking about trying to create digital twins of real world things that behave inconsistently, that behave unpredictably, especially human beings. And now we're trying to capture more data about them, and bring them in to the system. Highly unstructured, highly uncertain, learning and training. So, help us connect this notion of machine learning, artificial intelligence back to MDM, and how do you see MDM evolving to be able to take this massive, new and uncertain types of data, but turn it into assets very quickly. >> Absolutely. It's a crucial part of what MDM is all about today and going forward into the future. It is the combination of both the metadata understanding about what it is that these data sets are going to be about, and then applying artificial intelligence through machine learning on top of it, so that... MDM was always about well-curated data. How can you curate data by human curation, how is that possible when you've got these real time transactions coming in at such high speed and such high volume? This is where artificial intelligence can detect those streams, be able to infer the relationships across these different streams, and then be able to allow for that kind of relationship exploration and persistence, which is key to all of this. Completely new algorithms that are being built now, it augments... >> Does it enhance master data, or extracts it away? What's the impact... like ClAIRE, for instance. What's the impact to MDM? More relevant, less relevant? >> Even more relevant, and three key areas of relevance. Number one is about automating the initial putting together about MDM, and then also automating the ongoing maintenance. Reacting to changes, both within the organization and outside the organization, and being able to learn from previous such interactions and making MDM self-configuring. The second part of it is stewardship. If you think about MDM, in the past you always had stewards, a small number of stewards in an organization who would go out and curate this data. We now have tens of thousands of businesses across the organization saying, "I want to interact with this master data, I have a role to play here." For those business users now, you have tens of thousands of them, and then thousands and thousands of attributes. Machine learning is the only way that you can stop this data explosion from causing a human explosion in terms of how do you manage this. >> John: Yeah, a meltdown. >> Yeah, a meltdown. MDM both is going to be improved through these technologies, but MDM also has to capture these crucial new sources of data and represent them to the business. >> New metadata, right? >> Yeah, all these artificial intelligence systems and machine learning stuff is going to be generating data that has to be captured somehow, and MDM's a crucial part of that. >> Exactly, right. >> So let me ask you a question. >> If we can boil this down really simply... >> John: He's excited about MDM. >> Look, I'm excited about data, this is so... If we kind of think about this, we had an accounting system, well let me step back. In the world where we were talking about hard assets, we had an accounting system that had a fixed asset module. So we put all our assets in there, we put depreciation schedules on it, we said, "Okay, who's got what? Who owns it, who owns the other things?" Is MDM really become the data asset system within the business? Is that too far a leap for you? >> I don't think so. I mean, if you think about, if master data was all about making sure that the business critical data, everything that the organization runs on, the business is running on, and now if you think of that, that's the data that's going to fuel, um, enable this digital disruption that these organizations want to do with that data, MDM's at the heart of that. And finally, the last piece I think, your point about the artificial intelligence, the third part of where MDM increases its relevance is, you have the insight now. The data is being put together, we've curated that data, we've discovered those relationships through machine learning. What next? What's next is really about not just putting that data in the hands of a user or inside of a consuming application, but instead, recommending what that application or user needs to do with that data. Predict what the next product is that a customer is going to buy, and make that next best offer recommendation to a system or a user. >> Suresh, you're the GM now, you've got the view of the landscape, you've got a business to run. Charge customers for the product, subscription, cloud, on-premise license, volving. You've got a new CMO. You've got to now snap into the storyline. What's your role in the storyline? Obviously, the story's got to be coherent around one big message and there's got to be the new logo we see behind here. What's your contribution to the story, and how are you guys keeping in cadence with the new marketing mission? >> This has been a very closely run project, this entire re-branding. It's not just a new logo and a new font for the company's name. This has been a process that began many, many months ago. It started from a look at what the direction of our products are across MDM. We worked very closely with Sally and her team to... >> John: So You've been involved. >> Absolutely, yes. >> The board certainly has. >> Both board members said they were actively involved as well. >> Yeah, this has been a... >> What do you think about it, are you excited? >> It's fantastic. >> It think it's one of those once-in-a-generation opportunities that we get where we've got such a broad breadth of capabilities across the company, and now to be able to tell that story in a way that we've never been able to before. >> It's going to help pull you into the wind that's blowing at your back. You guys have great momentum on the product site, congratulations. Now you got the... the brand is going to be building. >> Fantastic, yes. >> Okay, so what's the final question? Outlook for next year? How's the business going, you excited by things? >> Very much so. MDM has been across the board for Informatica, and I'm sure you've seen here at the conference, the interest in MDM, the success stories with MDM, large organizations like Coca-Cola and GE redoing the way they do business all powered through MDM. MDM has never been more relevant than it is now. >> And the data tsunami is here and coming and not stopping, the waves are hitting. IoT. Gene learning. >> Suresh: Right. >> Batching. >> Batching, absolutely. >> With enable frederated MDM, we'll be able to do this on a global scale, and master class... >> We'll have to have you come into our studio and do an MDM session. You guys are like, this is a great topic. Suresh, thank you so much for coming on theCUBE, really appreciate it. General Manager of the MDM Business for Informatica Master Data Management. Was once a cottage industry, now full blown, part of the data fabric at Informatica. Thanks so much for sharing on theCUBE. We're bringing you all the master CUBE interviews here in San Francisco for theCUBE's coverage of Informatica World. Back after this short break, stay with us. (techno music)

>> Narrator: Live from San Francisco it's The Cube covering Informatica World 2017, brought to you by Informatica. >> Okay, welcome back everyone we're here live in San Francisco for the Cube's exclusive coverage of Informatica World 2017. I'm John Furrier of SiliconAngle Media. My cohost, Peter Burris, head of research at SiliconAngle Media as well as the general manager of Wikibon.com, Wikibon research, check it out. Some great research there on IoT, big data, and certainly cloud computing. Our next guest is Graeme Thompson, Executive Vice President and Chief Information Officer for Informatica, great to see you, welcome back to the Cube. >> Nice to see you, John. >> Conference here, lot of customers, you've got an executive summit, dinner last night, you're kind of like the sounding board, they go to you for the checkpoint, hey, does this story jive, what's going on internally, 'cause you're living through a transformation as well at Informatica. Your customers are going through a transformation as well. We're at this tipping point. What's your take so far of the conference, and is that still the case? Anything you'd like to share on that would be great. >> Yeah, I mean we're proud to have some of the world's best companies using our products to do meaningful and important things. And the scale that some of these companies are doing it at is just staggering. I met with someone last night at dinner and, at Allegis, the talent management organization, and they process and keep up to date 55 million resumes every day. And they extract the metadata from those resumes to match the right candidate to the right job. And you know, that's interesting for them as a company but the societal impact of that is significant. Imagine, I mean we're all starved for talent, and you're matching the right talent with the right opportunity more often than not, using the intelligence of the data, it's pretty interesting. And then of course, I know you had Andrew McIntyre from the Cubs on yesterday, I mean how can you not love that story of how an organization as great and renown as the Cubs is using data to transform it's business operation. It's really amazing. >> We had Bruce Chizen on who's Executive Chairman of the Board of Informatica, was on the board at Oracle, but Peter asked him an interesting question that I'll ask you. What's your definition of strategic data management? >> That's a good one, so the way I define it is, if the basis of your competition is on digital assets compared to physical assets. So we're no longer dealing with plant or machinery or even capital, it's digital assets. If that is the basis of your competition, then the data that you rely on is the very foundation of that. And then it becomes strategic just like money is strategic. And the access to talent is strategic. The ability to leverage the data within your company, about your company, is strategic, and you have to be able to do it on-prem, you have to be able to do it on the cloud, you have to be able to do it in the real world where most of us live, which is in both worlds. And that to me, that's what makes it strategic. >> But let me build on that Graeme, 'cause in many respects the whole concept of digital transformation is, oh let me step back. One of the premises of business is to try to reduce what's known in financial or economic worlds as an asset specificity. So traditionally we've looked at assets and said, this asset's going to be applied to that use, and this asset's going to be applied to that use, and if it's the use isn't needed or it's not being applied, you lose the value of the asset. One of the basic premises of digital business and business generally is how to we reduce asset specificity, and data let's us do that by turning an aircraft engine into a service, we have transformed the role that that asset plays in our customer's business. So you're absolutely right, it's the ratio of physical to digital assets, but all businesses have to find ways to reduce their asset specificity by adding digital on top of it so they can appropriate that asset to a lot of new purposes. Do you agree with that? >> Absolutely, so take, so I know you talked to Sally about the data leak. So take a user case like customer support. Who in a software company knows more about the customer, what product their running, what version of product their running, what they're using it for because of the connectors they have. Nobody in the company knows more about that than the customer support organization. But that asset, the most profitable use of that information, may be in marketing, because then we can help our customers adopt something more quickly, we can help them get value from it more quickly. And it helps us because it helps us focus our R&D effort where the customers are really using the product instead of having to guess. So I think you're spot on, if you can remove the constraint on the asset to be for who paid for it, for one particular purpose and make it available to the entire enterprise and outside the enterprise, then you really start to see the value. >> The thing that you mentioned about digital assets Peter, and the Wikibon team talk about this all the time in their research, digital assets, is the data. Whether it's content or whatever. Certainly we're in the content business, but... >> Peter: Well digital assets are data. >> Are data, exactly, and whether it's content or whatever aspect it is. So I've got to ask you... >> Software, software is a digital asset. >> Data is at the center of it all. So I've got to ask you, there's been a lot of artificial intelligence watching going on in the industry. I call it augmented intelligence because it's really not yet artificial by the strictest, purest definition, but machine learning is very relevant. We talked about IoT when you were last in our studio. How is it impacting your business and customer's business? Because that's the real proof in the pudding, if you will. And customers are trying to sift through the BS that they're hearing from other folks. I'm not saying that you guys are saying BS, but what's the acid test? How do you differentiate between smokescreen and real deal? >> I think it comes down to, like any other technology investment, is what is the business outcome that it generated? So if you're trying to... So humans make mistakes, if you're trying to eliminate human error from a process, a machine can execute that process more repeatably and more accurately than a human. It's not about reducing cost, that's only semi-interesting. It's about enabling outcomes that weren't possible before. So you think about healthcare industry. Everyone talks about self-driving cars and how safer it'll be if the cars aren't dependent on a human, but one thing I read recently is we kill more people in the US by prescribing the wrong drug or the wrong dosage than we do on the roads. So humans work hard, but they make mistakes. If we can have the machine do that job because a human can tell it how to do the job and it can learn over time, then you can eliminate that error. And we're able to do things that we can only imagine. >> Machines rarely get tired, they rarely lose attention, blah blah blah blah blah, and it's all those things, and that's where the augmentation is. And there will be the other forms of artificial intelligence, the algorithms have been around for a long time. The hardware now can support it, and the data is being generated to apply it. >> The data's available and the cost of compute is approaching zero. So we're able to do things that the government could only do before. >> Graeme, I want to get your thoughts on data integration. Certainly we saw yesterday the news with Google Spanner. You guys were one of three companies that was early on, before they announced their general release of Spanner Worldwide, the attributed database, horizontally scaled database. Big deal, but you guys were also on the front end of that as it says in their blog post, and you guys are really strong at data integration. What are some of the challenges that the customers face with integration? What are the key things? Because that seems to be, whether you go multi-cloud or hybrid-cloud today, which is a gateway to multi-cloud, which is happening pretty fast, data integration is pretty important. >> Yes, so as a CIO this is something that is a very hot topic for me, and it's not a new hot topic, it was a hot topic 15 years ago when we went nuts and deployed all these client server applications because they were cheap and easy. And then you had to think about, oh these different disconnected applications don't serve an end-to-end process anymore, now we have to stitch them all together. That was hard, but it was all on-prem and you had access to it all. >> Peter: It was all programed. >> Right, whereas now, like you said you've got Salesforce, you've got Workday, you've got Great People, you've got your on-prem stuff, you've got applications that you're hosting on someone's PAS cloud and the IAS cloud and the SAS cloud, but to execute an end-to-end business process to generate an outcome you have to tie it all together. So instead of thinking about... >> John: And it's not on-prem so you can't touch it, and it's not on, you don't have it. >> Right so you can't hand code that, you could, but I would argue that that would be an unintelligent way to do it, which is where Microservices API has come in. So you can leverage the R&D efforts that the great software vendors like Salesforce create for us. And then you use Microservices to plug into that instead of having an army of people hand-coding interfaces, which is what we used to do 15 years ago. >> That's the human error point. I mean, it could be spaghetti code, all kinds of errors could happen. >> But also the maintenance of that is just virtually impossible given the speed and the fact that human beings are now thinking about new ways of doing things. You just can't keep up with that. >> I mean the coding thing's a big deal. We used to call it, back in the day, spaghetti code cause it's like all this integrated purpose-built coding for one purpose to glue it together. >> Right and then you change one data element and you have to rewrite or retest the whole thing. >> John: A guy leaves or a girl leaves, it's a nightmare, right? With APIs and Microservices you're decoupling that. That's kind of what I think you're getting at, right? >> Exactly, and that's what the whole iPass space is about. You can decouple the user experience from the data and just have, what does a user have to do, and then Microservices and APIs will take care of the work behind the scenes between the applications and that really lets... There's this concept of a citizen integrator. So 15 years ago, it was kind of a modern thought to have business people write reports. I think it won't be long before we'll be able to give the business teams the ability to do integration between applications without depending on me. >> I was talking with a young developer the other day and I'm like, yeah you know your coding is like me doing PowerPoints. They're like, what do you mean, it's so easy. No, it's not that easy. >> Well we've been building macros, good or bad, inside for example things like Excel for a long time and one of the primary drivers, in fact of a lot of the BI stuff, was citizen coders building macros and said I need the data to make my little macro run. Now I don't want to say that that is... That's not what we're talking about, we're talking about something that's considerably more robust where we can be very very creative in thinking about how we might use the data. And then being able to discover it and find it and very quickly and with a low-code orientation being able to make the actual application happen that has consequential impact in the marketplace. So Graeme, you're in a company that's trying to help customers move through some of these transitions. You're in a crucial role because we know where the data is, we know how to integrate it. >> Graeme: You did? >> Well we're discovering where the data is, we have tools that's going to help us, we're learning how to integrate it. But one of the big challenges is to get the business to adopt new orientations to the role that data's going to play. That to me is one of the key roles of the CIO, having worked with a lot of CIOs over the years. For a very very simple example, agile development does not line up with annual budget finance. How are you with Informatica helping to acculturate executive teams to think through new processes, new approaches to doing these things so that the business is better able to use the data so that consequential action happens as these concepts of these great insights that you're generating? >> So the whole change in management effort is a huge and complex thing to overcome. But I have a personal passion about making sure that you always remind people why they're doing it. Too often as product people or technologists, we get into the how and the what and we forget the why. And as soon as it gets difficult people abandon because it starts to get too hard, it starts to get painful, and if they've lost sight of the big why they're not going to role their sleeves up and gut it out and get through the process. So that's the first thing you have to do is remind them that the prize at the end is worth the pain. And it will be painful because no longer are you optimizing just your function. You have to think about what happens upstream from you, what happens downstream from you, and try and optimize things at the enterprise level. And that's not how most people were brought up. It's not how their measured, it's not how their compensated, but that's what's really required if you're going to make that transformation I think end-to-end. >> But it's also, even our language, we talk about innovation in this industry as though it was synonymous with just creating something new. Certainly our research very strongly shows that there's a difference between inventing something which is an engineering act and innovating around something which is a social act. Exactly what you just said. How do we get people to adopt things and change behaviors and fully utilize something and embed it within their practices so that we get derivative innovation and all of the other stuff that we're looking for? >> Yeah there's no easy recipe. People are different so people require a different story in order to have them buy in. Some people are loss-framed people, where you got to explain here's what's going to be bad if you don't do this. Other people are gain-framed people where you can say if we can accomplish this, we'll be able to do these great things. And it would be great if everyone was the same and one story worked for everyone, but it doesn't. So it's almost a feet on the street. Go talk to people and just keep reminding everyone why you're doing this and why it's going to be worth it. >> Peter: A little bit of behavioral economics there. >> John: Graeme I want to ask you one final question. You mention client server and how it was easy on-prem in the old days, get your arms around things, which is the IT practice, you know? That's the way it was done. In the cloud, a little bit more complex. But to take that a little step further, I want to get your thoughts on something. You lived through the world of server sprawl. More servers, more glue, you get your arms around it but then it got bloated, IT got bloated. And that's one of the catalysts for going to the cloud is efficiencies, bottom-line costs. But now, top line revenue now is a mandate. So now we have SAS sprawl. So with APIs, a little bit more security concern, but your thoughts on the now we have a SASification happening or API economy. So you have a lot more APIs, there's Microservices coming on the scene, it's emerging very quickly, still emergent. Embryonic some will say, not so, but I think it's embryonic still. Okay server sprawl, client server, VM sprawl, now you got SAS sprawl. Your thoughts on this dynamic and how a CIO tackles that? >> Yes, so it's the modern equivalent of your legacy technical debt. So it's a modern mess instead of an old mess, but it's the same problem. You know, you have to stitch these applications together and it's made worse by the ease of consuming these SAS applications. So one business function can go off and buy an application that's just for them, and the adjacent business function goes off and buys another application that's just for them. And before you know where you are, you're single sign-on page has three pages because you've got so many applications that you're using to run your business. So I think we have to be more thoughtful and not make the same mistake that we made after 2000 when we went nuts on all these client server applications and make sure that we're thinking about the end-to-end business outcome. >> John: So the unification layer is what, Identity, is it the data? I mean how do you think about that just conceptually? >> Well I think you still need a sensible portfolio of applications. I don't advocate that you just go buy every great application that's out there. If your business doesn't compete based on the capability that that application provides, you've got no business innovating. Just be as good as the next guy. But if you compete based on something, go pick the very best application you can but deploy it thoughtfully. Make sure it's integrated, make sure it serves the end-to-end... >> Well I'm also fascinated by the role that Clair might play here at going and looking at the metadata associated with some of these SAS applications to help us identify patterns and utilization. I think Clair and the thing that was announced here actually could have an impact in thinking about some of these things. >> The Clairvoyant app is a great one, Clair, I mean... She, he, it's vendor neutral, that's a whole different story, only kidding. Final thought Graeme on this show? Just color perspective, what's your thought so far just on the show vibe for the folks who aren't here, what's it like? >> So when you and I met a couple weeks ago we talked about the fact that I'd just joined the company just after last year's show. So I have nothing to compare it to, but the energy level is phenomenal. The feedback from the customer's I've talked to just reinforces that we have really really important customers and we're really important to them. You know, the customers are the ones driving this digital transformation and we're proud to be helping them. And every conversation I've had with customers has really reinforced that and it's great, I can't wait to get back to the office. >> And as we say the KPI, the metric of the transformation of the world is not quadrants or category winners, it's customer wins. >> Graeme: Absolutely. >> And I think that's a great point. Graeme Thompson, Executive Vice President and Chief Information Officer of Informatica sharing his insight. He is an integral part of their transformation as well as his customers. Informatica World coverage with the Cube continues. I'm John Furrier with Peter Burris with Wikimon.com. We'll be back with more, stay with us after this short break. (electronic music)

>> Narrator: Live, from San Francisco, it's the Cube, covering Informatica World 2017. Brought to you by Informatica. (techno music) >> Hey, welcome back, everyone. Live here in San Francisco, this is the Cube's exclusive coverage of Informatica World 2017, our third year covering Informatica, and more to come. I'm John Furrier with Silicon Angle, the Cube. My co-host, Peter Burris, Head of Research for Silicon Angle Media, as well as General Manager of Wikibon.com, check out the great research at Wikibon. Some great stuff there on IOT, cloud ping data, great stuff. Of course, go to SiliconAngle.com for all the coverage YouTube.com/SiliconAngle for all the Cube videos. Our next guest is Bruce Chizen, board member of a lot of private companies, also Special Advisor at Informatica. You're on the board of Informatica, no? >> Executive Chair. >> John: Executive Chair of Informatica. Not only as Special Advisor, Executive Chair. Welcome back, good to see you. >> Great to be here. >> You were on last year, great to have you back. What a popular video. Jerry Held was on yesterday. Let's get some Board insights, so first question, when are you going public? (laughing) >> Good one. >> John: Warmed you up, and then, no. I mean the performance is doing well. Give us a quick update. >> Company's doing well. Q4 was a good quarter, Q1 was a good quarter. I think we will be positioned to do something late 2018, early 2019. A lot depends on how the company continues to do. A lot depends on the market. The private equity investors are in no hurry. >> John: Yeah. >> But it's always nice to have that option. >> So it's one of the things we, yeah, great option. Doing well. We heard that also from some of the management. We got O'Neil coming on, we'll press him on some of the performance side, but always had good products out, we talked about it last year. But the industry's going through a massive transformation. You've seen many waves over the years. The waves are hitting. What's your perspective right now? I mean, it's a pretty big wave. You got to get the surfboard out there, there's a set coming in. What's the big wave right now? >> So, data is driving every transformation within every organization. Any company that is not using and taking advantage of data will be left behind. You look at how companies like Amazon and Google and now a lot of our customers like Schwab and Tesla and others, the way they're using data, that will allow them to continue to either be successful in the case of a Schwab, or be a disruptor, like somebody like Tesla. Fortunately for us at Informatica, we are helping to drive that digital transformation. >> One of the things that I always observe, younger than you are, I've only seen a few waves in my day, but in the waves that were the most impactful in terms of creating wealth, and opportunity, and innovation, has had a cool and relevant factor. Meaning, if you go back to the PC days, it was cool and relevant. If you go back to mini computer, cool and relevant. And it goes on and on and on. And certainly internet, cool and relevant. But now, the, you mention Tesla. I'm testing driving one on Friday. My kids are like "Don't buy the Audi, buy the Tesla." This is my kids. So it's a cooler, it's a spaceship, it's cooler than the other cars. >> Bruce: Or an iPhone on wheels. >> Peter: (laughs) Exactly. A computer on wheels. >> So cool and relevant, talk about what is the cool and relevant thing right now. You talk about user experience, that's one. Data's changing it. So how is data being the cool and relevant trend? Point to some things that... >> If you look at what's happening from the chip on up, everything, everything will be intelligent. And I hate to use the term "internet of things," but the reality is everything will have intelligence. And that intelligent information will be able to be taken advantage of because of the scale of the cloud. Which means that any company will be able to take information, data, analyze it on the cloud, and then use it to do something with. And it's happening now. Fortunately, Informatica sits right in the middle of that, because they're the ones who could rationalize that data on behalf of their customers. 'Cause there's going to be a lot of it and somebody needs to govern it, secure it, homogenize it. >> John: You consider them an enabling platform? >> Absolutely, absolutely. I was joking, we just went through a rebranding exercise. And it's kind of cute, new logo, and it's kind of bold and sleek and it shows we'll have a leader, but it's a logo. But there's really around the messaging, we are finally getting across that we are the ones unleashing the power of data. That's what Informatica does. We'd just never really told anybody about it. We're very product focused, not really helping customers understand how uniquely positioned the company was. >> And it's also, you guys have done some things. Let's just go back and look at going private. Brought a new management team, have product chops again, we've talked about that in previous years. Last year in particular. So, okay, you have the wind at your back. Now you got Sally as a CMO, now you got to start being a humble braggart about the cool stuff you're doing. So which is marketing, basically. >> That's correct. >> John: But now, it's digital. >> Yeah. >> So, what's the Board conversation like, you say "Go, go build the brand!" >> So first of all, being private is great. (laughing) Because we get to do things you couldn't do as a public company. We're, a lot of our customers what to buy the products and solutions via subscription, that has huge impact to the P&L, especially in the short term. Cash flow's fine. So the PE guys are going okay, it's great, because we'll come out of this as a better company, and our customers like it because that's the way they want to buy products. So, that helps a lot. The conversation at the Board level has been, "Wow, we're number one in every category in which "we participate in. "Everything from big data to cloud integration "to traditional on-premise, to real-time streaming, "and, and, and data security." >> You're only one of three vendors in the Google general availabilities banner which went out yesterday. We covered that on Silicon Angle. >> We're number one there, we had AWS speak at our conference, we had Azure speak at our conference. All of the cloud guys love Informatica because we are the ones who are uniquely positioned to deal with all this data on behalf of their customers. As a private company, we're able to take advantage of that, spend some extra money on marketing. You know a lot of our customers know about us, but a lot more should know about us. So, part of coming out, having a new logo, having a new digital campaign, changing the website, that costs money. But as a private company, we get to do that. Because the fruits of those efforts will end up occurring a couple of years down the road, which is fine. >> So let me see if I can weave those two thoughts together in what I thought was an interesting way. Given that increasingly a lot of data's going to be in the cloud, and that's where the longer analysis is going to be required, that means a lot of the tools are going to have to be in the cloud. Amazon Marketplace is going to be a place where a lot of tools are going to be chosen. People are going to go into the Amazon Marketplace and see a lot of different options, including some that are free. They may not work as well, but they're free. You guys, what happens with marketing, and what's happening with that kind of a trend, is you need to buy, as customers, to choose tools that are actually going to work to serve or to solve the problem, to do the work that you need them to perform. And so what Sally Jenkins, the CMO, has done, with this new branding, is introduce the process of how do you buy us more customers to choose the right tool to do the right job? Does that make sense to you? >> It makes absolute sense, free is good. But be careful what you ask for. Sometimes you get what you pay for. You're talking about enterprise data. You want it to be governed, you want it to be secure. You want it to be accurate. >> John: Now there's laws coming out where you have to do it. >> You look at GTB... >> Peter: GDBPR. >> GDBPR in Europe, the privacy issues. You look at what's happening with Facebook, or what was reported today with France and how they're not happy with Facebook's privacy behaviors. It's an issue. It's an issue for anybody who does business anywhere, especially if you're a global company and you do business in Europe. You have to worry about corporate governance. Data security, data governance, data security. That's Informatica. The other thing is, while there will be some customers who will say "I'm going to AWS," there will be more customers who will either say "I have some legacy "systems that I'm going to leave on-premise, "and new projects will be in the cloud." Or they're going to say "I'm moving everything to "the cloud, but I don't want to be held hostage "by one cloud provider." And they're going to go with Amazon and Azure and Google and maybe Oracle, and, and, and. And again, because Informatica is Swiss, we're able to provide them with a solution that allows them to accomplish their data needs. >> Well, congratulations on the performance, I want to get that out of the way. But I want to ask a specific question on the historical, holistic picture of Informatica. Going back, what were the key bets that you guys made? 'Cause you guys sit around, and you got the private equity now coming to the table, they have expectations, but at the end of the day you've got to build a business. What were the key bets that is yielding the fruit that we're seeing? >> The number one bet was that the company had great products and a great R&D organization. We believed that, and fortunately, we got it right. Because if you don't have great products and passionate R&D organizations around the world, you can't make up for that. It doesn't make a difference how much you spend on marketing. At least not in the business that we're in. So that was number one bet, and that proved to play out well. The second thing was, this was a company that had done so well for so long that they never needed to change their business processes to behave like a billion, two billion, three billion, four billion dollar company. Many of their business processes were like that of a 200 million dollar company. And that's easier to fix. So things around back end, IT, legal, finance, go-to-market, marketing, sales. >> John: Less of a risk from an investment standpoint. >> That's correct. So that's what we believed, we were right And where we've been spending most of our energy and effort is helping the company, through the new management team, improve their business processes and their go-to-market. >> So we had a critical analysis yesterday during our wrap up session, and one of the comments I made, I want to get your reaction to this, was although impressive, your number one and all these Gartner Magic Quadrant categories, but that's an old scoreboard. If we're really living in digital transformation, those shouldn't really be a tell sign for what the performance of the new KBIs or the new metrics are. And so we were pontificating and analyzing what that would be, still unknown, we're going to see it. But Peter had a good point, he said "At the end "of the day, customer wins." >> Yeah, that was my reaction. It's like at the end of the day, all that matters do the customers.... >> What's the scoreboard look for customer wins? I know you were at the executive summit they had yesterday at the Intercontinental right around the corner. I had a chance to meet some of them at that dinner, some conversation. But I want to get your perspective. What is the vibe of the customers, what are those customer wins, and how does that translate into future growth for Informatica? >> Any customer who is looking at data, data management, strategically, is going with Informatica. >> Mmm hmm. >> There are a number of competitors that we have who try to compete with Informatica at the product level, and they end up doing okay through pricing, through better sales tactics, but when we have the opportunity to speak to the Chief Data Officer, the CIO, the CEO, they go with Informatica. It's the reason why Tesla went with Informatica on their project where they're trying to tie together the auto business with the solar business. Because if they get to know both sets of customers and are able to sync that up, one plus one will be greater than two for them, and that's why they did that deal. Or it's why Amazon has chosen our MDM solution for their sales operations. So you look at leading companies who are able to look at the enterprise level, at the strategic level, they are going with Informatica. That's why we know we're winning. >> So Bruce, give us three sentences, what is strategic data management? >> Strategic data management is being able to take reams and reams of data from all different platforms, traditional legacy, big data, real-time solutions, and data from the cloud and be able to look at it intelligently. Use artificial intelligence and machine learning to be able to analyze that data in a more intelligent way, and then act on it. >> So two questions on that point, I was going to ask about the AI washing going on in the industry. Every event now is like, "Oh my god, AI, we've got AI," but that's not really AI. What is AI, we call it augmented intelligence because you're really augmenting with the data, but even Google IO's got a little neural net throwback to the 80s, but what's your thoughts on how customers should look through the lens of b.s. to say, "Wow, that's the real AI, or the real "augmented intelligence." >> Does it do anything? That's ultimately the question that a Chief Data Officer or CIO or CEO...is something changing because of the artificial intelligence being applied? In the case of Informatica, we announced an AI platform called Clair, "clairvoyant," so artificial intelligence. What is Clair? It allows you to develop solutions like our enterprise information catalog, where an organization has thousands and thousands of databases, it's able to look at the metadata within those databases and then over time keep disclosing more and more data appropriate to the information that you're looking for. So then, if I'm an analyst or a businessperson, a marketing person, a sales person, I can take action on the right set of data. That's true artificial intelligence. >> Bruce, I want to get to one final point as we are winding down here. Again, you've seen many waves. But I want to talk about the companies that are trying to get through the transition of this transformation, Informatica certainly cleared the runway, they've got some things to work on, certainly brand-building. I see that as their air cover in many rising tide will float a lot of boats in the ecosystem. But there are companies where they have been in the infrastructure business and the cloud is one big infrastructure, selling boxes and whatnot. Other companies have traditional software models, download, whatever you want to call it, on-prem licenses, not subscriptions. They're working hard. Your advice to them if you are on their Board, or as a friend, what do you say to them, what do they got to do to get through this? And how should customers look at who's winning and who's losing, in terms of progress? >> The world of enterprise computing is moving to the cloud. Legacy systems will remain for a while. They need to figure out how to take their legacy solutions and make them relevant to the world of cloud computing. And if they can't do that, they should sell their company or get out of business. (laughing) >> And certainly data is the oil, it's the gold, it's the lifeblood of an organization. >> Of any organization. Even at Informatica, internally, we're using our own intelligent data platform to do our own marketing. Sally Jenkins is working closely with our CIO Graeme Thompson on working on solutions where we could help better understand what our customers want and need, so we can provide them with the right solution, leveraging our intelligent data leg. >> Bruce, thanks for coming on the Cube. Really appreciate your insight. Again, you've seen a lot of waves, you've been in the industry a long time, you have great Board presence, as well as other companies. Thanks for sharing the insight, and the data here on the Cube. A lot of insights and analytics being extracted here and sharing it with you. Certainly we're not legacy, we don't need to sell our business, we're doing great. If you haven't, make the transition. Good advice, thanks so much. >> Bruce: Great to be here. >> Bruce Chizen inside the Cube here. I'm John Furrier with Peter Burris. Stay with us for more coverage after this short break. (techno music)

>> Narrator: Live from San Francisco, it's The Cube. Covering Informatica World 2017. Brought to you by Informatica. >> Okay, welcome back, everyone. We're live in San Francisco, this the Cube's exclusive coverage of Informatica World 2017. It's the Cube, our flagship program. We go out to the events and extract the signal from the noise. I'm John Furrier with SiliconANGLE on the Cube. My co-host Peter Burris, Head of Research for SiliconANGLE Media, as well as General Manager at Wikibon.com research. Our next guest is Sally Jenkins, who's the Executive Vice President and Chief Marketing Officer. New to Informatica, not new to the industry, but certainly put her mark on the show, with the new branding. Sally, welcome to the Cube. Great to have you. >> Thank you. >> John: I know you must be exhausted, all the work you've done. >> Thank you. We're running on adrenaline, I can tell you that. But it's all good. We feel really good about it. >> John: So this is our third year following Informatica. We know a lot of the folks from other companies, see some Symantec product guys now running the show at Informatica. Always had great product shops, but with this industry transformation with the cloud, just in the past three or four years, there's been a massive shift and wave. And the pecking order of winners is changing pretty quickly. Informatica went private, kind of like what Dell did, Dell Computer, now Dell Technologies, and re-tooled. Now, you're going to be doing the brand reboot, which we can see behind us. >> Sally: Right. >> You've done that in three months. Take us through that, because this is an interesting story. You're now going to bring the brand perspective to Informatica. What's the strategy? What's your plan? How did you get all this done in three months? >> Yes, no, it's been an incredible journey, but you know, I was just made this enormous offer as a marketer. You couldn't dream for a better challenge than what we had at Informatica. So when I came in, what I recognized is, looking all around and trying to understand our strengths and our weaknesses, and what were the opportunities. We have everything in place. So, as I mentioned in my keynote yesterday, our brand is having to catch up with the business. So the business is there, we've got great products. The leadership that we hold, with all of the Gartner Magic Quadrants, you know, leadership in the six categories that we say that matter, we have a tremendous backing to come out with a new story, and that's exactly what we needed to do. It wasn't just about the logo. In fact, the logo was the last thing that we looked at. It was about, what's our strategy? What's our vision, our mission? What's the story we want to tell with our customers? And we were hearing from our customers, as well, that they wanted us to change, because they're going through transformations. So that was kind of the backdrop for how we got started on this, and so we went right off the bat, trying to nail down our messaging, and reviewing that with customers and partners. I mean, our new partner community is a big part of this, so we did our due diligence that led up to this unveiling. >> We're always kind of complimentary of you guys. Some critical. We had some critical analysis yesterday in the wrap-up session. Minor relative to the big bets. These guys have product shops. They always have had good product shops, and with going private, they've done a lot of re-tooling, a lot of change in the past year. And they talk about that. I'm going to see... We had Amit on, we're going to have Neil on earlier, but I've got to ask you the question, as the new exec. What does the brand stand for? Because the products change, the customers, they have some legacy customers that are growing with them and transforming. What does the brand stand for, from your perspective. And what is that story? >> Well, the brand stands for unleashing the power of data. And I think, as you've probably heard throughout this conference, that our whole stance on this is understanding what the destructive power of data holds for you as a customer. Because, as our customers are transforming, we are also recognizing that we have to transform, too. And our customers are moving from on-prem to cloud. They want to use our products on subscription versus perpetual license. So we're going through this massive change right alongside our customers, and so our brand had to support that. And our brand was, quite frankly, left behind. And so that was the opportunity for us to think differently about, what is that story that's in support of what our customers want? >> The promises you want to make to customers. >> That's right. >> So next for you, you're going to take a vacation. >> (laughs) I get Friday off. (laughter) >> Work from home, basically. >> Then you're going to start applying yourself to the challenges of using data within marketing, to improve Informatica's performance to customers. >> Sally: Absolutely. >> Talk about the transformation that you think your function's going to go through, as you use Informatica to be a better Informatica. >> Yeah, that's a great question. In fact, I talked about this also in our keynote yesterday, because I was talking about a little bit outside-in, and then I flipped and said let's talk inside-out, and I was explaining how my job is to deliver the best customer experience to our customers and our partners. And in order to do that, I need to have those unique insights that I gather from all the data that I'm collecting on our customers and our partners, to make sure that they're getting the right information at the right time to make those right decisions. And so I'm using our own internal intelligent data lake to create what we call our marketing data lake, and that gives me-- First of all, it gives me the whole perspective of the customer and what they're doing and where they're coming from, so that then I can turn that around and make that a unique experience for our customers. So I shared that, because I wanted our customers to understand that I'm going through the same thing that they're going through. In fact, if you've seen some of the quotes that are hanging around here at Informatica World. Jewelry, TV, AWS, they're all talking about delivering the best customer experience for their customers. So, I feel like I'm going through this just as well as our customers are. >> So what's the marketing perspective? Because now you have to sell to the customers. You're listening, so digital's going to be a big part of it. We're in a digital transformation, so we're here at a physical event, we're broadcasting digitally live, and all these assets are flying around. There's a lot of data out there. (laughs) How are you harnessing that data? What's your vision on how you're going to bring Informatica to that digital role, for listening to the customers, engaging with them-- >> Sally: That's right, that's right. >> And creating a touchpoint, digitally. >> Well, and that's-- Digital is a big part of what I'm responsible for, and we oftentimes talk about what's the digital journey our customers go on? And that gets back to, I'm needing to understand where they're coming from, what device are they coming to me from? What kind of information do they want back from me to help them make the right decisions for their company? And quite frankly, bring ideas back to their C-Suite. So, that's all right in my wheelhouse, and that's actually what I'll be turning my attention to post-Informatica World, is really getting deep under, having a better understanding of what that buyer's journey looks like. And it's all digital. I mean, these days, everything we do in marketing starts with digital. >> John: And in some cases, the moment of truth to the beginning of a journey is all digital. >> Yeah. >> John: Analog is kind of-- Is self-service, if you will. >> Peter: Well, except for those customers, except for those customers that you currently have, who you're trying to expand and develop. >> Of course, yeah. >> And help them as well, obviously. But this is... One of the things I find especially interesting about marketing, and I want to test you on this, is that in many respects marketing has been under-appreciated, because the output of marketing has been very information oriented, and the value of the information that the marketing has generated. While we're now starting to recognize how unbelievably valuable it is, historically it's been under-appreciated. >> Sally: That's right, that's right. >> So how are you bringing the story, marrying the ability to tool things, but also to better define... What's the value of a brand? >> That's right. >> Peter: We have no idea. It's goodwill on a balance sheet. >> Yeah, yeah. Well, that's a great question. This is a testament to the belief that our board and our executive team has around the power of a brand. This is why they're investing. They realize that they've invested, and done, and delivered in every facet across Informatica, and the last place that they needed to invest in is in marketing, because they realize the power of the brand in that story. And look, everybody's talking about us. I mean, if you've talked to any of our customers here at Informatica World, they're like, this is unexpected. We haven't seen this from Informatica. They've been hungry for this from Informatica. And so we're really putting our money where our mouth is on the brand this year. So you'll see it all come together. And I have to say, as a marketer, I mean there's nothing more special than the company realizing that they need to get behind the brand. >> John: You've got a great mandate, and you've got a good product behind you. I think that's going to be impressive. The question I want to ask you is twofold. One is, with the rebranding experience, you mentioned you went through digital transformation, a lot of your customers are going through he same thing. What experiences did you learn from that? If you could share some insight, whether it's personal or business, anecdotally, or specifically, quantitatively, what you learned from the rebranding experience. And then, the second part of the question is the brand-building process, how do you envision that road map? >> So, it's interesting. So, I actually brought a best practice in order to get this done in three months, honestly. This is normally like a nine month process. I use this rubric where we start with understanding what's our overall vision and mission, and what's the market opportunity? So, enterprise cloud data management. We're the leaders in that. We've never said that. And so understanding each of the bits and pieces that make up the entire story, before you get to the brand identity, that's actually a best practice that we've employed now, here at Informatica. And that was something that was foreign, just because they hadn't taken the time to focus on that. So that was, not necessarily learning a best practice, but deploying a best practice here at Informatica. And now, we need to turn back inside and change the culture. So we just rolled this out with the Informatica employee base last week, and they're all excited. And I said okay, we'll tune in once we get past Informatica World. So now the employees are excited to understand, how can they help tell the message, get the story out there? How can we change the culture so they understand who we are? You know, we've had many messages in the marketplace, so there's a little bit of confusion. And now we have one story. And now we need... Our employees are our best salespeople, so we need to engage them, and arm them with a story. >> I can just see people watching this video. Give me the rubric, where do I find that rubric? >> Oh, it's posted. It's on our intranet, absolutely. >> John: Interesting, so it's on a public blog? >> It's on our intranet inside, yeah. >> John: Oh, intranet, so it's not for the general public. >> Yes, yeah. >> John: I'm sure they're dying to find out the secret rubric. >> It's a guide to help them under-- Because everyone says, oh what's your new logo? And I'm like, we have a lot to do before we talk about colors and all of that, and so we wanted to make sure our employees understood the messaging, and what was behind that, so that when we got to the logo, they could understand how everything was unfolding. >> John: So what's going to iterate? So, you know, we see this digital transformation, whether it's deploying cloud. You get some structure, a rubric as a guidepost to kind of get the hard work done, foundationally. But then iterating and being agile with the brand. Do you have a philosophy on what points of the brand you're going to be iterating on, and what are the key areas that you see some evolution on the brand side? >> Yeah, well it's definitely that reiteration of our leadership stance that we have on the marketplace. You know, we've been humble, and there's nothing wrong with humble, but we also can be proud, and we can be proud to be proud. >> John: Yeah. >> So you'll be seeing a lot more from us around our leadership that we have in the marketplace, and we're going to be taking that on the road. So what you see here this week at Informatica World, then we roll them out all around the rest of the world through our Informatica World Tours. So we'll package up the story, we'll package up the look and feel, and we'll take that out so that our customers around the world can experience what we're experiencing this week. >> Take us through... I always love to ask this question for new folks, and I did this with Jeremy Burton when he joined EMC, now he's CMO of the Dell Technologies. >> Mm-hmm. >> Because you're new. You see everything fresh, with the fresh eyes. And of course, you've got to come in a little skeptical. Wait a minute, is this going to be a good opportunity? So when you were assessing the jewels, if you will, inside Informatica, what are some of the things that jumped out at you, that you could share? What's the coolest thing you saw? What motivated you? What was the tipping point? Was there a moment when you go, okay, go the next level? >> Yeah. >> John: Was it just a sustained, hmm. Or was there one-- >> No, there were a couple of things. I mean, first and foremost, our leadership. I mean, you guys... There's no other company, I'm sure you can validate this. There's no other company who has leadership in six-- Not just in leader quadrant, but the leader, in the leadership quadrant, in six categories. That's unheard of, and it's something that we need to be proud of. We don't ever talk about that. So that was the first thing. I said okay, we'll check that box. That's really good. Second thing is this interest in investment in the brand. And I thought okay, I've heard that before, but let's see if we're serious about it. >> John: Test that. You had to test that. >> And I've tested it, I've proven it, we've delivered it, and everybody's proud. And so I think those two things combined, our leadership and the fact that we actually can get behind the story, and we have one story, that's the momentum we've needed. So, that's just validation itself. >> Jerry Held, who's a board member, was on yesterday, is very proud of the work you've done, and he's excited. So he's pumped up. You've got one board member on your side. >> Sally: Great, yeah. >> We'll get to see what Bruce thinks this afternoon. >> Board members, we've got our channel partners. I mean look, our channel, for us, is our mouthpiece. And we needed to provide them the story, too. So the channel's engaged, and more excited than ever. Our sales teams are engaged. I mean, they've needed this story. So, you know, it was just guide rails that we needed to bring to the company, and I think this just solidifies that. >> John: You have the wind at your back. Certainly we heard from the channel, sales are up. Certainly the product's doing good. Looking at over a billion dollars in revenue. Great pre-IPO. I mean it's pretty obvious-- >> Sally: Hottest pre-IPO out there. >> Okay, we're going to evaluate that, but we think it's pretty hot right now. Is it the hottest? Mm, I think so. But what are you worried about? Because with all that pressure, being aggressive on the marketing side, you've got to be... You have the wind at your back. What are you worried about, if anything? >> It all comes down to execution, right? So, we've done the heavy lifting to get us here, but as I've said to executive staff and the board, this is our starting line, it's not our finish line. And so the rest of this year, and of course going into 2018, it's all about execution. And I feel really good about that, because you can't execute without a great strategy, and we have a great strategy. And we have a great story to tell. >> And a great management team. I mentioned it earlier, and John and I talked about it last night on the wrap-up, Informatica has a track record of making promises, big promises, and at least recently, keeping them. >> Sally: That's right. >> So you have a track record of executing. Customers are able to bank in you. So going back to kind of why this might be a great opportunity is, from our perspective, you've got good products, you've got good management, you've got a good customer base, you've got a good financial position. Marketing can make a big difference. >> That's right. Now we have a good story, and we have a great brand, and we've got investment, so we'll be out there. I mean, this is our year. I hope you all see that this is our year. >> We'll be watching. You've got a lot of air cover coming in for the folks to try more business and customer satisfaction. >> Yeah. >> What are we going to be talking about next year? (laughs) >> Wait and see. Wait and see. There's more in store. >> Tell us about your first 100 days. (laughter) >> No, no, no, no, no. >> Oh, I rebranded the company. (laughs) We'll just leave it at that. >> Sally Jenkins, Executive Vice President, Chief Marketing Officer, changing the brand, building the brand for Informatica. Wind at her back. Congratulations, great to have you on the Cube. >> John: Thanks for supporting the Cube, being on the Cube. >> Thank you. Exclusive coverage here from Informatica World, I'm John Furrier with Peter Burris. Stay with us more after this short break. (electronic music)

[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)

>> Announcer: Live from San Francisco it's the CUBE. Covering Informatica World 2017. Brought to you by Informatica. >> Welcome back everyone. We are here live in San Francisco for Informatica World 2017 exclusive coverage from the CUBE. Third year covering the transformation of Informatica as a company. I'm John Furrier, Silicon Angle. My co-host this week is Peter Burris, General Manager of Wikibon.com and Head of Research for Silicon Angle Media. Our next guest is eight time CUBE alumni, Amit Walia Executive Vice President of Products at Informatica. Amit, great to see you. >> Good to be here. >> Thanks for spending the time to come on. Saw you had a nice dinner last night with all your top customers. Very happy customers. Welcome to the CUBE. >> Yes, thank you. We keep them happy. Eleventh year in a row we got number one in customer loyalty. We work hard for that. >> There's a lot of exciting things happening. I just want to jump into some of the products though because that's your wheelhouse. You guys have been an amazing product company. I've always been kind of bullish on you guys, very complimentary. The one thing that, when we've talked on FaceBook and also on the CUBE is that not everyone knows about Informatica. They know about the old Informatica. We had Jerry Held on yesterday talking about the transformation, how hybrid cloud's here to stay. You guys have made great strides on the product front, the platform front, decentralizing data with control. Now you got the new brand. What's going on, give us the update. You got to be pretty pumped now, you got a megaphone out there with the new CMO. >> Yeah, lots happening at that end. I'll go back and paint a picture about how we see where the industry is and then how we are basically transforming that. My fundamental belief is that we're going through this massive transformation. Pick any word, but underlying at the technology level, the systems of records, all the databases and all the apps are massively fragmenting. Cloud, on-premise, hundreds and hundreds of choices. Systems of engagement for customers are fragmenting, right. When I talk to customers, they're struggling to figure out what is the system of intelligence. What's the organizing principle? Take a great example, my customer data and what I know about you John, is available inside the system, within multiple databases, multiple apps, outside the systems, what you do on LinkedIn, FaceBook, Twitter, how do I get a handle of you to be able to effectively engage with you? That is a fundamental change that is happening in the industry is what is my organizing principle to have the system of intelligence? We've honed in at the metadata layer for that. We believe leave the data wherever it is because it's going to be in different places. Use your best of breed apps. Organize the metadata because the scale and scope of that, while small, power of that is very high. Yesterday in my keynote, I announced the launch of Claire, our AIML offering. The idea is that we are going to be the Google of the enterprise to bring the entire metadata together. When we apply machine learning to it, it's the same algorithms that LinkedIn applies, or FaceBook applies for photo tagging or relationships, or Amazon applies for recommendations. We're going to apply it for data and make that then be what I call organizing principle, the system of intelligence for an enterprise. That's the nutshell of what we're trying to do. >> Also this Jada 3.0 thing, I want to press you on this because this is really cool. You guys have increased the surface area of addressibility of data and we talked about that last year, making it horizontally scalable yet with all the goodness of the controls as we talked about in the past. Now you're bringing in access methods via machine learning and AI techniques to make it accessible. Think Alexa, right. People at home, "Hey give me a song." How are you guys using the algorithms because now algorithms have become a super important part of what to look at. FaceBook, you mentioned FaceBook and Google, they've been criticized for their algorithms suppressing quality data. News cycle, things pop up once they see some traction. How do you guys tweak and enable algorithms to surface the best data possible? >> The best way to describe is that our philosophy is different. Claire, our AI engine, our goal is to make sure we can surface all of the data to the customer, but in an organized fashion. We're not looking to say, filter something. The best example is that predictive maintenance. If I am BMW and I'm running a robotic driven shop floor, how do I know when something's about to go down? I have a lot of old, historical data on my shop floor, but real time streaming data's coming from the sensor of the robot. I want to marry the two together and then let the system tell me, boy I feel like in the next 30 minutes, something is about to happen. We are doing those kind of things, solving those problems so we're not looking to filter or suppress anything. Our goal is to make sure we can bring more and more and more data together and with the help of machine learning, Claire, make it easy for customers to make decisions. Intelligent decisions, smart decisions, easier versus hundreds of people having to guess or predict which ends up not being very smart. >> On the road map side, I want you to take a minute to explain it. It's a good laying out the value proposition there, but I want to tie the cloud together with this because Jerry Held said yesterday, hybrid cloud's going to be a very long journey because legacy doesn't go away. You guys have a great business on-prem that's been historical for you guys. As you guys have modernized, what is the connection on a product basis that's available today and that's being worked on on a road map basis that says, you can do all this stuff with the data, but it's going to be cloud enabled. How do you get that cloud, hybrid cloud connection so the customer doesn't feel pain in moving to the cloud? >> First of all, I can boldly say that we were probably the only software company in the industry that disrupted our own industry to go to the cloud. By the way, data integration which is our core model, 11 years ago we invested in the cloud. We didn't know where it will go and we announced that Informatica 11 years ago and today 11 years later, we are the number one market share leader in cloud integration, number one in Gartner Magic Quadrant, and our cloud platform today is transacting a trillion transactions a month. In some ways, we were disrupting ourselves as you speak. >> Yeah, I mean the Gartner thing, I always say this cause those are old metrics, but the new metric is customer traction. You guys were in the announcement with Google Spanner as they globally GA their spanner distributed database which is a horizontally scalable database. You have a relationship with Amazon, you're in Microsoft. What is the customer uptake and what are some use cases? Give us some specifics. >> Three specific use cases. The customer started a journey in cloud more connecting cloud applications. On SalesForce, connected with World Gate, connected to SAP, so on and so forth. Simple application integration, all API management. Where data gravity is moving to cloud, where fundamental workloads are going and we see more and more traction is taking analytics to the cloud. I'm moving my workload to Redshift or I'm moving to an Azure data warehouse. That's where, by the way between January and May, we have moved half a trillion data objects to cloud data warehouses. Half a trillion. Clearly in that context we work with AWS. Three years ago, we started with them. Azure -- >> Just to put an exclamation point on that, in January it was a billion so between January and now, it's up to a trillion. Huge. That's a hockey stick. >> Kale is a hockey stick over there because so much more is being created outside the enterprise and customers don't want to bring it on-premise. They say look I just want to put it in Redshift or Azure database and I want to process there and over time, what they want, more to your point is connect me to my on-premise data warehouse too. Let's say I've done some analytics here, connect the relevant analytics and move it to, let's say my on-premise data warehouse and over a period of time as I get comfortable with this hybrid, I may take this workload and 100% flip over to the cloud too. They want this bi-directional journey. That's what's really enabling customers. >> It's always kind of hard to cobble together things that customers language that they're used to speaking in, to new concepts. It seems to me that data integration is your business of business. >> That's the foundation. We discovered data integration is the foundational layer and everything else we do is what I call more value added data management capabilities. Like MDM. Data integration allows you to connect, bring data together, MDM is a value added data management solution to say now I can get a 360 degree view of my customer like Nordstrom is using us for. Or a 360 degree view of my products, or a 360 degree view of my suppliers to make more business decisions. >> John: So integration is table stakes from your standpoint? Foundational. >> It's foundational. >> John: Foundational. Okay, better word. >> In that context, we operate like the Switzerland in the world of data. Whether it's Amazon, Google, Azure, tomorrow Oracle, SAP, we connect to the whole world. >> Amit, you have a vision of where this is all going to go. It's one thing to say, we've got our product set and we're moving it to a new technology base, which is good. That'll improve productivity. This whole concept of data management is bigger than just moving existing tooling, existing practices to a new set of platforms, no matter how much more productivity you might get out of those new platforms. It means something more. It means the way your business operates differently, business thinks differently, it means different ways of institutionalizing work. Give us the vision that you're laying out to your product team about how, yes we're re-platforming, we're introducing these new development technologies and all these other things, but here's where we're going. Here's the role we want to have in business. What is the role that Informatica wants to have in business? >> Our vision is to be what I call the system of intelligence for our customers because the organizing layer for that is data. When we say data management, data management's a very broad word you could argue. Our goal is that we want to organize the enterprises data. The vision that Google has for the internet, organize the customer's data whether it's inside their four walls or outside, in the context of the business processes. I'll translate that for you in two ways. We used to optimize for the IT technical user. A couple of years ago we made a big pivot to put an AND to it. We are also optimizing it for the business user because data now is such a powerful asset that business users want direct access to it. One of the things you would see from us in the last three or four years is we have been putting out a lot of out of the box data solutions. Intelligent Data Lake is a great example of that. We are giving IT full control of it, but we have a bi-modal experience where a business user can self service analytics. I just want to walk in as a marketing analyst and understand what was my lead to revenue conversion. I don't care about all the underlying infrastructure. I don't (mumble), but I just want to do my job. IT also wants to make sure as business users are accessing it, there's governance, security, compliance issues. We're marrying the two together. That's a very high bar for ourselves. >> Let me see if I can follow up on that because I want to make sure that at least I understand it. When you say you want to be the Google for enterprises data, there's actually a couple subtle things in there. First off, number one is that Google is looking at mainly public data and you want to look at public and an enterprises private data. As you said, that requires a whole level of functionality >> Amit: Totally right. >> That Google doesn't worry about like privacy, like ownership, like management and control. Secondly, increasingly the enterprise concept, especially when it comes to data is being able to get access to any data, anywhere. It's not organize the internet. It's not organize the enterprises data, it's organize all data for that enterprise. >> For the enterprise. >> Is that right? >> Exactly. We don't own the data. The enterprise owns the data. Big difference for us. >> The enterprise is also going to go out to all those sources that Google's looking at - >> Two big differences, the data within the enterprise and outside the enterprise for the enterprise, and we don't own the data, we want to bring it together for the enterprise to consume and operate and execute a lot more easy and efficiently. >> We're not talking about just small corners of data. >> No, not at all. >> We're talking about the enterprise, all data that's possible -- >> We are going outside the world, we're looking at unstructured data because, for example when you are, let's say on Twitter. Today we're going to be Tweeting, that's unstructured data, but it's about you and me. Today if Nordstrom wants to figure out something, what John likes, what John thinks, they want that, they want to. We are bringing that together within the MDM to say, oh you know what John bought for you, here's what John is saying on FaceBook or here's what John's saying on Twitter. Marry the two together and you understand John a whole lot better. That's what we want to do. >> And make it addressable and make it available to not only databases and systems, but developers. >> Amit: Oh absolutely! >> When I asked the question about data management, kind of the vision of data management, in many respects, it's the enterprises access to data that's relevant to it, number one. The ability from a metadata standpoint to know where it is and have the properties of ownership and privacy and rights and privileges and identities, and number two, the ability to move it around according to, as you noted, the integration laws that the -- >> That's exactly right. Because we've been operating for the enterprise for the last 25 years, we understand what they need. What regulations, what security concerns, what governance and compliance issues. If I had to summarize that context, look, we want to organize the enterprises data whether it's inside the four walls or outside for them, at their level of scale and security and governance and then with the help of Claire, democratize that for any user to truly use it. >> Democratization's a big angle and I want to ask you that because as much as you see the future, and I think you do, we've been talking to you many times here in they keynotes, customers aren't in the future. You've got to kind of come to earth and get to reality so I've got to ask you the question for customers, because they're trying to just deal, I'm trying to move to the cloud, I've got some VM Ware, I've got Amazon over here, I've got Azure, I haven't really baked out my full how I'm going to integrate cloud in my business model, what are some of the use cases that you guys are engaging customers with? You have good vision, products are solid. When you go out to the field, talk to customers, what are the use cases? What are you engaging them on? >> The journey to cloud is a big use case. In the journey to cloud, as I said there are two specific journeys customers are on. One is I'm deploying these thousands and thousands or hundreds and hundreds of enterprise SaaS apps. Help me weave them together in the context of data integration or MDM. Second is, the whole data gravity going to cloud. We talked about data warehousing analytics. Second is all of that. Move my data warehousing, but give me the flexibility in the hybrid. As I said, right, I want to bring outside data within Redshift, but connect it to my. Those are our two biggest use cases we see. Third we see that rides on both of them is self-service analytics. If I'm able to do both of these, then I'm much more easily able to do self-service analytics. Those three are the ones -- >> John: Are primary use cases right now? >> Those are the three prime use cases. Second one, on the other hand we see governance and compliance come up very big. Clearly customers are realizing that all of this re-architecture that's happening, you still need the same governance and compliance. If I am a large bank, if I'm a large insurance company, the laws didn't change for me. Cloud may have come, Hadoop may have come, the laws still stay the same so governance and compliance is a huge one for us. Look at GDPR. There is a deadline in May 2018 and customers are unprepared for that. That's the number two, I see governance a lot I see. >> In Europe it's even worse. You could get a top line, is that the top line, four percent of you -- >> Amit: Customers don't realize if you're a US company, even if you transact with one, single European entity, you are now -- >> The liability's there so let's just go to the root cause of what causes that liability potential, that's security. Quickly, security obviously's on the mind of you guys. You have an interesting security product. You guys are digging in the product, what's the product vision on security? >> That's the last one I was going to say. Four years ago, we saw that coming that security is an unsolved problem at the data layer and that's where the world is going to organize itself. We invested, and we have to invest ahead of the curve. We launched the product Secure@Source. Today, it's basically the industry's number one product. 11 awards at Odyssey. Raymond James is a customer, deployed within their four walls. Seven thousand databases go through Secure@Source to give them a full view of my sensitive data, who's accessing it, all of those risks that are now coming to the data layer. As data gets democratized, the security issues become bigger and broader. >> Final question for you. I want you to take a minute to end the segment because I want to give you the chance to say that because you know I'm a big fan of product work. Watching you guys go private and seeing the transition with the new management team, the product guys came in. I've said this on the CUBE many times, you've got the brand marketing going on now, new CMO, things going to be pumping out there. What is special about Informatica right now from a product standpoint? What makes you guys unique? You guys have done some good things, products coming down the pike. What are the guiding principles for you as the leader of the product team to continue to stay on that wave and innovate and make these products valuable to customers? >> I think the biggest change I would say is that we are innovating at the space of a start up. But we have the skill and breadth in the world of data management that is unparalleled to anyone. In this space, whether it's the traditional architecture, big data architecture, real-time streaming architecture or a cloud architecture or it's MDM and security and governance, nobody can do it at scale as us. By the way, we firmly believe in the best of breed concept. All of those capabilities are best of breed within their own market. Our belief is that look, we can solve a customers transition a lot more seamlessly and a lot more risk-free, and a lot more in the future proof way. Of course, we are modeling ourselves to move at the pace of a startup. I call ourselves the hottest pre-IPO -- >> John: I was just going to ask the revenue question. >> A billion dollar in revenue company, not billion dollar market cap company. >> John: You're doing over a billion in revenue? >> Doing over a billion in revenue. >> I'm going to add one more thing to that Amit. I'm not even going to test it. We are especially impressed that you have made very, very bold promises the past few years and you've executed on them. You're one of the few companies in this space in the whole data management, this emerging data management next generation world that has executed on the promises that it's made. Your promises make sense and all the things that you said are excellent. The promises make sense, but your execution makes is safe for customers. >> Well we had some critical analysis yesterday so we're not going to just all fawn all over you guys, there's some things to work on. The big bets are paying out. You guys made some great bets. The cloud bet was key. Congratulations. Amit, great to see you. Coming on the CUBE, thanks for spending the time. You got a keynote coming up this afternoon. Real quick, what's going to be the topic? >> Well I'm going to talk about how Claire will be able to solve a lot of future-looking problems. Today's keynote is all about the futures and what the vision of the future is. I'm going to showcase a few examples of what machine learning and AI can do to increase productivity and help ease the pain of our users and customers. >> Get that data integrated, democratize it and create freedom for data to fly around and get those apps addressing it. This is the CUBE, bringing you all the data here inside the CUBE, but soon we'll have an AI bot doing all the interviews in the future sometime. I'm John Furrier with Peter Burris. We'll do them today. Informatica day two exclusive coverage from the CUBE. We'll be back with more coverage after this short break. Stay with us.

>> Announcer: Live from San Francisco, It's The Cube. Covering Informatica World 2017 brought to you by Informatica. >> Hello everyone, welcome back to The Cube coverage, exclusive coverage of Informatica 2017, we are live in San Francisco breaking down all the action of Informatica's big conference Informatica World 2017, I'm John Furrier with Silicon Angle The Cube, my cohost Peter Burris, head of research and also general manager wikibon.com check it out, great research there, next guest is Richard Cramer, Chief Healthcare Strategist fpr Informatica, welcome to The Cube. >> Thank you John. >> Great to see you, we were just talking before we went live about you love data, you love customers, and healthcare is booming, certainly healthcare is one of those use cases, it's a vertical that everyone can relate to, one. Two, it's the most dynamic with data right now and internet of things connected sensors you know what a room looks like a zillion things connected, now you got wearables, still you got the data problem, it's never going away, certainly it exists there, but now it's changing, so break it down for us, what is the challenges and drivers right now in the healthcare industry relative to getting great software and great solutions to help patients. >> Well you're 100% right, one of the things that's exciting about healthcare is it matters to all of us. Every one of us is a patient, every one of us has a horror story of interacting with a healthcare system and so when we look at the opportunity for data, healthcare has historically not used data very well. We had the High-tech Act in 2009 that got electronic healthcare records in place, we're coming out of the backside of that, so arguably for the first time we finally have the deep rich clinical data that we've needed to do analytics with for the first time. We now have the technology that's coming around with what we call data 3.0 and big data processing power and then as you mentioned internet of things and all of the rich sources of new data that we can do discovery on and learn new things about how to treat patients better and then really the final component is we have the financial incentives are finally aligned. We used to in healthcare pay for piecework. The more you did, the more you got paid. And shockingly we were inefficient, we did too much. (laughs) And now we're changing to paying for value. And we can pay for value because we can finally measure quality and outcomes because we have the data. And so that's really the analytics opportunity that's so exciting in healthcare right now. >> What's interesting is that in this digital transformation, and business transformation and all the conversations we've had over the years on The Cube and look at all the top shows in the enterprise and emerging tech, you're seeing one pattern, we had the Chicago Cubs on yesterday talking baseball but whether it's sports, business, or healthcare or whatever vertical, there's kind of three things, and we'll take baseball, right? Fan experience, how to run the players and the team, and how to run the organization. Healthcare is the same thing, how to run an organization, how to take care of the players, the doctors and the practitioners, and then also the end user, the fan experience, the patient experience. So now you have, it used to be hey are we running our organization and the practitioners were part of that maybe subordinate to it, maybe they interacted with it, but now like a baseball team you have how do I run my organization, how do I make the players, the doctors and practitioners successful, and now the patients, the end users are now part of it as well. This is opening up massive innovation opportunities. What's your reaction to that and how should people think about the data in that context? >> So I think the first piece of what you said is very true, which is really for the first time, healthcare organizations are behaving like real businesses. When you start to get paid for results, you now care about a lot of things that you didn't care about before. Patient experience matters 'cause consumers have choice, those types of things, so all of those digital transformation examples from other industries are now relevant and front and center for healthcare organizations. Which is radically different and so that opportunity to use data and use it for a specific purpose is very valuable. I think the other thing that's important with digital transformation is historically healthcare is very local. It's regional, you go to the hospital that's closest to you. And digital disruption is all about removing geographic barriers. The goal in healthcare today is we're reducing cost, you want to push healthcare out of that high cost hospital into the most cost effective highest quality organization you can. That maybe a retail clinic in a shopping mall. And how do you do that? You do that with digital technology. Telehealth in the home. All of those types of things are traditional digital transformation types of capabilities that healthcare has not traditionally cared about. >> So optimizing a network effect if you will, we always hear in network, out of network as a term (laughs) >> Yep. >> My wife and I go oh it's in network, oh good, so out of network always kind of means spendy but now you're talking about a reconfiguration of making things much more efficient as piece parts. >> Well exactly right and the idea of the network, the network used to be drive everybody to the hospital, 'cause that's where we made our money. Well when you're getting paid for results, the hospital's a cost center, not a revenue center. You actually want to keep people out of the hospital. And as a consumer and as somebody who's paying for healthcare, that's actually a good thing. If I can avoid going to the hospital and get healthcare in a more convenient setting that I want to do at home or someplace closer to home and not be admitted to a hospital, hospitals are dangerous places. >> Peter, you've been doing, I've seen you and I comment on Facebook all the time, certainly the healthcare things sparks the conversation but big data can solve a lot of this stuff, I know you're doing a lot of thinking around this. >> Well so fascinating conversation, I'd say a couple things really quickly and then get your take on it. First off a lot of the evidence based management techniques we heard about yesterday originated in healthcare. Because of the >> You mean like data management and all that stuff? >> Peer review, how we handle clinical trials, the amount of data that's out there, so a lot of the principles about how data could be used in a management framework began in healthcare and they have kind of diffused the marketplace, but the data hasn't been there. Now there's some very powerfully aligned interests. Hospitals like their data, manufacturers of products like their data, doctors like their data, consumers don't know what to do with their data. They don't know what value the data is. So if we take a look at those interests, it's going to be hard, and there's a lot of standards, there's a lot of conventions, each of those groups have their so now the data's available, but the integration is going to be a major challenge. People are using HIPAA as an excuse not to do it, manufacturers and other folks are using other kinds of excuses not to facilitate the data because everybody wants control of the final money. So we've heard a lot at the conference about how, liberate the data, free it up, make it available to do more work, but the second step is integration. You have got the integration problem of all integration problems in data. >> Yes. >> Talk about how some of the healthcare leaders are starting to think about how they're going to break down some of these barriers and begin the process of integrating some of their data so they can in fact enact different types of behaviors. >> Yeah and great context for what's happening in healthcare with data. So if you think of five, six, seven years ago at Informatica, my role was to go and look at what other industries had done for traditional enterprise data warehousing and bring that knowledge back into healthcare and say healthcare you're ten years behind the rest of industry (laughs) here's how you should think about your data analytics. Well that's completely different now. The data challenge as you've outlined it are we've always had data complexity, we now have internet of things data like nobody's business and we also have this obligation to use the data far more effectively than we ever have before. Well one of the key parts of this is that the idea of centralizing and controlling data as a path value is no longer viable. We can argue whether it was ever successful, but it really is not even an option anymore when you look at the proliferation of data sources, the proliferation of data types, the complexity, we simply can't govern data to perfection before we get using (laughs) which is traditionally the healthcare approach. What we're really looking at now is this whole idea of big data analytics applied to all data and being able to do discovery that says we can make good decisions with data that may not be perfect and this is the big data, put it into a data lake, do some self service discovery, some self service data preparation, reduce the distance between the people who know what the data means and being able to get hands on and work with it so that you can iterate and you can discover. You cannot do that in an old fashioned EDW context where we have to extract, transform, load, govern to perfection, all the data before anybody ever gets to use it. >> John: That's why I'm excited about data in motion. >> Well even, yeah data, we'll get to that in a second because that's important, but even before we get there, John, I mean again, think about how powerful some of these industries are. Drug companies keep drug prices high in the U.S. because they have visibility into the data, the nature of the treatments, et cetera. One of the most interesting things, this is one I want to attest with you on. Is that doctors, where a lot of this evidence based management has started because of peer review, because of their science orientation, even though they get grooved into their own treatments, generally speaking our interest is in exploring new pathways to health and wellness. So is, do you have a very powerful user group that will adopt this ability to integrate data very quickly because they can get greater visibility into new tactics, new techniques, new healthcare regimes as well as new information about patients? Are doctors going to be crucial to this process in your opinion? >> Doctors are going to be crucial to the discussion, we had a healthcare breakfast with a speaker from Deloitte the other day who talked about using data with clinicians to have a data discussion. Not use data to tell them you're wrong or whatnot but actually to engage them in the discovery process of here's what the data shows about your practice. And you talk about the idea of data control, that's absolutely one of the biggest barriers. The technology does not solve data control. >> Right. >> In the old days, everybody admits we have silo data, we have HIPAA, it was so hard to break down those barriers and actually share data that nobody really addressed the fact that people didn't want to. Because they couldn't. Well now with the technology that's available it's >> What's possible, the art of possible. >> Yeah, now it's possible to actually get data from everywhere and do things with it quickly. We run into the fact that people have to explicitly say I don't want to share. >> But here's where that data movement issue becomes so important John and I think that this is a play for Informatica. Because metadata is going to be crucial to this process. Being, giving people who do have some understanding of data, clinicians, physicians, because of their background, because of the way that medicine is supposed to be run at that level, giving them visibility into the data that's available, that could inform their practices and their decisions is really crucial. >> Absolutely. One of, a good friend who's a clinician has been asking for years, he says if all you did was give me access to data about my patients so I could explore my own clinical practice, says I'm guaranteed I take care of diabetics the way I learned in medical school 25 years ago. There has been a lot of innovation in that and just having the perspective on my own practice patterns from my own data would change my behavior. And we, typically I haven't been able to do that. We can now. >> So I've got to ask you, so let's get down and dirty on Informatica, 'cause first of all I think instrumentation of everything now is a reality, I think people now are warming up to certainly in levels, super hot to like I realize it's a transformation area. What are you guys saying to customers? Because they're kind of drowning in the data, one. Two, they are maybe held back, 'cause of HIPAA and other things, now it's time to act, so the art of the possible things are now possible, damn I got to get a plan, so they're hustling around to put a plan together, architecture, plan, what do you guys pitch to customers? What is the value proposition that you go in, and take us through an example, a use case of a day in the life of your role with customers. >> So I have the best job in Informatica. I get to go out and meet with senior customer executive teams and talk about data, how they're going to use data, and how we can help them do it. So it's the best job in the company. But if you look at the typical pitch, we start out, we first we get them to agree with the principle, centralizing control is dead, being able to manage data as an enterprise asset in a decentralized fashion with customer self service is the future reality. And everybody universally says yep, we get it, we agree. >> John: Next. (laughs) Check. >> But then we talk about what does that actually mean? And it's amazing how at every step in my presentation, the 20 questions always are the same, it comes down to well how do we control that? How do we control that? >> Peter: How do we manage it? >> So you start with, you think of this idea that says hey, decentralized data, customer self service, you got to have a data catalog. Well enterprise information catalog is a perfect solution. If you don't know where your data assets are and who's using them, you cannot manage data as an asset >> And they're comfortable with that because that's the old mindset of the warehouse like that big fenced in organization, but now they say okay I can free it up >> Yes. >> And manage it with a catalog and get the control I need. >> That's right and so the first piece is the catalog, well then the minute you say to people the catalog is the way to get value from your data, there's somebody in every room that says ooh that value represents risk. You're letting people see data and make data easy to find, that can't possibly be good, it's risky. Well then we have secure at source was the opposite product from enterprise information catalog that says here's the risk profile of all those data sources for HIPAA and protected health information so we got a great answer to that question, and then you look and you say well how do I fundamentally work with data differently and that's the idea of a data lake. Rather than making data hard to get in so it's easy to query which is the traditional enterprise data warehouse, and even people who do enterprise data warehousing well, little secret is, takes too long, costs too much, and it's not agile. >> Yeah. >> We're not suggesting for a second that a centralized repository, a trustworthy data governed within an inch of it's life so that it can be used broadly throughout the organization without people hurting themselves is not good, it can't be the only place to work with data. Takes too long, costs too much, and it's not agile. What you want is the data lake that says put all the data that you care about in a place, big data, IOT data, data that you don't know what you're going to use, and apply effort at query time only to the data that you care about. >> And we're always talking about cleanliness and hygiene yesterday versus heart surgeon, different roles in an organization, the big fear that we hear from customers, we talk to on The Cube, I want to get your thoughts and then reaction of this is that my data lakes turn into a data swamp. Because it's just, I'm not using it, it's just sitting there, it gets stale, I'm not managing it properly, I'm not vectoring it into the right apps in real time, moving it around, your reaction to that objection. >> Early days of the data lake, absolutely data swamp because we didn't have the tools, people weren't using them correctly, so just because you put it in a data lake doesn't mean that it's ungoverned. It doesn't mean you don't want to put the catalog on it so you know what's there and how to use it. It doesn't mean you don't want to have end to end transparency and visibility from the data consumer to the data source because transparency is actually the first level of government. That's what provides confidence. It's not agreeing on a single version of the truth and making sure the data's right. It's just simply allowing the transparency and so when you have a data lake with a catalog, with intelligent data lake for self service data preparation, with the ability to see end to end what's happening with that data, I don't care that it's not been governed if I can inspect it easily and quickly to validate that your assumptions are reasonable, 'cause this is the biggest thing in healthcare. We can't handle the new data, the IOT data, and the scope of things we want to do that we haven't thought about the old way. >> Yeah we have limited time. >> One last question. Framingham Heart Study has shown us that healthcare data ages differently than most other data. How do we anticipate what data's going to be important today and what data's going to be important in the future? Given that we're talking about people and how they age over time. >> So the key thing with that and we talked about it earlier, you can't analyze data that you threw away. And so a big part of this is if the data might potentially be of interest, stage it, and don't put it in an archive, don't put it someplace in the database backup, it's got to be staged and accessible, which is the data lake. >> And ready. >> And ready, you've got to, and you can't have distance between it. Somebody can't have to go and request it. They need to be able to work on it. And that's the revolution that really is represented by data 3.0, we finally can afford to save data, huge amounts of data, that we don't know we care about. Because somebody may care about it in the future. >> Peter: That's right. >> Great Richard, great commentary, great insight, and appreciate you coming on The Cube and sharing what's update in the healthcare obviously super important again they're running like business, a lot of optimization, a lot of changes going on, you guys are doing some good work there, congratulations data 3.0 strategy. Hopefully that'll permeate down to the healthcare organizations and hopefully the user experience, me, the patient when I go in, I want to be in and out >> Peter: Wellness. >> Of the hospital and also preventative which I'm trying to do a good job on but too many Cube interviews keeping me busy, I'm going to have a heart attack on The Cube, no I'm only kidding (laughs) Great coverage here at Informatica World in San Francisco, I'm John Furrier, Peter Burris, more live coverage of day two at Informatica World, Cube, we'll be right back stay with us.

>> Announcer: Live from San Francisco it's the CUBE, covering Informatica World 2017 brought to you by Informatica. >> Welcome back everyone, we're here live in San Francisco for our wrap-up of day one, the CUBE's exclusive coverage of Informatica World 2017. So our flagship program, we go out to the events, and extract the signal and the noise. I'm John Furrier with SiliconANGLE, the CUBE. My co-host this week is Peter Burris, Head of Research at SiliconANGLE Media, also the General Manager of Wikibon.com. Go to Wikibon.com and check out all the great research, great stuff behind the paywall, subscription required but also some free content there as well and our special guest is Neil Raden, who's the new analyst on the Wikibon team. Welcome to the team. You're covering the value of data, and analytics industry veteran, great to have you on the team. Thanks for joining us on our wrap-up here. >> Thank you. >> Welcome Peter, look here, this is kind of a coming-out party for Informatica. We've been following them for multiple years. Some of their top exec has been CUBE alumni for many, many years. I think I admit Wallie's going to be on his eighth year, eighth time on the CUBE, but look behind as you see a new branding. Informatica has a new CMO, and she's got swagger and she's got brand impact. Informatica is now going to start bragging about their products. Although I have some critical analysis of Informatica we'll get to in a second but I've always said they've brought in a team of folks during the going private that have product chops, and they've had an install base, and their goal has been from the beginning let's go private close the curtain, and get stuff where you organize, and really work on the product and install base. Can they pivot? That was my question three years ago. Every year they keep on coming out with not a land grab but an incremental and moving the ball down the field to use your football analogy first and then do it again but starting to get into that horizontally scalable cloud model and with good cloud deals, looking poised, in my opinion, for being a data layer, potentially for making that data fabric on. So to me, I think that's the big story here. So far is some good news around the brand, product increases got AI, augmented intelligence with CLAIRE. Some interesting dynamics, which means the interface the data is changing, not only the underlying value of the data, which we want to get into but Informatica is trying to up level the interface. Your thoughts? >> So I think you're absolutely right, John. I think we've seen three things here. First off, Informatica has always had a pretty decent product kit, well embedded within some really first-rate customers. Number two, they've been talking about the need to accommodate some of the new trends around cloud, and how they're going to move in that direction. They've been talking about it. This is the first year we've really seen it. Number three, they even, when Informatica talks, people have historically not listened as much. Sally Jenkins, the new CMO has gotten an enormous amount of work done in a very, very short period of time. This is a bang so and it's manifesting itself in that people are buzzing about it. >> Yeah. >> It's even if Informatica has a lot to do to really be that enterprise cloud data management leader, a lot left to do but it all starts by presenting themselves in a coherent way. That's something that we're seeing for the first time. >> The value proposition has changed significantly. I was talking about the Amazon stock price. Since 2010, it's just been a skyrocket growth for Amazon across the board. Yeah, I got the retail but AWS certainly has been powering it. Having a good brand behind you is going to really energize the channel, ISV, software developers. Like I always joked about the old days, when I used to work at Hewlett-Packard, the joke was I used to call cold dead fish versus sushi. HP would be so accurate, so engineering-oriented, they would be so accurate around the products. They didn't really have a lot of marketing, and the joke was if they had sushi, they called it cold dead fish because that's what it is. Sushi sounds better but again back to marketing, they need to bring the brand out, and put a message around the shift to value. >> Well think about how important it's going to be to a company that increasingly acknowledges or acknowledges increasingly. Their customers are going to find it in something like the Amazon Marketplace or in Google, or in some other cloud environment. It means that they have to bias the customer to choose Informatica versus a range of tools that may not be as good but some of them are going to be open source to get people to bias at that moment, you got to get your brand out there. You have to get your identity out there. Informatica was not going to be a success when the customers making that decision as they're looking at that Amazon Marketplace just by word-of-mouth. They have to get their name out there. So this is big. The products are still good and making, and improving. Getting to the cloud is a big deal. Delivering on their promises, and now having a marketing platform that allows them to scream a little bit louder from the rafters, about who they are and what they want to be. A lot of it's coming again. >> Day two, we're going to have a lot. All the top execs on, they were in an off-site down the street right here at Intercontinental in San Francisco with Executive Customer Day, but we had SVP on for cloud business. We had the board member, Jerry Hill, who's five decades in the business. I mean he essentially laid it out. Hybrid cloud is here to stay, and it's not going to be an overnight success. It's going to be a transition, and that favors the legacy vendors, who are sharpening their saw, and getting their products in line. Of course we have the Chicago Cubs on, and we took the ring, almost put in my pocket in a very Putin-esque like style. We all know Robert Kraft waltz Super Bowl ring, to the biggest criminal in the world, Putin, but kind of a fun there. But the baseball team highlights the customer journeys. They have customers that love them and stay with them 'cause of the install base. >> Absolutely and Informatica is deeply embedded, and has been, Neil has been on the vanguard. Look, they got a lot of work to do but they've been on the vanguard of tying together the idea of data, data is an asset, tooling. So you can get more value out of the data through analytics. >> That's right, I'll tell you a little story. I mean, I brought Informatica in to one of my clients the first time in 1996. They were pretty much a brand new company. >> Peter: About a year after they started? >> Yeah and what motivated me to think about Informatica as opposed to any other way we were trying to get data into a data warehouse was that they understood metadata. They were the only company that had an active metadata repository. So this is their heritage. I know that Informatica claims they have, I don't know 10,000 customers. I think a significant number of those are not going to be interested in this whole thing. They don't have the budget for it. They don't have the time or the staff or anything but they've got the elite. When you look at the companies that are clients of Informatica, those are the people that would be interested in and spend time and money on this sort of thing. >> Well let me get you guys perspective as analyst because let's turn this into the analysis of what's happening here with Informatica, and compare that to what's happening in the industry. SAP Sapphire is happening right now in Orlando. We got CUBE coverage in our studio in Palo Alto. But Oracle, SAP, these are database guys. They have systems of record. IBM, Amazon is now a new player in that. They have to balance the install base, systems of record of their data. Now granted old techniques for walls, data warehouse, whatever you want to call. It was an old way. Now the new way's to empower developers to actually build and use that data. So the question is how do they get their product from old to new and modernize quickly, and highlight data as value because this is the thing that you guys are both researching heavily, is that data now is going to start to be evaluation discussion. Are we getting the data through the pipes, if you will, into the hands of the developers, into the apps, into the decision-making process in the value chains that are being reconstructed. This is a top conversation that not a lot of people are laying out there with best practices. Your thoughts? >> Well I think the first thing, then I'll start, like the first thing is that that's probably my biggest thing on Informatica here, is that they need to be more of a beacon about what is the new data management. It's more than just the combination of tools. It's more than just getting data out of applications, and getting data out of databases, and freeing it up so they can be applied. The notion of data management is evolving rapidly, and businesses are trying to as they try to use data as an asset is going to require some significant changes to how we think about-- >> Do you think they could put that stake in the ground right now and owned that right now? >> I think somebody has to. I think they need to take a crack at it. >> I think they're weak on the value. I think they're weak on, you know what happens, I always have this idea that you see their layer cakes, and the things that go from left to right but on the right-hand side of the diagram, there are no people right. What happens when you implement all this? How do people use this okay? That's true of everybody in this industry, not just Informatica. So that's one weakness. Last year when I was here, I thought they had a real weakness in governance but with the dike who acts on acquisitions, I think they made a giant step towards that. They've got a lot, they've got a lot of the piece, parts, and then putting them together but I don't think they're addressing what happens next. I call it the Jordan River problem. We wandered around for 40 years. We got to the Jordan River. We can't get across the damn river right. >> Is it a river or lake or an ocean? I mean it's a data river. It's something happening. It's a lake or something. >> I think that's where they are because it's a whole different discipline. >> But is that on Informatica? I mean they're now a smaller company or is that an industry issue? >> No, it's an industry issue but companies like Informatica, if they really want to be a leader as he flings his grad classes around, that's all passionate I have about this. If they want to be a leader or the leader, they have to put a stake in the ground don't they? >> I believe so. >> Okay so what about positives? Neil what's your thoughts on how are they well-positioned in your mind? >> Well, putting together all these different pieces so that they operate together is phenomenal. Moving to, I still don't understand how enterprise software companies move to a subscription model smoothly. That's got to be a real headache but they're moving to that. They've adopted the cloud. They still have the data integration. I mean that's their keystone. It works beautifully, it gets better every year, and that's what attracts people to them. So I think these are all good things. >> And the good news is they're private so they can do that subscription, kind of hide the ball a little bit then come out. But they're not doing bad. I mean they have a spring to their step. >> Here's, I think Neil's absolutely right. Here's what I would add to it. They're executing, they have demonstrated over the past couple of years, certainly that we've been here, and listening to them, they made promises, they've delivered. They've made new promises, they've delivered. Some of these promises have been complex. Some of them have been extremely hard. They've still delivered. That is a real important piece of the story because this notion of data management is changing. Developers are going to want to work with companies that have competent management, that deliver on the promises they're making and Informatica is proving that they're up to that progress. >> I think, I think-- >> Another thing John, they have brilliant people. Everybody I've met here from Informatica is really special. I mean you know maybe they kept the clunkers in the closet somewhere but they've got brilliant motivated people working here. >> John: You've got a ton of experience. >> Peter: We're passionate about this stuff. >> They've got a lot of experience too, and they brought in some new guns the product side we're going to admit has a fantastic product executive and he obviously has that background but I want to shift now to the end user now. They're now living in the world of massive business transformation. Yeah, digital transformation, rah-rah. It's kind of overhyped but what that translates to is business transformation. That's the conversation on all CXOs. >> Peter: Business transformation around data. >> Around data so I want to get your thoughts now vis-a-vis that the customers perspective. I'm looking at Informatica. How do I feel about them? >> Well before I march off this mortal coil, this is what I want to happen. I want to say look computer I want to put together a new pricing model all right. Here are a couple variables I'm interested in. One of my competitors just issued a press release with some new pricing data. Go get that and come back to me with some data. Recommend some data I need to build a model to do this. >> Peter: Give me some updates. >> Yeah. >> That's CLAIRE, I mean that's something to talk about doing some automation machine learning. Peter, do you think that's the nirvana, that is a nice position to be? It's like hey Alexa, play some music, and you know they play a genre for you. So I mean give me some data, pricing data. >> So let's think about the elements that are going to be important as we think about this new notion of data management. Again, I don't think Informatica is too far from this. A new notion of data management suggests number one, that if your business is going to use data differently, you have to introduce some notion of some concept of design. How do I design business around data, and how do I design data around business needs? Part of that problem is going to be being able to go out and capture inventory catalog metadata. No question about it. You're going to need the next generation of data management. It's going to be very metadata focused. Secondly, you need a lot of the tooling that's capable of doing the transformation and creating derivative value out of data. That's something else that they have. The third one and this is a really, really important piece, and we talked about it for example with (faint) and a couple of other people. Data has to move but it has to move not just based on point to point interfaces that are programmed and built but based on patterns of utilization, and in a way that the system recognizes that. That is going to be crucially important, that whole notion of data that's moving in response to what the business needs, and not what the people recognize and do. >> Okay, so that reminds me. I was speaking to someone who is part of their security stuff right and I said well have you considered how data security could benefit analyst as opposed to keeping the company out of trouble? >> Peter: Business analysts? >> Yeah, just couldn't answer the question right. Because I said, so tell me how this works, and she said "Well, if someone has a pattern "of how they work with data, "if suddenly they work out in that pattern, "it's going to send off a signal." I said what's a signal? Are they going to get a skull and crossbones like oh you can't have this data. >> It sends off a policy flag. Okay, hey you're out of your swim lane. It's like get back into your jail cell. I mean it's restrictive, Absolutely restrictive. >> But think about it this way. Don't you want your analysts to be thinking out of the box? Which means on a regular basis, they would be requesting data they don't normally want. >> Here's what I like about Informatica from my perspective. Again, you guys are in under the hood in a deeper way but from my perspective is that what they're doing with the horizontally scalable is interesting, and this is interesting on the metadata side, you mentioned that with SPAN, Google SPAN are now available. They're in Amazon. If they can somehow create that addressable data sets that could be horizontally scalable and freely available, I think that is a winning strategy because most of the vendors in the data take a siloed stack approach. Okay here's our stack, you own it. So I think they're on this genius play of okay we can get this horizontal layer, that is now the lock spec, because now I mean I'm agnostic on cloud. So to me I think that directionally is correct. Where that is when the rubber meets the road, is a whole another story. So your thoughts on that. >> It's very exciting, I hope they pull it off. >> Yeah, I think it's very exciting. So if you think about it-- >> How do they pull it off? >> Let's well, so there's, let's-- >> We're not being shot by the other income with bigger guns. >> Let's think about it a couple of different ways of thinking about this right. On the one hand, you have new ways of thinking about how data is going to be spread in a multi or a hybrid cloud world. So that's happening. Secondly, we're thinking about data control, and a data control plane above that, and they're a bunch of companies that are talking about how you bring control across all these different multi cloud instances. On top of that, now we're talking about some of the analytics and how data gets huge from a metadata standpoint. So this is extremely relevant to where the industry is going to be in five years. Somebody is going to get there. It's best to look for the folks who are skating to that puck. Informatica seems to be skating to that puck. >> All right, I want to ask you guys a question. I want you to tell me if I'm smoking crack or not. When I say this the whole goal of getting data from any database at any given time in less than 100 milliseconds, no matter where it came from, when it came from, IOT included all the stuff that's coming in, I'm an app developer, I want data programmability. Meaning I have an app, and I'm doing some some cognitive, cognition thing and all sudden, Neil you bought something at Nordstrom's from three years ago. It's some database. Yeah, that means let's think about the logic on that query. But that data could be cross connected with other relevant data, your Twitter stuff or whatever you're doing, and pull together, provide some insight for you. Now that sounds like I'm smoking crack to pull that off. Is that possible? Can it be done in the kind of low latency mechanism? >> You know it can be done but I don't think we know enough about the data. There are four types of metadata still leave out deep semantic information. I'm hoping they're going to work on that. I mean I was in here 10 years ago pitching ontologies, and they threw me out. (laughs) But I think that the four types of-- (fast crosstalk) Yeah, I think the four types of metadata are great but they're still generating it mechanically from datasets as opposed to some knowledge about what the data really means. To do what you want to do, I think you need some kind of semantic metadata. >> I agree with that, and you also need semantic information about the underlying network as well. So the idea of a semantic-- >> So a lot more work to do to make that happen. >> A lot more work. So final question-- >> It's probably not going to be 100 milliseconds, 140, 150, maybe 200. >> Yeah, well I mean anything, just getting the data would be a win. Okay final question this is kind of more on the stuff we were talking about in leading to the intro of the work you guys are doing. The valuation concept of data, I mean I say valuation, I could mean financial valuation. How valuable a firm is? Or what is our CFO goes, where's our assets, where's our data assets? So there's a combination of data hygiene, and also in heart surgery, right, if it's the heartbeat of your organization, who the hell's the surgeon? Who's the doctor? When do you do CPR? Who does the hygiene? Who does the amputation? I mean who does, I mean this is like, I mean this is a data nightmare of a reconstruction of a company. The nature of the firm is completely upside down when you start thinking data. Just your reaction to that concept. >> Well, they have a very loyal customer base. So I think that they can get out with this before it's completely cooked, and have some success. Maybe I'm being optimistic. I don't know but I think-- >> John: Valuation of data. >> I think that there is a way of thinking about it is not to value data in a narrow sense but to think about data, what we're calling data dynamics. The idea that data's value is founded in its use. It's not something that has value when it's just sitting there and not being used. >> It's, yeah, it's like that old saw. I don't know how to define pornography but I know it when I see it, right. That was a Supreme Court Justice. I didn't say that. >> John: Looks like teenage sex. The hero things they're having it, pull the notch. >> This goes back to the notion of data management. It's how am I going to use data? How am I going to get value out of data through its use? That suggests a whole different set of principles and practices that are quite different from how we normally value assets. >> Okay, tomorrow we got the top execs coming in. We got the CMO, we got the CEO, we got the EVP of Products. What should we be asking them tomorrow? What should I be opening up the kimono and digging into them on? >> I'll ask him what the roadmap is in terms of getting this implemented in their best customers. Not the software development roadmap. So tell us. (fast crosstalk) How this is going to roll out for you? >> You're going to be here up 'til two o'clock. We'll be there, what are you going to be looking at? >> I'll look for two things. One is I would continuously push on the execution. Are they really executing as reliably as we think they are? 'Cause they're making some big promises this year too. The second one I'd look at is again, that beacon, that touchstone, what is this new data management? What are you really going to be leading? >> I'm still blown away by the conferences I go to, everyone's like what is a new way, new modern era's evolving and it's transforming. We're number one in five magic quadrants. I mean how can you get magic quadrants as the scoreboard if you go into a new definition? So again, our metric KPI on that is customers. What is your customer traction? Show me the proof points. I don't care what magic quadrant you're in. That's an old metric. That's siloed based. That's not reality based, in my opinion. So we will drill them on customers. To me that's the scoreboard. Okay it's the CUBE breaking down day one wrap up here at Informatica World. This is CUBE coverage. I'm John Furrier, Peter Burris, and special guest new Wikibon analyst, Neil Raden, covering the value of data and analytics. See you tomorrow, stay with us for more continuing coverage tomorrow for full day. Be right back.

>> Announcer: Live from San Francisco. It's The Cube! Covering Informatica World 2017. Brought to you by Informatica. (electronic music) >> Welcome back to The Cube at Imformatica World 2017. I'm Peter Burris, and having a great series of sessions today and tomorrow. And in this one particular, we got another great conversation with the user. Really looking forward to it. I'd like to introduce Tom Gottweis, head of data strategy at Winsupply to The Cube. >> Thank you very much. Nice to be here. >> So, Tom we've had a full day of conversations with Informatica people, partners, as well as a number of different users. The brands are joggling, what's Winsupply? >> Winsupply probably is one of the more common companies you've never heard of. We are a national distributor of plumbing, heating, and electrical supplies, so we provide everything that makes your home comfortable. Toilets, water heaters, furnaces, air conditioners, all of the wiring that makes it go. >> Well thank you for being you then Tom. >> We like to make sure that everybody's leading comfortable life here. >> So, that's, I mean, so Winsupply, obviously as distributor, a lot of dumb products that overtime will get smarter, but you want to intelligently improve how you move them around and get them where they need to be, so tell us a little bit about the role that you see data playing in Winsupply. >> Well, Winsupply really traditionally has been an organization that relies an awful lot on the expertise and the gut instinct of the people who manage our individual locations. We've got almost 600 of them across the United States right now. And that's served us very well over the years but right now conditions are changing in the market place and are forcing us to really add a more data related, evidence-based component to the decision making paradigm that we've been used to over the years. And so for us, data first of all means making sure that we have the kind of data that we can extract useful information from in a business sense to be actionable, decisionable information, and also it means that we've got the information necessary in order to really add value to the supply chain because we sit firmly right in the middle of the supply chain between the manufacturers and the end-users of that. And so, we want to be able to be the single source of information about the products that we sell throughout the entire life-cycle of those products right from deciding which ones to purchase for any given application to how to install that to how to maintain that over time and ultimately to, how to dispose of it at end of life. And in that way we add value both to the consumers of the goods that we distribute, but also, we serve a purpose to the manufacturers of the goods that we distribute. >> And you operations people to make sure you're optimizing inventories, and movement of things and all those other things. So, that suggests that it's an industry and a company that's in transition from a relatively stable way of doing things with a main focus on just getting parts out sometimes months in advance so that you don't run out, to now becoming much more time-sensitive, customer-sensitive, and operation-sensitive. What does a data strategist do in that context? As head of data strategy? >> Well, in that context, a data strategist has a look at what the existing state of the data and organization is, looks at the desired end state, how we would like to be functioning as an organization in the future and puts in place the projects and programs necessary in order to bridge that gap and charts the path to get to where we want to be as an organization from a data standpoint. >> So, here's where we are, here's where we want to be, here's the road map. That suggests, and we talked a bit about this beforehand, but that suggests that there's a design element to how you think about data. Designing the way forward, both from an end user, from a user design standpoint, as well as other standpoints as well. >> There is, and it's certainly again. We need to design not only the structures of the data to support the functions that we'd like to accomplish, but also design the systems that are going to accomplish those functions for us and quite importantly have that interface smoothly with all of the existing legacy systems that are currently in place, because you can't change out everything all at once, so you need to pick where you want to start. For us it was product 360. That was our initial area of attack to gain the most value from that and subsequent products that we're looking at implementing are-- >> From Informatica? >> From Informatica of course. Our Entity 360 to do our customer and other mastered entity sets that we're doing to kind of help get us along that path. >> Do you work within the IT organization? >> I actually work within the marketing organization. >> Oh, really? >> I report to the CMO. >> Oh, cool. >> I'm one of the two percent. >> Well, but that's good. But tell us a little bit about how as an advocate for the use of data, now working with the IT organization. So, you're the data strategist, here's where we want to go, you have to work with the IT organization and help them turn that into investments and plans for actually building out the capabilities, right? >> Absolutely. Part of that is to assess what products out there, what tools are going to help us get along that path to where we want to get to. Part of that is building a business case to really convince executive management to make the investments that they need to, to get us along that path. And a lot of it is also advocacy right. Working with the IT organization and other different business functions as well to really garner support for the new systems that are going to be put in place. Because ultimately, you can create the best system. If people are unwilling to use that it's still going to create no value for the organization. >> So evidence-based management's been around for quite some time in a number of disciplines, health-care, for example, being perhaps one of the first places where it was devised and practiced. As you work with, in marketing, work with the IT organization to put in place these strategic data capabilities that the business is going to need, what are you doing with the executive team to get them to really buy into evidence-based management, especially in a company that has a history of thinking based on their experience? >> Well, I'm very fortunate in that respect. The executive management team of Winsupply recognized very early on that that paradigm shift was needed and in fact created my position and hired me on as one of the first steps in that transformation that they were seeking to undergo. >> Peter: So, what's your background? How did you get to the point of being a data strategist in that crucial role? >> Well, I come from a highly technical background. I started off as a programmer, system administrator, database administrator, moved into really the software development management arena. Then into architecture and so, it's been kind of a long, strange trip that began as a highly technical function, but over a number of years I've been drawn to the business side of things as well and have been fortunate to gain a fair bit of experience in that side, working with business people to define the results that they were looking to accomplish, and so this data strategist role really fit very well. It really lives with one foot in the technical world and one foot in the business world and serves to sort of unite those two functions in a business. >> Peter: Well, data is in both worlds. >> Indeed. >> And increasingly in many respects what we need to do is liberate it out of the technical world and have it be applied through evidence-based management, through thinking about road maps, the role that data's going to play as an asset it the business more in the business world as well. So, when you came here again, as one of the perhaps a minority of individuals from the business side, when you came here to Imformatica World, what has been resonating with you here? >> Well, integration is been resonating quite well. Scalability and the investments that Informatica is making into cloud-based computing. I see that facilitating a lot of the kind of analytics that we're going to need as we move further along that digital transformation to help us turn the vast quantities of data that we have into actual actionable intelligence for the business. Moving further along, I'm pleased to see that there is some talk of artificial intelligence and deep learning and machine learning that they're sort of moving into that space. I can see there being a huge value for that in a business sense to really enable targeted identification of different results that the business is trying to achieve, whether it be optimizing the product mix at a particular location to maximize the business potential or trying to look for the right people to manage a location, or just determining which customers, you know, are going to go from, you know, your service drain or low level into your core customers that become one of the key customers driving your business. And so, all of that I think is possible to identify via machine learning techniques once we can get the basic source data for all that sorted out and at a particularly quality level that we need it to be to sort of feed those systems. And so, that's kind of where we are as an organization right now. At a fairly basic level trying to get our customer data, trying to get our product data in a sufficiently decent quality that we can begin to distill that actionable business intelligence from it. >> So are you here with an IT peer? >> Yeah, both an engineer and a business analyst. I wanted to make sure that they were exposed to the different products that Informatica has to offer so that, you know, I could get some different points of view on things that we might be able to leverage in our IT infrastructure, our environment, in order to get the most value out of what we're trying to do. >> So as head of data strategy within Winsupply, but report to the CMO, are you looking at it from the customer data perspective or are you looking at it more broadly from data anywhere? >> I'm really trying to look at it more broadly. Certainly, you know, one of the primary areas of focus is marketing and making sure that our marketing organization has the information they need. >> Or customer at least. >> You know, our customer at least. But, that can't be the only focus of data in the organization just because it's so pervasive. It drives everything that a business does and it needs to be used optimally across the business. >> So, you have, Winsupply has a special set of complexities in that you've got, you know, what you do within your role and proximity to you like the IT organization. You have an management team that's moving to an evidence-based management approach, which serves what you're doing. But as you said, you also have those 700 locations that, probably all of them have some degree of autonomy because they're responsible for making those locations sing. How are you working with them to start pushing some of these concepts out into the field? >> Well, that's an interesting question. I mean, that really highlights sort of the advocacy part of the role of data strategists, at least within Winsupply. Once again, you can create the best systems, the best tools in the world and if your users are unable to understand or to use what you've created, it really adds no value. And so, part of it of course is having systems in place that create the kind of data that you need. The other part of that is very much an educational role where you're teaching the people out in the business to make use of those tools that have been created and how they apply particularly to their corner of the business. >> Last question. When you think about, let's say we had a couple people here that want to be data strategists. What would you advise them to do next to move down that career path? >> It's one of those that would be really useful to have an engineering degree and computer science discipline and an NBA. >> So, you've got to have data and understand what data is and the disciplines of it, but you also have to understand how it's going to be applied in business over time. >> Tom: Precisely. >> Excellent. All right, Tom Gottweis, head of data strategy at Winsupply. Thank you very much for coming on The Cube and talking about what you're doing at Winsupply and the role of data strategy and how Informatica's helping you along your path to evolve and make Winsupply better. >> Well, thank you very much for having me. >> Peter Burris, once again, this is The Cube at Informatica World 2017 and we'll be back shortly with a wrap up for today and anticipating tomorrow. (electronic music)

>> Announcer: Live from San Francisco, it's theCUBE covering Informatica World 2017. Brought to you by Informatica. (light techno music) >> Welcome back to Informatica World 2017. I'm Peter Burris, and once again theCUBE is broadcasting morning to night two days in a row to bring you The Signal from the Noise, this very very important conference. There's a lot going on here as we talk about the increasing role that data's playing in the world. Now, to get a user perspective, and not just any user perspective, a leading user perspective, on some of these issues, we've asked Mel Kirk to come on board. Mel, welcome to theCUBE . >> Thank you sir. Glad to be here. >> Mel is the senior vice president chief information officer for Ryder Systems. For those of you who don't know Ryder, it's a trucking company, a trucking and leasing company. >> Mel: Absolutely. >> And my background is I used to actually do a lot of research around transportation-related things, and I always found the ability to use queuing theory, >> Mel: Ah. in both technology and in transportation, >> Yes. to be very fascinating. So again, Mel, welcome here, but tell us a little bit about what you're here at Informatica World for, and what's your interest in all this? >> You know it's interesting, this was one of the conferences that I set out this year that I wanted to come to because I wanted to learn more about where Informatica is going in terms of leveraging data. Transportation company, we generate a lot of data. We have three business units, we have a fleet management company, a 3PL traditional transportation, supply chain company, and a dedicated transportation company. All three of those businesses generate a lot of data, and we're on a journey to try to figure out how, what's the best way of using that data to improve business outcomes. So that's what I'm here for this week, is to learn more about the tools that are here, the applications that are here, that we can use to do just that. >> So one of the things that I'm fascinated, often the new branding of Informatica, which we think is good: enterprise, Cloud, data management, leader. We know what enterprise is, we know what Cloud is, we know what leader is. One of the dynamics is, what is the new data management? We've talked to a couple of people about it. From your perspective, all this data coming in, what is the new data management function at Ryder, or the new requirements and capabilities? >> I think the biggest thing for us, from a data management standpoint, is mastering our data. Like I said, we generate a lot of data. We've got two really important domains in which that data revolves around. It's a customer and it's a vehicle. And so our objective this year is to master both the customer and the vehicle, the information around those, so that our marketing team can create better solutions by understanding all of the ways that a particular customer may interact with our business. It's also our operating team is leveraging that same data to win at the local level on a day-to-day basis. When a driver comes to one of our facilities, and he wants work done on his truck, our account people and our service people at that location will be able to pull up specific information about that customer and perform the work that they need based on the contract they have with us. That's a win for the customer and a win for our local team. >> So key, handle the customers, handle the crucial assets. That seems to be a general trend in the industry, is you look across both the conversations that you're having here at Informatica World, but also beyond. Where do you think the industry is going, from a trend standpoint, with some of these questions around data? >> I think we're all on a journey to try to figure out the best ways to leverage the data, treat data as an enterprise asset, right? A real enterprise asset that may have more value to it than some of the physical assets that sit in our business. And as I've talked to people during the week here, it's really about that journey of trying to figure out how do you get better value out of the investment that you make, and understanding, cleansing, liberating your data. And for us, again that's creating products, new products, from the data that we have, and it's improving productivity and efficiency in our operations with that data. >> So you must be excited about some of the new capabilities Informatica's announcing about being able to discover, you know, inventory, and then use metadata in new and different ways. What do you think about some of the metadata issues that Informatica's talking about here? >> Yeah, I think, you know, both metadata and Cloud for me is very important. The metadata is important because, again, we've got multiple business units, right, that are operating with elements of data that are not associated across the enterprise. And so, you know, getting more deliberate about understanding the data at the metadata level will help us as we try to bridge everything together across our enterprise. The Cloud's important because more and more of our customers are moving from a batch world to a near real time world. And what's happening there is we need the ability to spin up operations in a very quick way, receive data in large swaths. So having burst capacity is what the Cloud is going to give us. The immediacy of capacity is important to us, so the Cloud-based applications that I've seen here, even the enterprise information catalog is important because as we go through and we cleanse and harness our data, having it in a structured, governed pattern is important to us as well. >> So you had been in the business. You're ex-GE before you came to Ryder, a couple iterations before, you know, Master Black Belt, Six Sigma, that kind of stuff. You're an operations guy. >> I'm an operations guy. >> So as you think about going from an operations guy, and great operations guys are very focused on data, into the CIO, how was that transition? >> It was more than what I thought. You know it's interesting, I've said that as an operator, I'm not sure that I would've been effective in this role five, ten years ago, because it was a different type of role. >> Peter: Right. >> Today I don't know how you'd not do this role, how you could do this type of role, the CIO role, without having an operational background because the technology is integral to everything we do now. So, you know, where before, companies differentiated themselves on, you know, operational rigor and process, which is what I live in, >> Yep. >> Now it's about data. Now it's about data and the technology tools that can free up capacity, create productivity, and again, generate products. And so, this has been a great exercise for me, a great learning experience for me getting involved in technology at a time when it's moving so fast, right? Every day is a different day from a technology standpoint, and bridging that with my operating background, I think it's been a great experiment for both me and Ryder. >> Well a lot of CIOs that have great job satisfaction at heart are operations people who have figured out how to be operations people as opposed to people who often, CIOs who often don't have that satisfaction are spending their days putting out fires, and they never get into that groove. But think about as the role of the CIO changes at Ryder, but just in general, how do you see yourself organizing your groups around data assets, because it used to be that the key assets were, you know, the hardware. >> Right. >> Or the network. How is that catalyzing a new way of thinking about getting your talent mobilized to do what Ryder needs your function to do? >> You know, the big shift is away from keeping the lights on and keeping the phones working to delivering outcomes for the business. So that's that operational view, right? It's really whether there's an application development team or a talent on our, employee on our infrastructure team, it's about delivering outcomes for the operating team, for the business team. And so an example of that is in our fleet management business, right, we run 850 shops around the US and Canada, repair centers, and our core application in that business, our technicians in those shops say, "Mel, if you can do one thing for us, "make the application faster." That's both an application problem and an infrastructure problem. >> Peter: Sure. >> Right? In terms of trying to find the right solve. What I've been able to do and what I've been focusing on is translating that ask, of give me more speed, to the infrastructure team and the application team in a way that they understand that that incremental speed means better customer service, better outcomes for the business as well as our customer. That driver that comes to that repair center, he or she is on the clock. >> Peter: Right. And they want to get out as fast as, they are more, of more value to the customer when they're on the road doing their job. >> And a truck is typically not a cheap thing. >> Mel: It's not a cheap thing. >> So a truck's on the clock too. >> Mel: Absolutely. >> So as you think about the new, these new disciplines, and then acculturating the application team to, at least in this case, speed, the infrastructure team to speed, are there any new skills or any new disciplines that you are finding need to be filled within your shop? >> You know, the thing that's been interesting, and I'm going to go back to my Six Sigma background, the thing that's really been interesting, and when I take into consideration the pace of change of technology, it's been change management, right? I mean, the application team can come up with the best, the absolute best solution. I'm going to add two, it's change management and the UI, the user interface is important to that journey, right? >> Peter: Absolutely. >> And so they can come up with the greatest application, it could be the best solution ever, but you've got to get people, like in our organization it's nothing to see employees that have been with the company for 20 years. And getting them to fundamentally change how they do work, that's a challenge. And so we, what we've been focusing on is educating both the IT organization as well as the business team on how to drive change, especially in an organization with such a long, rich heritage. >> So as these changes start to manifest themselves, your relationship with the executive staff, how's that evolving? >> Yes, so when I went over to, when I came over into this role, you know, I'd left the operating role as a peer, and I came over to the IT role, and I think they felt sorry for me because of all of the challenges. But what's evolved is that as I've learned more about the technology and how to deploy, I've been able to actually balance between communicating with the technology team on the needs of the operating side of the business, and then translating the technical challenges to the operating team so that they've got a better sense of if we're going to launch a new product, or if we're going to onboard a new account, right, there's some lead time, there's some pre-thinking that needs to happen to get the technology right for you to be successful when you deploy for that customer. So I think bridging the gap between the two sides of the company has been very important for us, especially now given that, again, the pace of change with technology. >> Peter: So does Ryder have a COO? >> Ryder actually doesn't have a COO at the corporate level. We have a COO in our fleet management business, but I'm playing kind of a hybrid role I'd say. >> Peter: Yes. >> You know, kind of a CIO/COO because I can blend the two. >> Excellent! And how's that, how's that going? >> It's actually good. When I first moved into the CIO role, I was very deliberate about not encroaching on the role of the operating teams, right, even though my heritage and all of the things I had done in the company was around operations, I didn't want to make operating decisions from the CIO role. What I'm realizing now is the best value, the best benefit for Ryder and the customers is for me to bring all of the skills that I have, right, plus the talents of the team, to bear on a problem for the company. So I've thought less about boundaries and more about delivering outcomes. And if that means I have to put a, you know, a little bit of an operating perspective on a technical challenge, so be it. >> Which is really quite frankly what any real great Chief anything does. >> Yes. >> How do I take shareholder capital and translate it into an outcome through my purview. >> Mel: Right. >> So, Mel, let's pretend we got five CIOs sitting here, >> Mel: Okay. >> All about ready to start the journey that you're quite a ways along. What is the one thing you want to say to them? Say, here's how you're going to get started, and here's the pothole that you have to look out for. >> You know, I think one of the most important things that I would advise is to divide, especially if you're like me coming from a different purview and even folks that have been in technology for a while, establish a board of directors, right, your own personal board of directors. For me that was, I had to identify, you know, a couple of folks that had been in this role before that I could call and reach out to and get unfiltered advice, right? It was also identifying, the second one was identifying a short list of vendor partners that I could go to for technical questions in their domain, plus beyond their domain where I felt comfortable with the autonomy of the answer. >> Good ideas. >> Right, just good ideas. No sale, just good ideas. Then I had to reach inside of my team and figure out who are the one or two people in the organization that I'd go bounce ideas across for the sake of the change management that I talked about, right? Some for technology but also from a change management standpoint. And then build a couple of key partners at the leadership level within the organization, again to help with some of the concepts and the ideas. A lot of what a CIO is going to bring to bear now is going to be disruptive to the way a business, a company does business today, and so they're going to need constituents or partners from the executive leadership team. >> Yeah, none of it happens if the CIO doesn't recognize the change management that they have to drive. >> Absolutely. >> About their role within the business. >> Absolutely. So I used my board of directors, this board of directors, as a way of getting smarter about the job, you know, secondly, to help facilitate the change that we need, and three, just to bounce ideas. For sanity. >> Awesome. Fantastic. Mel Kirk is senior vice president, chief information officer of Ryder Systems Inc. Mel, great conversation. Thank you very much for being here in theCUBE . >> Okay, thank you for your time. >> Once again, Peter Burris, Informatica World 2017, we'll be back with more in a moment. (light techno music)

>> Announcer: Live from San Francisco, it's theCUBE, covering Informatica World 2017. Brought to you by Informatica. (Upbeat music fades) >> Hey, welcome back everyone. We're live here in San Francisco for Informatica World 2017. I'm John Furrier with theCUBE, SiliconeANGLE's flag shift program. We go out to the events and extract the seth-a-pla-noids. My co-host for the next two days is Peter Burris, general manager of Wikibon Research. You can find that research at wikibon.com. Our next guest is Deepak Gattala. Big data architect, enterprise business intelligence strategy and planning with Dell, EMC Dell. Welcome to theCUBE. >> Deepak: Thank you so much. >> Or Dell Technologies. That's a big company now. You got a zillion brands. We just came back from two days at Dell EMC World in Vegas. A lot of action goin' on in your world, but you're here in Informatica World. You are the distinct winner of the Innovation Honorary Award. Tell us about that. That was last night. >> Yeah, exactly. It was a really good. It was great to be there, and part of the Honorary Awards and things like that. Its been really trusting that, well, you should know, big data is coming into maturity at Informatica, and we use a lot of Informatica products to be successful in the big data site. >> So, you're a customer I n this case, with Informatica. You're a customer of theirs. >> Deepak: Yes >> Alright, so how are you guys using Informatica? >> So, Informatica, we use, uh... Well you name it, and we have it so many products that are out there for Informatica right now, so, we started our journey back in 2007 with Informatica Power Center. As we evolved in different silos and different data sets, that got into, over a site regard lot of structure and unstructured data, and the first of big data also started growing tremendously. So, we have a new platform, and we have a data lake today that we harvest a lot of data that's coming from different sources. Some structured, unstructured, semi-structured data. We needed a tool and technology that can help us to actually use our existing skill set, and the army of the people who knows Informatica from the days of 2007 til today, that we have kept in sight. We wanted to level raise our skill set. Then you're creating a bunch of new folks in the big data platform, and starting them from scratch. >> Deepak, Hadoop was supposed to change the world, and like actually kill Informatica. All the press had, "Low End for Matica," and "Big Data Hadoop." Hadoop is just one element, now, of the big data space, or, how we wanted to describe it. Data lakes are also just fine. I don't like the them data lake because they become data swamps if you don't use the data, and as Informatica-- My question is, as data is gettin' laid out, whether it's Hadoop, or in the clouds, making it relevant is a real architectural challenge. Can you share your insight into, how do you guys look at that data architecture? >> Differently, right? So, like anybody else, you know we also face the same problem off record a lot of data or that we put it on, whether it is water data or lake? Whatever you want to call it. Then over the time we realized like, "Oh, okay. "Now what do we do with this data? "What is the value? How we can extract it," right? That's how the tools and technologies around this whole ecosystem comes into the play, which actually provide that value to get that data value extracted from it. Informatica is one of the tools that our choice was offered doing some of the big ops, and going though a process off proof of concept, and we are identified. This is the stage that we have to make a conclusion to say that we want to go with Informatica because of too many reasons I can't speak about, but one the major reason was, what I can say, I can do the same existing skill sets of what we have in house, and improve on top of it. >> So Deepak, the concept of data management used to be associated with managing a file, managing a data base, effectively managing tools that handle data. As we're hearing it increasing applied in the digital universe, I presume at Dell as well, the notion of data management is starting to extend and generalize a little bit differently. How do you see data management? And the next question I may ask you is, from an architectural standpoint, what's the relationship between what you do an architecture standpoint and how you envision data to managed. What is data management to you? >> So the data management is basically like harvesting your data, right? So basically, drives, like I said, data is coming in different forms. You wanted to go and get the data consumption happen from different sources and different silos that we have one time. Now we are at the situation like, what kind of data exists? What is a metadata? What is the governance unearned it, right? So those are becoming more and more and more important as we move and getting mature in this whole data management prospective. >> So, its looking at data across applications and across tools to try to increasingly treat data as an asset that can be managed just like a plant can be managed. Do I got right? >> Exactly. So, we have to realize that now data is an asset. That's where the value is. Your business and your stakeholders, everybody is looking at the data that we extract a value enough. >> So, does a data architect, then... Again a data architect used to be the person who laid out the database manager, and what not. Do you see your job now more as, design plus implementation with an eye towards performance and ensuring peple understand how to use data. Making sure things can be governed. What does the emerging and evolving job of a data architect in this new era of data management as managing data assets? >> So, traditionally with the relational database, it worked pretty well for the architects with the work they are doing, and it worked pretty well. But the thing is with the new changes we are going though, with the fast evolving technologies that we are having and the mobile data that we are getting in different forms. It always gets challenging that it's not just a data architect. It have to be co-- Together with some of the solution architecture together, to see how we have to go and consume all this information, but at the same time, Paul, we are providing value at affect >> So the tools that Informatica is providing are helping you do that? >> Yes the tools at Informatica have definitely helped us, starting at the power center site, which is more inclined towards conditional databases. Today we use big data management tools on our website, which is actually helping us the same kind of value that it provided with the power center. Now we can provide the same value at our new platform. >> So as you look forward over the course of the next few years, do you anticipate that the assets, the data assets that you're creating in Dell, are going to be applied to... How developers going to do things differently? How users are going to do that things differently. How do you see the data architect and data management serving these different consumers of data within Dell? So, what all includes, like, you know the business satisfaction right? The business is trying to get the value of the data yesterday. So, you know what? You need to be so fast enough to deliver the stuff to the business. One of the major capabilities that we are looking at is, to have the self-service capabilities for the business stakeholders so they can go and do themself rather than waiting for the IT or being a bottleneck for them to deliver what they want. >> So I got to ask you about this award. Dell was recently selected as the grand prize winner of the Informatica one million dollar software and services big data ready challenge. Was that cash prize? Michael Dell just spent 69 billion dollars on EMC, you'd probably use-- No, I'm only kiddin' (Peter laughs) Was that cash or was that product services and-- >> No, it's not the cash. You're suggest I'm one of the hundred year award that we got as Dell, being a proactive customer. A few guys who got inbranded. And, so research and the software that actually we are looking at Informatica data and degration hub and Informatica Intelligence Data Lake, which actually will provide self-service capabilities and integration at a single point. >> So you apply-- so, the objective of the self-service capaibility. The outcomes that you seek, you use the data inegration hub and some, for a period of time, some free software and free services to build that pilot, and then roll it outto the organization. >> Exactly. The whole idea is to show the values out of the these tools and technologies that Informatica has been investing` and helping the whole ecosystem to improvise the standards. >> So, Deepak, I got to ask you. We had some of the execs on earlier, and they're talking about, "oh, data's the heartbeat of the organization." You know, kind of cliches, but kind of accurate. We believe that to be true. Certainly, data is the center of the action. But then, it brings up the whole data conversation. Who's the practitioner? Do you have heart surgeons? And then, what about the hygienist? You know you got to have data hygiene. The big data ready challenge is interesting because its always been a challenge to go from pilot to production, but then also its the readiness around an organization's ability to understand what the hell they have, how do they use it, and then how do they take it to the next level? The mastery of doing the data. So, certainly there's different skill sets. How do you look at that analogy, and how would you organize teams around that, because in some cases, there's a heart surgeon needed. You got to redo some surgery on the company, Felt at the data strategy. And, sometimes its just know your hygiene, brush your teeth, if you will, kind of a concept of being ready. Your thoughts and reaction to that? >> So, yeah, initially we also started in the simplest days just to get the data and put it in one place, but it's not; it's just one part of the whole equation. You have so many things like data governance, data quality, data security, because you know, you might have a PIAD now that you want to secure it, and you might have something like, weblocks is doing your security. Everybody has a play in this. Its not just a one thing that you know, here we have the data fusion done, and then, you know, you're good. So it's not that the case. You should just always that the maturity happens in different stages. >> So the hiring and organizing a team, that's a specialty right? You're going to have the more skilled folks, and then some of the, you day to day, maybe an analyst or citizens data wrangler. You know, these things going on. Your thoughts on organizing, and the teams around data. >> Yeah, so one of the teams is that we are starting looking at these. We are harvesting a lot of data scientists interknow to Dell. That's because Dell's the ones, guys stuck Bill Nye on mostly to see, to extract the value of the hidden stuff, that we are not able to see as of today. To do that in an effective manner, we need to know how to unleash those guys and be self sustained by themself, so they can improve the quality and provide the value of innovation. >> The folks that have been following Informatica over the years, they were once a public company. The data warehouse was all the rage. Now, its real time. All kinds of landscape changes in the marketplace. What's Informatica all about today? >> Informatica is no more just data platform. I think its fanning it's wings to do more stuff. Especially on the beginner side. Now you have this Informatica data degration hub, and you are talking about having this intelligent data lake, and things like that. Which is going to be a link to use in learning off machine learning algorithms and things like that, having this whole meditator concept that is matured, or just a metadata manager. And right now, its going very huge because of the different big data platforms are coming together. Its not only the big data platform. The big data platform is very loose term to me. It's just not the Hadoop, you know? It could be... At Dell, we have so many different technologies come together and recall all of them as a data platform for us. We did a platform for us. We know how to just being one of the competent ones. >> So you're saying basically is there's no silver bullet. >> Yes. >> and there is no magical answer. >> But there are skills. >> Yes. >> And so, increasing what you're looking to do, is saying, what are the outcomes? What are the objectives? What are the skills we need to get there? And then, lets look for tools you today are lining up nicely with Informatica. >> Deepak: Exactly. >> So if you think about the next steps that you're going to take, where does the function of a data architect go within Dell, and what kind of recommendations would you make to those users out there who are thinking about how they want to optimize their skills. Their use of their skills in a data analytics world. >> Yeah, sure. So the data architecture is, like I said, knowing the previously in their traditional data warehouse kind of stuff, it was pretty straight forward. But now, they don't-- we are seeing that data architects are getting more and more matured, and I'm getting this data into semi-structured data, and improvising that how the data fit actually get readjusted in the right manner, so that, you know what we can really... Is it like three and one half, or whatever? Is it-- You can't have a data silos anymore? It's like what you need to bring in all data sets together to actually making a meaningful answer-- >> Peter: Well, at least make it possible to bring it together. >> Exactly. >> We had a lot of costs and a lot of pain. >> Yes. >> You may not have to bring them all together. As you said, you don't, its not all about putting it all in the data lake, its about making it possible to acquire. >> Exactly. So you have to know where the data is, you have to be able to quarry, you have to build and reformat on the fly, all these other things to servwe your customers, especially in the self-service world. >> Right. >> So, where does this go? How is this going to drive? What recommendation would you give to companies who are looking to accelerate their use of these new technologies and new approaches? >> I would say this to everybody. Adhere to your customers. Adhere to your business. They are the reason it is for your-- like you know what? There's no person in the organization that knows every domain. So you need to be in a way where right off your sneeze off different data domains that you have, and make sure you pull all these resources together to actually contributing to the whole arbitrational white impact. >> So, start with-- be true to your business. Your customers. Focus on finding data. And then focus on bringing the appropriate level of integration. Not putting it all in one place, but so your customers can be matched to the data they need. >> Deepak: Exactly. >> John: Alright, Deepak, final question. Just your thoughts on the show here. Again 3,000 people and growing every year. The new rebranding, Informatica going into the cloud world. Automation, you're seeing CLAIRE, this new AI meets data. What's your thoughts? >> I think this is phenomenal approach that Informatica is taking right now, and I'm glad. Like you said, there's 3,000 people here really interested to know what's going on and how the things are evolving with Informatica. It's a really great show to be here. Thank you. I'm very glad to be part of it. >> Congratulations on your award for the Big Data Ready Challenge, grand prize winner. A million dollars worth of products. I can knock down some of that purchase price, but I'm sure you guys are big customer. (group laughs) >> Thanks for coming on and sharing your insight as a customer of Informatica. >> It's my pleasure. >> It's theCUBE. I'm John Furrier with Peter Burris. More live coverage in San Fransisco. theCUBE at Informatica 2017. We'll be right back after this short break. Stay with us. (upbeat music)

>> Announcer: Live from San Francisco, it's the CUBE. Covering Informatica World 2017. Brought to you by Informatica. >> Hey, welcome back everyone. We are here live in San Francisco for Informatica World 2017. Exclusive CUBE coverage of the event, Informatica World 2017. I'm John Furrier with my co-host, Peter Burris, General Manager, Head of Wikibon Research at Wikibon.com. Our next guest is Greg Hanson, Vice President of EMEA Cloud and DaaS, Data as a Service. Welcome back, good to see you again, CUBE alumni. >> Good to see you, yeah thank you very much. >> Year two, or year three of our coverage. >> Exactly. >> So last year, we had a great conversation. I think you laid out pretty much the playbook. Lots happened, in fact Brexit happened. But cloud in outside of North America is a tricky game because there's a lot of different countries. We got EU, and other parts of the world there. It's really a regional issue, and you see in a massive expansion. The cloud guys, we have Amazon, sponsorship here, Google, now expanded globally. What is the landscape like? Given Brexit, that was a political thing has ramifications but also the regional expansion of the cloud players has been pretty significant over the past year. With announcements coming, I can't even keep track of 'em all. How is that impacting your business? >> So it is quite fragmented across EMEA. Our region is EMEA and Latin America as well. It's a huge geographical region. Across a geographical region that's very different in different countries. So the EU as a whole, there is, cloud is very hot in the EU at the moment. There's a large adoption. I think we've past that point of no return, past the tipping point, as you should say. Every enterprise customer I talked to is now it's not when they're going to, or if they're going to adopt cloud it's when. Usually, they're already on a journey that we can help them with. But then in some of the far-flung regions where the maturity of cloud is less so, where the presence of Amazon or Microsoft, or even ourselves is limited. Like Russia for example or the Middle East. There's not that same kind of infrastructure. So the desire and the demand for cloud in those regions is less. But the large majority of our geographical region, cloud is a huge topic for every single customer. >> What's the state of the art right now in your territory with cloud? Obviously, from Informatica perspective, you have a view but also in cloud adoption, hybrid, clear, public cloud, there's use case for that, a lot of on-premise with hybrid. What' the key state of the art right now for Informatica and the cloud players? >> I think there's fabulous opportunity for Informatica. It really is a hot topic. There's two ways that we can deal with that. I mean, there's the enterprise space, which Informatica has been ruling for 20 years now but cloud gives us a huge opportunity to go into new market sectors as well that we've really not been in before. Mid market opportunities. You no doubt see a lot of the partners around the event here that we've got that allowed us to address customers that we simply weren't addressing before. We had an enterprise sales force. If you think about those mid market organizations, they're the organizations that are really going to drive the cloud adoption as well. In countries like Italy and Germany, where you very quickly get down to small and medium sized enterprise. Cloud is huge in those organizations, in those countries. There's a great opportunity for us to go after mid market sector as well as the enterprise. >> But increasingly in the digital business, we were talking about this earlier in one of your segments, in the digital business, you have greater distribution of data, greater distribution of function, and almost inevitably, the ecosystem is going to be comprised of big enterprises but also mid market companies. They're going to have to work together. >> Greg: That's true. >> So it's not looking at the enterprise and the mid market in isolation. Increasingly the enterprise is going to be acknowledged as a way of extending your influence into a lot of different customers or a lot of different domains both through partnerships, as well as your customers. How is Informatica going to facilitate that kind of a new approach to thinking about business as a network of resources. >> One of the great things about the cloud infrastructure itself, if we reel back and think about 10 years ago, when all our products were on-prem. It's very difficult for us to understand what our customers were doing with our products. We have to go an talk to them, and speak to them on the phone, visit them to understand what their use cases were. Now in cloud, that world has changed. Because if you think about one of the things at Informatica is well-known for is metadata. So operational metadata, technical metadata. We can actually see what our customers are doing with our products. We can understand the uses cases. That becomes a crowd sourcing in terms of how you can replicate, how you can industrialize, how you can you reuse a lot of that type of integration, which is enabling us to create new wizards, new accelerators, which are common across the marketplaces and use cases. So really a phenomenal change over the last two years, which has been brought on by that ramp of cloud adoption that we've seen globally to be perfectly frank. >> Okay, take a minute Greg, to talk about this DaaS. I think of Daas, I think of like cellular distributed antenna system but let me, it's an acronym, it's Data as a Service. >> Greg: Data as a Service, yeah. >> Peter: But what does it really mean? >> Take a minute to just break that down. What does that mean to the customer? What's the product? What's the offering? >> Greg: Okay. >> It's important, obviously data is the key, and people want it as a service. So take a minute to just explain what that means and the impact. >> Yeah, it's important to understand what Informatica means by Data as a Service, I think. Our Data as a Service product line, pretty much concentrated and focused on increasing the quality of data. So high performance, quality of data. If you think about digital transformation as the topic, which is being talked all around in rims and corridors around this event here this week. Fundamentally, data is really the key foundation of digital transformation. But I would say high quality data is key to the success of digital transformation. That's what our DaaS product can enable us to do. So if you think about-- >> Peter: How does the customer engage with DaaS? (faint statement) >> So the typical use case is that you could have address verifications and we have products that support multiple different countries and regions, more than 240 countries. So if you want to get high quality data to our customers, which everyone is ultimately wanting to do these days to effectively cross-sell and upsell. We can provide a global facility to do that. But you can fix, you can fix data in batch orientation but what's much more effective is actually plugging into the applications. So become seamless to an end user. So they're using Salesforce.com or they're using another application, and it's embedded into their application. So it runs in the background. When they enter a poor address for example, it will correct it, and it will validate email addresses and phone verifications. We've got a customer in Germany, just as an example, 1&1, which is an Internet service provider in Germany. They've got 7.7 million customers. One of their biggest problems is inaccuracy of data. That prevented them billing, prevented them onboarding the customer first and foremost. Then it prevented them billing, which is a pretty serious problem for an organization. >> Peter: Yeah, I'm moving to Germany. (laughs) >> So by implementing the DaaS products, what they enabled them to do is make sure that when they enter data into a system, that it was high quality, it was correct at the point of entry, which by the way is seven times cheaper to do it there rather than trying to fix it downstream. So it's an important product set for us to support high quality data for that digital transformation journey. >> So you're, sorry John, you're not buying and selling your customers' data. What you're using-- >> No. >> Is this is a service to enhance the quality. >> Greg: Exactly. >> Of your data. >> It will fix data and it will also enrich data that they've already got. >> That's an important distinction, John, because a lot of people talked about Data as a Service, they say, "Oh yeah, I'm going to monetize my data "by giving it to the marketplace." We all know that you give that data to a good data scientist they're going to reengineer your customers pretty quick. >> Exactly. >> That's what people are worried about, the privacy. So back down the drivers for your business. What are the drivers for your business in EMEA? >> Yeah, certainly cloud option which we already talked about is a huge growth market for us in EMEA. But there's other things that happening locally in EMEA marketplace, GDPR, General Data Protection Regulations that are coming up. That is a hot topic on the lips of all of our customers right now. Let me take a minute to describe what that means for people who maybe are not familiar with it. Because it's generally an EU thing but it affects every organization that wants to sell into the EU. It came on the back of the Google Right To Be Forgotten ruling where really what we've got to do, we've got to provide a framework, where a customer can say to an organization, I want you to forget me. Obviously, then need a central library. They'll be able to manage it from a single point. That is an extremely complex thing for an organization to do, particularly an enterprise organization. >> John: Forensics is what it is. >> Exactly. If you think about how to approach that, I think Informatica is in a unique position to help organizations deal with that type of issue. Because, I know one of the announcements today, I think Ronen, who was on before me was talking about CLAIRE, our Clairvoyancy, and our artificial intelligence but it's all about that unification of metadata. That's a great example of how a good use case of where that can be deployed. 'Cause if you think of the fragmentation of data that we've got across many clouds, on-premise, how do you understand even where all your customer data is? That's what the unified metadata can provide. It can go out, collect all the metadata from all these different vendors, index it, catalog it for you. We've been in business 20 years. We know what our customer data looks like. We know what product data looks like. We can categorize it and index it for you. Then you can search it. So you can identify where your risk is, where your customer data is at risk. You can do something about it. Now, with the most recent acquisition that we made last year in terms of Diaku, which is a missing piece for me in terms of how do we expose that to business users to actually engage in the governance process. The new Diaku acquisition of Acson, really fills that gap for us. I think we've got a really good stack to help customers. >> You got product chop, we talked about in the past. The brand is new brand is out there. You're seeing some branding, brand value. Good for the partners, good for business. So with that, I'll ask you my final question which is, what's different from last year? A lot of change in 12 months. Just in a short 12 months, certainly in the product side, we saw some awesomeness from the products. Always had good product folks at Informatica World, which is why I love doing this conference. But the brand challenges were there. What is Informatica? So what's different now from last year? The big highlights. >> For me personally, and I've been here at Informatica quite a long time. I think it's quite refreshing. We had quite a lot of change in terms of our C-level at Informatica. It's really breathe new life into the organization from my own personal perspective. There's a huge refocus and a drive on our, fantastic new product sets that we're releasing here today. Internally, in the organization, there is a big motivation. There is a new kind of culture, a new resurgence almost in terms of where we feel we're going to be in the next five years. 'Cause we're looking at the product portfolio. We're looking at the outlook in terms of our growth, and our strategy. It's a great place to be right now. Sales, it always helps when you get good sales and everything. I'm sure you've seen the figures et cetera that we've been doing. But I can't see that changing. (fast crosstalk) >> Amazon's stock price and sales, and net income over the past year. Really the inflection point was right at '08, end of '08, beginning of '09, but really the real kick up on the hockey stick, which they have, has been around 2010, halfway through 2010, and then just pretty much straight up, massive shift. This is a wave, cloud is here. >> Yeah, I think Sally Jenkins, our CMO, earlier on this morning. I think she put it exactly right. In Informatica, in my view, we've been a little bit too conservative in terms of shouting about how good we are. I think we're pretty much one of the hottest pre-IPO companies that are out there right now. So if you look at our product set, the leader in six market segments. That's a great place to be. So I'm excited about the future-- >> Going private, we've talked to Anil, and talked to all the top executives. It's just a great close the curtain, open the doors back up again when you're ready. Easier to retool. Certainly as a private company, no pressure on the 90-day shock Clark Cherry held, board member was talking about how that makes things go really smooth. >> That's right, yeah. I mean imagine trying to make that journey towards subscription when you're a quarterly based organization. It's helped for the product development, it's helped with the commercial modeling as well. It's an exciting place to be right now. >> So it's good for the management to be focused on not that window every 90 days. But it's really 60 days, when you got 30 days to prep for the earnings call. But focusing on real product innovation, Micheal Dell did at Dell Technologies, now EMC. Lot of great stuff. Greg, thanks for coming back on the CUBE and sharing your insights. >> Nice, great to be here. >> When we're in EMEA, we're going to come by and say hello. >> Absolutely. >> Certainly, we'll keep in touch as we expand the CUBE out to in Europe. >> Look forward to it. >> Thanks so much. It's the CUBE, live coverage. I'm John Furrier with the CUBE with Peter Burris, Wikibon. We have got more live coverage here in San Francisco at Informatica 2017, after this short break. Stay with us. (enlightening tune)

>> Announcer: Live from San Francisco, it's theCUBE. Covering Informatica World 2017. Brought to you by Informatica. (light techno music) >> Welcome back to theCUBE. We're here at Informatica World 2017. We're going from the morning to the night, today and tomorrow, to talk about some of the things that are happening in the world of data management, analytics, master data management, etc. Very, very important topics. And I'm Peter Burris, and we're going to spend a few minutes now talking with Ansa Sekharan... >> Got it, Sekharan >> Sekharan, sorry Ansa, I got it earlier. Ansa Sekharan, who's the executive vice president of Informatica global customer support and the head of the Informatica University. Thank you for coming on theCUBE . >> Good afternoon, Peter. Thank you for having me on theCUBE . >> So, global customer support. Big issue when a company's going through a lot of transformation, compounded by the fact that your customer base is going through a lot of transformation. Business as well as technology. When you take a look at what's happening, 3000 people to show, what is the most important set of messages coming out about global customer support? >> At Informatica, the tagline says great products are just the beginning. As customers make this investment, we have a great services arc which looks at the investments customers make, and see how they can help their desired outcomes. At Informatica, when you look at innovation, you hear a lot about products. You see a lot of great launches. We have a very similar strategy in support. Every four years, we kind of come up with a major version of support offerings to keep up in line with our product innovations, and also to meet customer innovations. Right, so in every two years we have a minor release. So we look at our services as a product. Like the saying goes, we want to make sure our customers do not have to call in. So we have a lot of emphasis on quality, and the great interlock with RND. Make sure, we have been ranked number one in customer loyalty for eleven straight years in that regard. So, we want our customers to take away that support and services is viewed as a product here at Informatica. >> Well I want to push you on that a little bit, and I think this is an important point. In the world of, characterized by a significant amount of change, it's important, I think, that we draw distinction between inventing something and innovating, where invention's an engineering duty, or an activity, and then innovating is a social activity. So we create something new, and then through the innovation process, we get people to use it. So I like the idea of looking at support as a source of innovation in of itself, but talk about how that lines up with the idea of support to help make or ensure that customers are successful. >> Right, it's two parts. It's like how you build the relationships, along with automation. In this age of customers, a lot of emphasis is placed on how customers can do self-service and so on. So a lot of great innovation has been built on the portal. We leverage machine learning and AI, and we have built a great platform to have the customers learn best practices, and find the needs and answers for the most common questions. But, we're an enterprise software company. About 85% of business comes from existing customers, and we enjoy great renewal rates of about mid-nineties. This is only possible if customers are realizing value from our products. So, we pride ourselves on our relationship. We have a customer success team, which also is emphasizing how do we drive desired outcomes. People ask what is desired outcomes? When you make a purchase, there is an expectation of an outcome. That outcome, in conjunction with your effort, the experience makes it desired. So, that is where as we pivot to a subscription company, that is all the more important. Customers now sort of rent our software, when they are on subscription. The onus is on the vendor to make sure you build on the relationship, and you deliver value back to our customers. That is where we our very different. I think, to answer your question around innovation and we combine that with relationships, it's a great combination. >> So let me push you on one other feature there. So, the difference is in innovation on premise or license software is a little bit different than the innovation process associated with Cloud oriented or subscription oriented software. On the one, you get the invention, customer installs it, you might help them install it, you might help with a little bit of support on it, or they are largely responsible. But in the Cloud, the whole notion is you're actually getting the service itself and not necessarily the software. How does the concept of customer support change as you move in to a subscription Cloud oriented world. >> So when you are on the Cloud solutions, you have the meta data of the customer. You can measure every click, you know exactly what the customer is doing and not doing. So we have a product called Discovery IQ, which mines that information and offers recommendations on how the customers could better leverage our products. >> To your team. >> To your team and back to the customer. >> And back to the customer. >> Now on an on-prem product, we help in installation configuration. But the software is running on the customer's premises. That's where we have built in supportability tools which can share meta data back, so that we can understand what phase of the project the customer is in. You heard of a product called Ops Insight, which we just launched. That's a Cloud based product which connects with our on-prem products so that it gives you a window into what the customer is even doing on-prem. The more we know about the customer, the better we can serve them. Some customers are very forthcoming to partner with us, and whenever we have a customer success manager we have great collaboration, we know the milestones, we can orchestrate, how we should march the customers towards the milestones. But, if that level of communication is not there then we have to rely on supportability tools to get the meta data back, and then we push information back to the customer. >> And that notion of a road map or a journey to get to the outcome is crucially important. >> Extremely important, and in fact, we want to build those features in the product. Today if you take a master data management product, the data model is the foundation. Today we are able to collect the data model and look for patterns to see if there is a better data model that we can recommend to the customers. Because if the foundation is not right, months later, potentially there could be issues around scale and so on. What we've been able to do is detect that very early on to offer better solutions to customers and we're talking about solutions data models varied by life sciences, varied by health care, financials. We are able to leverage this knowledge and share across customers. This is not customer proprietary information, just the foundation data models and this what our consulting services team is also able to go on-site and leverage it further. >> So the historical interaction between a software vendor and a customer, typically was around those characteristics of the product. The speeds, the performance of the product, what was required of it, how to configure, how users used it, the interfaces what not. As you move more towards solutions, especially in a period of significant transformation. Now you're talking about how a product does or does not support a business capability. In the world of analytics, it's becoming increasingly obvious that is a strategic business capability that has to be put in place. That means that your support people are moving from deep understanding of the product, and being able to convey that, to having to have a better understanding of the capabilities that the customer is trying to achieve and helping them work through that process. Have I got that right? >> Right, so one of our focus areas currently is the topic of services convergence. In the past customers would make a product investment, support is mandatory, it gets bundled in. They have to make separate purchases for professional services and education. As we pivot to subscription, we're kind of bundling the services along with the subscription. So we are coming up with some innovative solutions later in the year, where as part of the subscription which the customer is signing up for, we're going to offer a five-day consulting services package, or a ten-day services consulting package, included in the subscription. Why are we doing that? When we talk about driving business outcomes, we are talking about, if you are really serious about accelerating those outcomes, you ought to make that investment up-front. And in the case of ... >> Both parties do. >> Both parties. It's a partnership you got to build. >> In many respects, it's a test of almost the seriousness of the customers. That the customers. Are you going to invest your time, and not just your money in to this process. >> Ansa: It's not a one-way relationship. >> Absolutely >> It has to happen both ways. So when the professional services goes on-site, tries to understand what's the business imperative the customer is embarking on. That information is shared back with customer support. So we have an idea. The support folks are still going to be product line focused but the domain knowledge, in terms of solutions, we're trying to address it through our solution architects in professional services. So what is unique is, beginning of this year we launched something called a Support Accelerator. >> Peter: Support >> Accelerator >> Peter: Okay, Accelerator, yup. >> Yes, so you talk about big data. In my experience, like I said, I have been with Informatica for 21 years. When it comes to big data, I have never seen a technology which is changing so rapidly. It's getting disrupted every quarter I would say. So we realized customers have to look at security, the hadoop distribution, and those hadoop distributions change pretty rapidly. It used to take them, could take them weeks, just to install and configure the product. >> Peter: Correct >> No fault of Informatica. Just the complex ecosystem. So we come up with the Support Accelerator, we have some checklist. We'll get this information from the customer, we'll remotely install and configure the product in days. >> So you just gave a great example of exactly what I mean by the difference between invention and innovation, where hadoop is constantly inventing but the customers need help with the innovation side. To get it adopted, to get it applied, to get it used. So they can create value in and of itself embedded in their business practices, and that's essentially what your focusing on with some of the support regimes. >> This notion of support accelerator is focused on installation and configuration. With the example I gave you, we just could shave off a couple of weeks. We are expanding this to other product lines, ideal EIC, and then we are going to be offering upgrade services. When I talk to CIOs, they want to know as I upgrade to the latest version, you have my meta data. Tell me what value am I going to get with the upgrade. I know it's going to be supported, the latest certifications if you can tell me if this feature is going to run X times faster. If there is some configuration that I need to change so that I am better leveraging the features in the product. That's the path we are on. I think we have made great strides on the Cloud side of the house. We have a product called Informatica Discovery IQ, which can make the recommendations we have to replicate the success on our on-premises solutions. That's what we're trying to do with Ops Insight product. >> So I used to do a lot of research around a particular topic, and that was a customer journey with an IT organization. Turns out, that the CIO is most involved in the discovery process, and then that first application process. Discovering the characteristics solution and then ensuring that they are going to get value out of the product, that first project plan. And the reason for the discovery is because the business is typically is finding out that something is not working right, and brings it to the CIO's attention. But interestingly, it's not at the moment that they buy, it's after they buy and sitting down with the team and making sure that the business gets value out of the purchases, and that's where your guys shine. >> Right, and do you know? We want to come up with a success plan with the right milestones along the journey. Through our customer success team, we want to orchestrate this journey. The role of customer success management is like, how do you orchestrate this journey as you go through these various steps. Customers' outcomes are also evolving. Especially in the case of big data. I read an article that said companies, only if they have a business strategy which leverages big data, they have a higher degree of success. Not the other way around. >> Peter: Right >> You know what I'm saying. >> Peter: Oh totally, 100%! >> And when customers make this investment sometime it comes from top down and working with the customer success team understanding with what they want to do. The good news is most of our customers are very happy with our current implementation strategy. So they have a mandate to go big data. So we kind of tell them, "Hey what's your work loads? "You want to do data warehouse optimization, "you're going to shift from teradata to hadoop. "Here is how we will do it, here is the blue print." We've been able to share some of our success stories with other customers to them. It's all about accelerating the journey for them. >> But it certainly is not about getting a cluster. >> Ansa: No >> Deploying hadoop and looking at it and say, we are done. >> Ansa: That's step point one. >> That's exactly right. And increasingly because you can now buy a lot of that as a service, it may not even be step one anymore. >> Ansa: Exactly >> It's an option that you may not choose. So as you think about where customer support, in the context of Informatica's journey, can you give us just a couple of insights as to where you think the customer support concept is going to be in a couple of years? >> A lot of emphasis is going to be on service automation, and the other big board level priority at Informatica is this customer experience. You talked about the journey mapping. It has a story-telling element, and it has a visualization element. As customers come to our website, have awareness, become a prospect, a lead, make a purchase, we land, adopt, expand and renew. A gamut of interactions across the board. We're now going to be focusing on optimization, every step of the journey. We're going to find the moment of truth, which would yield the biggest value to the customer have an outset in approach to validate that. What this has given us, the customer experiences have a cohesive strategy which cuts across all functions. Before we had KPIs on a functional basis, now we have KPIs on a horizontal basis. >> Peter: Tied back to customer experience. >> Tied back to customer success. Can we get them to go live faster. >> Right. >> Are we getting them to renew on time. So these are metrics which are shared by every function within Informatica, not just the renewals team, not just the support team. I think with the emphasis from the board and with the support and investments we are making, I think this is going to take us to the next level and I'm pretty excited about it. >> Excellent! So Ansa Sekharan. >> Sekharan >> Thank you very much. Just to let everybody know, with Informatica longer than Derek Jeter was with the New York Yankees. >> Here you go. >> 21 years. >> Thank you Peter. >> Thank you very much for coming on theCUBE . So, Ansa Sekharan is the executive vice president of Informatica's global support and service organization. Once again, thank you for being here and we'll be right back with more from Informatica World 2017, in a few moments. >> Ansa: Thank you. (light techno music)