 From theCUBE Studios in Palo Alto in Boston, connecting with thought leaders all around the world, this is a CUBE Conversation. Hello everyone, welcome to this CUBE Conversation. I'm John Furrier, host of theCUBE. We're here in our Palo Alto Studios in California for CUBE Conversation, which Russ Menon, who's the Senior Vice President General Manager of Informatica, of the Master Data Group. It's Russ, great to see you. We couldn't see you in person. Three-time CUBE alumni at Informatica World, industry executive, we're remote. Great to see you. Good to see you, John. Great to be back. Wish this was in person, but I'll take this. This is fantastic. Well, one of the things that's clear in my interviews over the past four months, we've been doing our best at the remote interviews. We've got a quarantine crew here. We're doing our part telling the stories that matter. Data now more than ever, COVID-19 has shown that these, the companies that are prepared that have done the work, and for this digital transformation, putting that cliche aside is real. The benefits are definitely there. And you're seeing things like reaction time, war rooms are being put together, because business still needs to go on. This is like the reality. And so companies are seeing some exposure and some opportunities. And so a lot of things are going on. So I want to get your reaction to that because there are changes on how customers are evolving with data. You guys have been at the forefront of that, pioneering this horizontal data fabric, data 4.0 as Amit talks about. What are you seeing from customers? How are they approaching this? Because at the end of the day, they got to come out of the pandemic with a growth strategy. They got to solve the problems they got to do today and be in position. What are you seeing for changes? So one of the most important things that we started seeing, there were three big trends that we began to see starting in about late March. And share some of the data points that we saw across the world. Starting with Italy, which was in the news earlier this year with the pandemic, we saw that in one week, the stats were that online or digital sales increased by 81% in a single week. And it's obvious. When you lock down a large population, commerce moves away from the brick and mortar kind of model to being completely online and digital. The other part of it that we started seeing is, we had already started seeing a lot of our customers starting to struggle with supply chain issues. As border started closing, opening, and then closing again, how do you maintain a resilient supply chain? And a resilient supply chain also means being able to be really agile in terms of trying to identify alternate supply sources, be able to quickly onboard new suppliers, maybe in different parts of the world that are not so affected. And then finally, the last piece that we saw were, every single CFO, Chief Financial Officer, people who ran finance organizations at all of these companies. For them, it is almost as if you're driving down the highway and you suddenly run into this fog bank. The first reaction is to hit the brakes, of course, because you don't know what's, so every CFO around the world started saying, I need to be able to understand what my cash flow situation is. Where is it coming in from? Where is it going out of? How do I reconcile across geographies, lines of business? Because everybody realized that without an adequate cash reserve, who knows how long this thing is going to carry on, we need to be able to survive. And then the fourth element that, has always been important for our customers is all about customer engagement and getting the best possible customer experience. That's just been turned up to 11, the volume, because as organizations are saying, there's disruption happening now, there are new ways in which consumers are going out there and buying products and services, and these things might stick. There's also an opportunity for some of these organizations to go out and enter into markets, gain market share that they were not able to do in the past. And then how do you come out of this? Whenever it is, how do you come out of it? It's always by making sure you're retaining your customers and getting more of them. So the underpinnings across all of this, whether it's supplier data, whether it's getting the most accurate product information delivered to your online channels, whether it is being able to understand your supply chain holistically, with a data platform under it. And then finally, customer experience, depends on understanding everything end to end, including everything you need to know about your customers. So data continue to become top of mind for all of these organizations. Yes, Suresh, we've had conversations with COVID in the past three years, and I can remember them vividly all about, and we've been really geeking out, but also getting very industry focused on all the enablement of data and doing all these things. Arrosothal scalability, application enablement, AI, Clare, all these things are very relevant. But now with COVID-19, that the future has been pulled to the present and it's accelerated so fast that everything's impacted the business model. You mentioned supply chain and cash flow. The business is right there, visible, and all these things are exposed, heightens the volume, as you said. And so everyone's seeing it happen, they can see the consequences. So this is like the most reality view of all time and any kind of is digital transformation, it will happen. So I want to get your thoughts on this because I've been riffing on this idea of the future of work, the word work, work places, work force, work loads and work flows. So they all have work in them. We thought about work flows and work loads, that's a cloud term and a tech term, but work places is the physical place now home. Work force are people, they're emotional stability, they're engagement. These things are all now exposed and all this new data is coming in. Now the executives have to make these decisions. This has really been a forcing function. So for example, I'm sure you agree with all that, but what's your reaction to that because this big is up challenges that customers are facing. What's your thoughts on this massive reality? Yeah, this is where I think the other domain that is very important, which is most important for organizations if you have to be successful is really that employee or work force, the understanding. We talk about customer 360s, we have to talk about employee 360s and tie that to locations. And there were very few enlightened organizations, I would say, maybe three, four, five years ago who had said, we really do need to understand everything about employees, where they work from, what are the different locations they go to, whether it's home and whether it's the multiple office locations that the organization might have and started quite realistically in the healthcare organization. There's a large healthcare provider here in California who many, many years ago decided that they want to create an employee 360. And considering it's doctors, it's nurses, it's hospital technicians and so on, who move from one hospital to another different outpatient clinics. And we are in a disaster prone state. And what they said is, I need to build this data foundation about my employees to understand where and someone is at any given point in time and be able to trace them so that if there is, let's say an earthquake in one part of the state, I want to know who's affected and more importantly who's not affected who can go out and help. And we started seeing that mindset now go across every single organization. Organizations that said, hey, I was not able to keep track when the lockdowns were started, I was not able to keep track of which one of my employees were in the air at that time, crossing borders stuck in different parts of the world. So as much as we talk about product, customer, financial data, supplier data, employee data and an employee 360. And now with a lot of state and local governments creating citizen 360s has also now become top of mind because being able to pull all of this data together and it's not just your traditional structured data. We're also talking about all the data that you're getting the interaction data from folks carrying their phones, mobile devices, the swipes that people are doing in and out of locations, being able to capture all of that tight altogether. Again, we're talking about an explosion of volume, which I think is to your point, bringing in more automation with Claire with artificial intelligence machine learning techniques is really the only way to get ahead of this because it's not humanly possible to say as your data scales, we need to get the same linearly, the same number of people, that's not going to happen. So technology, AI has to solve it. Well, I want to get to AI in a second. I have someone on my list to ask you about Claire, get the update there. But you mentioned 360 view of business and the employee angles, definitely relevant. Talk more about this 360 business approach, how are customers approaching it across the enterprise? Certainly now more than ever it's critical. Right, so the 360s have always been around John and I think we've had these conversations about 360s now for the last couple of years now. And a lot of organizations have gone out and said, create a 360 around a particular, whichever one, a specific business critical domain that they want to create a 360 out of. So typically for most organizations, you're buying parts from materials from a supplier. So create a supplier 360. You really need to understand, is there risk there in the supply chain? Am I allowed to do business with a lot of these suppliers? It's data that helps them create that supplier 360. The product is always important, whether you're manufacturing your own or if you're a retailer, you're buying these from your suppliers and then selling them via your different channels. And then finally, the third one was always customers without which none of those organizations would be in business. The customer 360 was always top of mind. But, and there are ancillary domains, whether it's the employee 360, we just talked about finance 360, which are of interest maybe to specific lines of business. These are all being done in silos, if you think about creating a full 360 profile of your suppliers, of the products of the customers. The industry's been doing it now for a few years. But where this pandemic has really taught a lot of organizations is, now it's important to use that platform to start connect data, align all the way from your customers, their experience, all the way back to your suppliers and all the different functions and domains and 360s that it needs to touch. And the most, I guess real world example, a lot of us had to deal with was the shortages in the grocery stores. And that ties all the way back to the supply chain. And you're not providing your best possible customer experience if the goods and products and services that customers want to buy from you are not available. That's when organizations started realizing we need to start connecting the customer profiles, their preferences to the products or inventory all the way back down to suppliers. And our, for example, can we turn up production in a particular factory but maybe that location is under one of the most stringent lockdown conditions and we're not able to bring in or increase capacity there. So how do you get a full 360 across your entire business starting with customer all the way back to supplier? That is what we are saying, the end to end 360 view of a business or as we, those too many words, we just call it business 360. Yeah, it's interesting. And I've interviewed a lot of your customers lately and talking some of the situations around COVID, there's the pre COVID, before COVID, during COVID, now looking after COVID. Some have been very happy and well prepared because they've been using it to see Informatica and have done the work and are taking advantage of those benefits. I've talked to other practitioners who are struggling with trying to figure out how to architect because what your customers who have been successful have been telling me is that look, we're in good shape right now because we did the work prior to COVID and now they are being forced to have a 360 view not because it's like a holistic corporate mission, it's they have to, right? People are at home. So it's not like, hey, let's get a 360 view of the business and do an assessment and do better and enable things. No, no, no, there's business pressure. So they're enabled now new types of data is coming in. So again, back to the cataloging, back to the, you know, some of the things that you guys have been working on. How do you talk to your customers now that they're in COVID for the ones that have been set up before COVID and the ones now that are coming to the table saying, okay, I need to now get quickly deployed with Informatica while I'm in during the state of COVID. So I can have a growth strategy coming out of it. So I don't make these mistakes again. What's your thoughts? Absolutely. And, you know, and I think, you know, the whether they've, whether an organization has already a customer has already, you know, laid the groundwork as the foundation, you know, before the, before COVID and the ones who have, who are now, you know, moving full steam ahead because, you know, they're missing capabilities in those functions. The conversation is in reality, more or less the same, you know, because even for those who have the foundation, you know, what they're starting to see is new forms of data coming in, new forms of new requirements being placed on the, by the business on that infrastructure, the data infrastructure and being able to most importantly, react very, very quickly, you know, and even for those who are starting off right now from scratch, it's the same thing. It's, you know, need to get up and running, need to get the answers to this, to these questions, needs to get the, we need to get the problems to these solutions as soon as possible. And the team, I guess the talking points for both of those customers is really two things. One is you need agility. You need to be able to bring these solutions, you know, up to life and delivering as soon as possible, you know, which means that, you know, the capabilities, the solutions you need, but that's a cat, you know, bringing the catalog, understanding where your data is, you know, very, very quickly, your business critical information, how do you bring that in, all of that data in, integrate that data into a 360 solution, be able to, you know, make sure it's of the highest quality, enrich it, master it, create those 360 profiles by joining it to all of this interaction, transaction data, all that has to be done with the power of technologies like Claire with artificial intelligence, so that you are up and running in a matter of days or weeks as opposed to months and years, because you don't have that time. And then the other one, which is quite important is cloud, you know, because all this capability needs infrastructure, you know, hardware to run on. And we started seeing a lot of, let's say cloud hesitant or, you know, verticals, entire verticals now in the last two to three months, suddenly going from, yeah, cloud is maybe somewhere down the road as far as our future is concerned, but to now saying we understand that we have to go to a cloud when our technicians are not able to get access to our data centers, to add new machinery in there to take care of the, you know, the new demands, you know, that migration to cloud. So it's that agility and cloud, which really is, you know, the common theme when we talk to customers both. Yeah, and now more than I really need it. This is an important time. And it's going to be an inflection point for sure. There'll be winners and losers and people want to be on the right side of history here. Sure, I've got to ask about AI. Obviously, Claire's been a big part of it. Now more than ever, if you have bad data, AI can be bad too. So understanding the relationship between data and AI is super important. This is going to be critical to help people move faster and deal with more data as they're dealing with now. What's your thoughts on the role AI will play? Oh, AI has a huge role to play. It's already begun to play a huge role in our solutions, whether we start from catalog to integration to the 360 solutions. The first thing that AI can really do very, very well is, you know, we've gone from folks who said, you know, let's take supply chain. You know, there were maybe three sources of supplier data, you know, that used to come into, you know, creating a supplier 360. Today there are hundreds of sources. If you go all the way to the customer 360 and we're talking about 1,300, 1,400 different sources of data with 90% of them sitting up in the cloud. How is it humanly possible to bring all of that data together? First of all, understand where customer information is sitting across all of those different places. You know, whether it's your click stream data, call log data, you know, whether it's the actual interaction data that customers are having, you know, with the in store online, collecting all of that information and from your traditional systems, like CRM, ERP and billing and all of that, bringing all that together. First of all, you know, understanding where it is, catalog gives you that, you know, that, you know, Google for the enterprise view, right? It tells you where all this data is. But then once you've got that there, it also tells you what its relative quality is, what needs to be done to it, how usable is it? To your point of, if it's bad data, you know, at least what AI can do first of all is tell you these are, you know, unreliable attributes. These are ones that, you know, we feel can be enriched. And then, and this is where AI now moves to the next level, which is to start, you know, inferring what kind of rules, you know, that are in our, let's say, repository across integration, quality and mastering and bring and matching, bring all that together and say, you know, here you as the developer who's been tasked with making this happen, you know, in a matter of days, we are going to infer for you what you need to do with this data and then we will be able to go in and bring all these sources in, connect it, load it up into a 360 solution and create those 360 profiles that everybody downstream, whether it's your engagement systems and others. So it's really about that discovery, that, you know, automation, as well as the ability to refine and suggest new rules in order to make your data better and better as, you know, you go along. And that's really the power of Clare and AI. You know, I love the Google for the enterprise or data because the metaphor really is about finding what you're looking for, it's a discovery piece, as you said, to make it easy. And Google did make these defined things, which is what their search engine did. But if you look at what Google did after that, they had to have large scales. SREs is what they call them, site reliability engineers, one engineer for thousands and thousands of servers that was revolutionizing IT and cloud. You guys are kind of thinking the same way, data scale, right? So it's Google in terms of discovery, right? Find what you're looking for, catalog, you know, get it in, get it out, quest, make it available for applications. But you're kind of teasing out this other point with AI comes in, that's scale. Yes. That's super important, it's not your nuance, but it's key to the future. Absolutely, because, you know, when we are starting to talk about now, not just tens of millions of records, when it comes to customer data or product experience data and so on, we're already talking about organizations like Dell, for example, with our customer 360, with billions of records going in, which would be equivalent to the scale of, if you look at Google search engine business back maybe 10, 12 years ago. So yes, we are talking about within, in the context of a single organization or a single company, we're already talking about volumes of unthinkable, even five years ago. So being able to manage that scale, be able to have architectures, technologies that are able to auto-scale, and the advantage of course is now, we've got an architecture platform that has microservices, as loads start increasing, be able to spawn new instances of those microservices, seamlessly, again, this is another part where AI comes in. AI being able to say, in the old days it was somebody had to see that the CPUs were overloaded to about 100% before someone realized that we have to go out and do something about it. In this new world, with AI managing the ops layer, being able to look at, is this customer bringing in another, in a cloud world, in a SaaS world, bringing in a billion records that they want to push through in the next 10 minutes, be able to anticipate that, spawn the new infrastructure and the microservices, and be able to take care of that load, and then dial those back down when the work is done. This again, from an ops perspective as well, so we're able to scale instead of having, let's say a thousand SREs, I think to your example, John, have only 10 SREs to make sure that everything, look at the dashboard and make sure everything is going well. Well, you know, I've been covering you guys for a long time, you guys know that, and I'm a big fan, I've always have been a fan of the vision, and it's playing out large-scale data, large-scale discovery, fast and easy, integrating that into applications for business value. It's not just the data warehouse, and just park something over here, this is a mindset, it's a foundational enablement model, you guys have done an amazing job, and now more than ever, it's, I think, more understood, because of the pandemic. Absolutely, and people are making that direct connection between the business outcome, and the value of having this data foundation that does all the things we describe. Sure, it's great to see you, and Bummer, we couldn't be in person, but hey, you know, the pandemic hit, Informatica World went virtual, a lot of different events, I know you guys have a lot of things going on, virtually you're engaging well, everyone's working at home, not a problem. Most of the techies can have their homework at home, it's not a big deal, but you got remote customers, you guys are engaging with them, and congratulations, and great to see you. Same here, thank you so much. All right, Suresh Menon, he's Senior Vice President General Manager of Master Data at Informatica. Data is more important than ever, we're seeing it, this is a foundational thing. If it's not enabling value, then it's not going to be a good solution. This is the new criteria, this is where action matters, people who need data need to integrate into new workflows, new applications, across work courses and new workplaces. This is the reality of the future. I'm John Furrier with theCUBE, thanks for watching.