 Live from Washington, D.C., it's theCUBE. Covering AWS Public Sector Summit. Brought to you by Amazon Web Services. Welcome to theCUBE's live coverage of AWS Public Sector here in our nation's capital. I'm your host, Rebecca Knight, along with my co-host, John Furrier. We are joined by Sanjay Sardar. He is the VP Modernization and Digital Transformation at SAIC, thank you so much for coming on theCUBE. Thank you for having me. So you are a 25-year veteran of data management. Why don't I start by asking you to sort of break down the principles of good data management. This is what we're here to talk about. Yeah, so yeah, and when you say it that way, it makes you feel very old, but no, I've done data management for a long time. The key to data management, some of the principles are understanding kind of what data you have, where it is, what's the value of the data. That's the key that everyone's trying to bring. In the last 20 years, we've seen an explosion in the amount of data that we are handling. So really, how do you get through all that data? How do you understand how to manage it? Where do you put it? And then really understand how to use it. What is that value of all of it coming through? Some of it is just machine data and noise that you're looking at that's important for certain aspects but doesn't really add much value to the overall working of the agency or organization you're with. And others are very valuable data that you can't really do anything with unless you manipulate it in some way or some fashion. So data management takes a lot of different practices and different ways to look at it. So we've been doing master data management, metadata management for a long time, which helps understand what that data is, but then what's the provenance of the data? What's the governance of data? What policies around it? Where's the security of the data? All those factors play into when you're looking at data as an enterprise. Julia, talk about SAIC specifically. I mean, the long history working with the government and many, many contracts, broad range of services. But now with the modernization focus, the conversation is about agility, speed, modernizing government, private public sponsorships, partnerships, responsibility and accountability. All these things are in a melting pot. What is SAIC like today? What's your specific role here in the Washington DC Republic sector? Fair enough, so SAIC is almost a 50 year old company that we've been around the government sector for about that long. We've done everything, we do everything from data management to software development to infrastructure and hardware. Pretty much a whole gamut of IT services. And we've worked with almost every federal agency in the area in the country. We've, from a modernization perspective, what we're looking at is the federal government is at this tipping point. We have a lot of legacy systems, we have a lot of old aging infrastructure that needs to be replaced, that needs to be upgraded and modernized. This is a national security issue. We're getting into a point where things, if they start failing, it'll be very catastrophic for the US as a whole. So where we are right now is we're trying to work with the government to bring in new technologies. As you said, it's a melting pot of things that are happening. Not only has data exploded, but the technologies that are being used have also exploded. You're seeing a massive consumerization happening. Biggest example is the Apple iPhone. When the iPhone came out, that consumers, that model of the Apple i-Store or being able to do everything from your phone is something the government has to get to. That's where you're looking at the UI, UX models. That's where you're looking at different workflows being moved to the cloud. How do you handle all that? Government used to be a consumer of technology. Now they're a regulator of technology. That's what the discussions are. They're looking at using data and technology for their workloads, so it's not so much a supplier-consumption relationship. They're much more active participants in the technology scene. The question is, do they really understand what's going on? Because if you don't understand it, you can't control it, you can't regulate it, you can't utilize it properly. This is the number one conversation around modernization. What are the key factors, in your opinion, that the government needs to do better? Is it the procurement? Is it just awareness, what's your thoughts? That's a loaded question. There's a lot of things going on there, yeah. And you're right. The government has become a consumer of technology. I mean, it used to be, back in the days when we were launching missions into space and putting man on the moon, the government was a leader in technology. Now with the commercialization, government has actually become a consumer of all these types of technologies and a creator of tons of data. So managing that data, and managing and understanding that data is very critical. How do you use it to add value to what the government's doing? And then further down the road to what the citizens are doing. How do you add value to the citizens' life? In doing that, there's a lot of different things that have to come into play. One, as I said, technology is a big part of it. Understanding what technology to apply. It's not just about replacing technology. That's not what modernization is. Modernization is how do you change and digitally transform your workloads, your workflow, how you do business, that's really where the value add comes in. To get there, yeah, you have to look at the technology, you have to look at the procurement practices, you have to look at different pricing and consumption models that the government hasn't been used to in a long time. When you look at these traditional contracting models, they may not apply to some of the new ways of consuming technology for the government. The world is absolutely changing. What will it take though for the government to become a more savvy buyer? I mean, what are some of the things that? I think the government's already starting to become a more savvy buyer. Again, remember, the FAR, as when they talked about it, the Federal Acquisitions Regulations, it's a massive volume that's probably 1,000 pages long. So there's a lot of opportunity to interpret that correctly. Where we're changing now is how do you interpret it? So there's fair practices for all competitors in the government market. And you're starting to see that. You're starting to see procurement officers look at things differently. You're starting to see CIOs demand different services. They almost cannot do it. The computing storage power is necessary. It's way too hard to go the old traditional routes. It's interesting, Rebecca. We talk about data all the time. We just read Informatica World. They're kind of supplier. They do the cataloging stuff. We're here at Amazon, multi-clouds of big conferences. So Amazon's one of the biggest cloud. Andy Jassy was just on stage last night in Arizona at a conference, talking about responsibility around recognition. So all these hot AI data issues, everything's a data problem, right? But yeah, we talk about government, but it's just not just government, it's public sector. It's federal. But it's also international nation-state competitiveness. So there's a lot going on in such a short period of time where analytics and data are a key part around the future value. So it's almost the whole world has twisted upside down from just 10 years ago. Oh, easily. Your thoughts on what's going on and what the public sector community, because a lot of these environments don't have huge IT budgets. But now we're seeing things like ground station, satellite, new stuff happening. Yeah, NASA, NOAA, yeah. Yeah, so you're right. This explosion of data has really caused government, and in fact, every industry to change. More industries are becoming digital industries than where they were manufacturers. Things like Uber and all those industries that popped up because of the data. That's what government is also turning into. They are starting to understand that all the decisions that government makes has to be done through a data-driven model. They have to have this evidence-based decision-making process, and you're seeing that because of the federal data practices, the data act, data management act, the creation of CDOs in every agency. This is really pushing the government's really recognizing data is an asset. It's a value-added asset that they have to use better to add value to the citizen's life, to what they're providing. It wasn't necessarily front and center on the quote data balance sheet, if you will, or the valuation of data wasn't always looked at that way. It was actually the perspective, understanding, and- It's a huge shift, like I said. When you look at the rise of the CDO, the Chief Data Officer in the federal government, that's a really big indication that data has now become looked at as an asset. The CIO was responsible for all the technology and they're governing all the technology and they're the owner of that. The Chief Data Officer is now doing the same thing from the data side. The governance, the policy, the usage, the cooperation across multiple agencies, multiple countries, as you said. Are agencies deploying CDOs across all agencies now? I think you're seeing more and more of the CDO being put out there. So, in fact, almost all of the agencies that I work with have a CDO already in place or are hiring one in the next three months. Why is modernization such a contentious topic? Is it because everyone has a different definition of what modernization is? It seems to be contentious when I talk about with folks is like, I mean, what does it mean? I don't know modernization is a contentious topic in the sense of I think everybody recognizes that they have to modernize. It's how do you do it? We are in a world where we have so much legacy infrastructure, legacy applications that are tied so closely to mission. There's a risk of how do you modernize? If you don't modernize correctly, you might affect mission. And when you're talking about things like in the DOD where that leads to potential in theater situations and problems, that's a big problem from the DOD side. In the civilian side of the house, the same thing. You know, if your taxes go up by 45% because you know someone messed up on the modernization side, that's a problem. So we have to be careful. Every agency has a personal journey. What SAIC, when we look at this, working with our partner systems, we look at an agency's personal journey. Everybody's going to do it differently. So I think the contention comes in as how do you do it? When do you do it? What do you attack first? Where do you look at the challenges and value ads are? Because everybody has to do it. Budgets are shrinking and security is important. Workload is kicked around a lot. Applications used to be the old word. We have an application sits on the server. It runs kind of monolithic, but the applications and the workloads are what really is the goal. Agencies get their own unique solution that taxes is for taxes, make that go better. So the role of data and cloud is different per workload, per environment, per mission. Very well could be. I think it's ubiquitous that there's a compute and storage factor that everybody has to use. But the workloads that really transform the digital mission are very different from agency to agency. So you have to look at what are they valuing and where are they going with it. So agencies like PTO, they're looking at how do I more effectively use our examiners time versus agencies like NASA, which are looking at how do I do higher level compute and HPC type work. So. One of the things you talked about when we first began our conversation is not only the explosion in data, but the explosion around the technologies and tools that are used to store and manipulate and execute decisions on the data. Can you talk a little bit about what you're seeing? For example, AI. I mean, this is all the buzz that all the big technology shows that we go to around the country. And it's maturing, but it's certainly, there's not a lot of adoption in the government. So you're right. Along with this data explosion, we've seen a technology explosion and the different types of tools handling the different sectors of managing data. Storage is what we talk about all the time because if so much data, you can't actually access all that data at once. So there's segmentation in the data that you have to look at. Companies like Cohesity are doing a good job of handling and managing that segmentation in their hyper-converged storage architectures. But we're also looking at in the AI world, yes, AI is artificial intelligence, deep learning, machine learning. These are all techniques that are working very well for certain types of data usage and data problems. But the adoption is not as widespread because they're new technologies. I mean, AI is where data was, like I said, 20 years ago. So they're starting to understand, how do I use AI? What do I use it for? That natural, that learning process that AI goes through to say, okay, I'm going to make something more efficient. How do I do clustering of that data? Where do I actually use that? When you have large volumes of data, security, for example, is a great example. When you look at security logs, lots of volumes of data coming out of that. But to use AI to learn which vectors the next security threat's going to come through, that's a pretty daunting challenge and not an easy one. And you have to find use case like that. So artificial intelligence, I think has a large promise in the world. There's image recognition that is working very well, image recognition and classification, natural language processing, to look at different core sets of data in the research community or in the patent community. Those are very good examples of how AI is being used today, but if there's a long way to go and there's a lot to be learned still. There's a lot of technology behind storing it. One of our sponsors that sponsors theCUBE, Rebecca's Cohesity, they sponsor us at AWS events that we always thank the sponsors. They're in the business of scaling up storage. So it's not that easy to store it. So you have not only just figuring out the business model behind how to use the data, there's also the technology around storing it cleanly without hiring away. Talk about the dynamics around tech in terms of managing the data. Well, so as you said, there's a storage aspect of it. There's a retrieval aspect of it. There's a time aspect of it. All of that leads to, yes, data is so valuable and so large and so woman is now doing all of those things matter. I mean, if you're waiting through, even nowadays, if you're waiting three seconds for any response to come back, you're going to look at it and be like, I got to change my computer out because it's too slow. I mean, that's the kind of area where we're in. So when you look at the segmentation of data, near line storage versus online storage, well, the near line has to be almost as fast as the online because now we're looking at things where, as you put it, the AI models are looking across vast amounts of data. They're looking at everything. How do you do that well? So all of that technology factor plays into it. One final thing, and this is just about the mindset of the government right now because what you're talking about is a lot of exploration and a lot of experimentation that's needed. How would you describe sort of the federal approach to this? I mean, in fail fast is the motto of Silicon Valley but that's a lot harder to do in the government when lives are at stake. Well, yeah, and it's cautious to be fair. It's not only lives at stake but it's taxpayer dollars, right? We're not, these are, everybody's putting in there and we want to make sure that we're doing right. Now, to be fair, the government is looking at a fail fast prototype type models that do work with hackathons and competitions that really bring together public sector and private companies like SAIC and others to do different things that help with this technology explosion. So for example, we work with USDA, we did multiple hackathons for precision agriculture. That kind of work is, it helps understand what do we need to do with precision agriculture? What tools make sense? We go to, so we have something called our innovation factory where we've contracted out with multiple Silicon Valley so we bring that to us and we bring that to the government. That way the government is not precluded by like certain, some of the rules that they have but those type of things really help that public-private partnership, it has to happen. Just on that point real quick, I know we got a break but one of the things that you mentioned there is that this new generation kind of mindset. Talk about that dynamic because there seems to be a new generation, digital natives emerging into the workforce and forcing the change within the government, can you validate that or can you share your opinion on how that's impacting everyone? Absolutely, I mean since I joined government over God, now it's over 12 or 13 years ago and I left four years ago but we've been talking about this cliff that's coming up in the human resources side of the house where 35% of the top tier leadership is retiring. That's all getting replaced by new folks entering the market and all of these folks grew up in the iPhone era. None of these guys do anything that, they're all mobile, they're work anytime, anywhere. They're coming in with a very, very different, they're very, very different mindset, but very different mindset in how to make government work and that's a good thing. That kind of shake up is actually necessary as these folks grow into leadership positions, they're going to change how government works so we've got to be ready for it. Great, well Sanjay, thank you so much for coming on theCUBE. Absolutely, thank you for having me. We'll have more from AWS Public Sector. I'm Rebecca Knight for John Furrier, stay tuned.