>> Live from Washington DC. It's the Cube. Covering AWS Public Sector Summit. Brought to you by Amazon Web Services. >> Welcome to the Cube'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 the Cube. >> Thank you for having me. >> So, you are a twenty-five 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... When you say it that way it makes me feel very old. 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. You know in the last twenty years, we've seen an explosion in the amount of data that we were 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 if 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 that you're with. And others are very valuable data, that you cannot 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, meta data 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 surround it? Where's the security of the data? All those factors play into, when you're looking at data as an enterprise. >> Sanjay, talk about SAIC specifically. I mean in long history working with the government and many, many contracts with broad range of services. But now at 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 Washington DC for Public Sector? >> Fair enough. So the SAIC is almost a fifty year old company. 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 the whole gamut of IT services. And we've worked with almost every federal agency in the area, in the country. 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 old aging infrastructure that... 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 would be catastrophic for the US as a whole. So, where we are right now, as 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 consumer... That model of the Apple iStore... 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 UIUX models. That's where you're looking at different workflows being moved to the cloud. How do you handle all that? >> They used to be a government. They used to be a consumer of technology. Now they are a regulator of technology. That's what the discussions are. They're looking at using data and technology for their workload. 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? Cause, 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? The discovered needs to do better. Is it the procurement? Is it just awareness? (Sanjay laughing) What's your thoughts? >> That's a lot of questions. A lot of things going on there. 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 men 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. Managing and understanding that data is very critical. How do you use it to add value to what the government is 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. >> The world has changed for the government. >> The world has absolutely changed. >> 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 is already starting to become a more savvy buyer. Again. Remember the far, as when they talk about it, the federal acquisitions regulations. It's a massive volume that's probably, you know, a thousand 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 that 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 looking at things differently. You're starting to see CIO's demand different services. They almost cannot do it. The compete in storage powers necessary? It's way too hard to go the old traditional route. >> You know what's interesting Rebecca, we talk about data all the time. We just read Infomatica World, they're kind of a supplier. They do the catalog and stuff for here at Amazon. Multi clouds of big countries, so Amazon is one of the biggest cloud. Andy Jackson who was just on stage last night in Arizona at a conference. Talking about response on recognition. All these hot AI data issues. Everything is a data problem. Right? But, yet we talk about government, but it's not just government. It's public sector. It's federal. But it's also international nation states. Competitiveness. So, there's a lot going on in such a short period in time, where analytics and data are key part, around the future value. So, it's almost the whole world is twisted upside down, from just ten 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. >> So you're right. The explosion of data has really caused government... And in fact, every industry to change. More industries are becoming digital industries than when they were manufacturing ones You know, things like Uber, and all those industries that popped up because of the data. That's where 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 management act. The creation of CDOs in every agency. This is really pushing. The government is really recognizing, data is an asset. It's a value added asset, that they have to use better, to add value to the citizens life. To what they're providing. >> And it wasn't necessarily front and center on the... Quote, "data balance sheet". If you will.. Or the evaluation of data wasn't always looked at that way. >> No. >> Cause that changed 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 is now become and 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's 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. In fact almost all 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 it with folks. It's like, what does it mean? >> I don't know if 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? You know, 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. You don't modernize correctly, you might in fact mission. And when you're talking about thing like in the DOD, where that leads to potential, you know, in theater situations and problems. That's a big problem from the DOD side. In the civilian side of the house, same thing. If your taxes go up by forty five percent because someone messed up on the modernization side, that's a problem. So, we have to be careful. Every agency has a personal journey. 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 is, how do you do it? When do you do it? What do you attack first? Where do you look at the challenges and value adds are? Because everybody has to do it. Budgets are shrinking, and security is important. >> And workload has kicked around a lot. Applications used to be the old worry. Now an application sits on a server. It runs kind of monolithic. But, the applications are what... And the workloads are what really is the goal. Agency's got their own unique solution. That taxes is for taxes. Make that go better. So. Data and cloud, is different per workload. Per environment. Per mission. >> It very well could be. I think it's ubiquitous that there is 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 they are going with it. So, agencies like PTO, they're looking at, how do I more effectively our examiner's 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 about what you're seeing. For example AI. I mean this is all the buzz, and all the big technology shows that we go to around the country. And it's maturing... But 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 with the different types of tools, handling the different sectors of managing data. Storage is one we talk about all the time. Because you have 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 at 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 wide spread. Because, they're new technologies. I mean AI is where data was, like I said, twenty years ago. So, they're starting to understand, how do I use it. What do I use it for? You know that natural... That learning process that AI goes through. To say, "Okay, I'm going to make something more efficient." How do I do posturing 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 volume of data coming out of that. But to use AI to learn which vectors the next security threat's going to to come through? That's a pretty daunting challenge, and not an easy one. And you have to find used cases like that. So, artificial intelligence I think has a large promise in the world. There's image recognition that's working very very well. Image recognition and classification. Natural language processing to look at different core sets of data in the research community. Or, in the pattern community. Those are very good examples of how AI is being used today. But there's a long way to go. And there's a lot to be learnt still. >> There's a lot of technology behind storing, and one of our sponsors that sponsors the Cube, Rebecca's cohesity. They sponsor us and invest in events. I think, 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 to not only figure 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 it. 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 limitless now. Doing all of those things matter. I mean if you're waiting, even nowadays... If you're waiting even 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 cause it's too slow. That's the kind of area where we're in. When you look at the segmentation of data, nearline storage versus online storage. Well, the nearline has to be almost as fast as the online, cause 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 that... 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 Silicone Valley. (Sanjay laughing) 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 tax per dollars. Everybody is putting in there. And we want to make sure that we're doing right. To be fair. The government is looking at a fail fast prototype type models. That do work with, like you know, hackathons, and competitions. That really bring together public sector and private companies, like SAIC and others. To do different things that help kind of 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? So, we have something we called our innovation factory. Where we have contracted out with multiple Silicone Valley. So we bring that to us, and then we bring that to government. That way the government does not, you know, not precluded by some of the rules that they have. But those type of things really help, that public, private partnership... It has to happen. >> I just want to... On that point real quick. Then we got to break. >> 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 work force. >> Absolutely. >> Enforcing the change, within the government. Can you validate that? Can you see... Can you share your opinion on how that's impacting everyone? >> Absolutely. Since I joined government over, God, now it's over twelve or thirteen years ago. And I left four years ago. We've been talking about this cliff that's coming up in the human resources side of the house. Where thirty-five percent of the top tier leadership is retiring. That's all getting replaced by new folks entering the market. And all these folks grew up in the iPhone era. None of these guys do anything that is... They are all mobile. They'll work anytime, anywhere. >> Very impatient too. >> Very different mindset. >> Cut the red tape. >> Right. Very different mindset and 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 got to be ready for it. >> Great. Well Sanjay, thank you so much for coming on the Cube. >> Absolutely. Thank you for having me. >> We'll have more from AWS public sector. I'm Rebecca Knight, for John Furrier. Stay tuned. (theme music)