Kevin Tierney 0:06
Hello, welcome back to the Government Technology Insider Podcast. I’m your host, Kevin Tierney. And today we are going to continue our conversation with Dan Carroll field CTO for Cybersecurity, US Federal at Dell Technologies. Dan has joined us to discuss the many challenges and opportunities that federal agencies are facing as they look ahead towards a digital first future. In our previous installment, we hit on the growing importance of data for government agencies and how these agencies should approach setting priorities in 2022 and beyond. So now that we’ve outlined how strategic federal IT investments should look for the year, let’s discuss the driving forces behind a digital first government. We’ve heard a lot about the priorities. But let’s take a step back and address why this is an important step for federal government. And what can you tell me about how a digital first government transforms service deliveries in the short term and in the long term?

Dan Carroll 0:57
Yeah, absolutely. So what’s interesting with the digital first government, and what it’s done in the short term, is you can look around today and see real world and real time activities that have had an impact. If you look at how the government has leveraged elements of Digital First, to handle like disaster recovery. Right. FEMA is a classic example of an organization that has definitely done more to adopt and adjust to digital capabilities to understand. Okay, what is the, you know, there’s an area that’s under threat, what is the possible impacts that area based on, you know, upcoming storms that we know about that we may need to respond to? What are the emergency service capabilities in that area, and they use things like Google Maps, and and the weather service capabilities of commercial providers that provide, you know, historical data for that area, to help them and inform them about how to best respond to either threats that are occurring or threats that could be coming down the road? So the capability of the federal government to leverage what I would say is the large set of both federal and commercial IT assets that exist today to help improve their mission has been has been huge. And then from a where are they going in the future sense, you’re going to start looking at and seeing more mature AI/ML models, right AI and artificial intelligence and machine learning, and the capability to leverage the large amounts of data that are produced to help them build more predictive models to make better decisions on on how to improve and handle government and federal missions, that feeds into things like digital twin architectures, right. So a digital twin architecture is a scenario where you take real world telemetry and different log and alerting information from the environment, you port that all into a computer model, and you simulate a twin of that physical environment. And it’s, you know, the realities of living there into this digital model. And then you can run different simulations. McLaren Racing has done this to help them improve the design of their race cars, right, they take all the telemetry data from the track, from the cars, from the tires from the, from the weather that is going on around the track, and how it affects everything. And I can draw a similar model to that, when I look at something like the design for military vehicles for you know, a tactical environment, right, IoT and the edge and the amount of data that is created there by our military and DOD agencies and pulling all that data back and moving it into this type of digital model where they can then simulate the effects on a Humvee or Troop Carrier Vehicle. They’re able to make adjustments in design, and function of those vehicles within the model instead of having to physically reproduce all those things, and spend a lot, much larger amount of time and money to test and validate. So they’re able to accelerate that design and deployment model for those type of solutions.

Kevin Tierney 4:37
So you’ve described a good amount of the benefits that can come from that digital first government model. But what do federal agencies and organizations need to really embrace, you know, this approach, what infrastructure do they need to have lined up to take advantage of everything and to bring those benefits to their citizens?

Dan Carroll 4:56
So two things right. So the backbone and structure and blood that will feed this, this capability is going to be data. And as I mentioned at the beginning, I’ll say it again, data governance. There is massive amounts of data out there. But the federal government’s biggest challenge is how to effectively manage it, classify and gain access to it right. If you look within federal agencies in the DOD, there are a lot of restrictions about sharing government data. In order for them to effectively feed that type of data into AI and machine learning models to support things like digital twin and other future capabilities, they’re going to have to work to figure out how you get your arms around that data and more effectively pull it into these type of future IT capabilities to help you develop the tools and strengths that you’ll need to meet tomorrow’s it goals. So let me add to that. So from an infrastructure standpoint, things that AI/ML and digital twin and other things are dependent on is storage. Storage solutions that are high speed, high access, so gaining capability to access the data in an expedited manner wherever it lives. It could mean instead of, you know, like in a tactical scenario for the DOD, or for a tactical scenario, for an organization, like Border Patrol, the capability to get that large amounts of data and process it at the edge where it is, and then send back the appropriate data to support your goals, that’s going to means that you have to have an effective data governance model at the edge, you have effective and appropriate compute capabilities at the edge, that your data transport effectively moves the right data from the edge back to your cloud, and core data center capabilities. And then within those, that you have the high speed compute, you’re going to want and need to turn that data and run it through your AI/ML models and other stuff like that, that the the engines have all of the different capabilities that you want to enhance and deploy.

Kevin Tierney 7:22
So as you say, there are a lot of really interesting technologies that can be used to enhance how federal agencies provide services to citizens. But how would integrating all of those solutions, how would that impact the way the federal government approaches data management?

Dan Carroll 7:37
So we’ve talked about standards baselining, and leveraging and coming to consistent standards on how the government handles data management from an IT perspective, I think is something that needs to have a stronger advocacy and push for within the federal government. Because right now, the way you know, traditionally, the way the government looks at data as they look at it as they should, from a security classification and protection profile, but not necessarily. How can I do that also from an IT, and IT enablement profile? Right? So like we’re talking about, okay, I know that this data for this mission, or this function has a certain sensitivity as it relates to its merit within the world that we live in. But how do I classify that and make it accessible and usable to help me with my AI mission in the wider federal government? Yeah, mission, right. So how do I fix it so I can share the right types of data across different agencies and divisions to enable all of us. So that is something that I think the government is trying to figure out right now. But I think it’s going to be critical for them in order for them to move forward with what I say is the future and far reaching goals around the digital future.

Kevin Tierney 9:02
Dan, and I conclude our conversation in part three of this podcast series, where we get at the heart of data management and federal IT and how agencies can bolster their data security with a modern data management system. But that is going to do it for us here today. To learn more about the best practices, lessons learned and proven strategies for using innovative technologies. To address the challenges faced by federal, state and local governments, please visit governmenttechnologyinsider.com. I’m Kevin Tierney. And until we meet again, so long.