In the intelligence community, perhaps more than anywhere else, delivering the right data to the right users – when they need it – is critical. The better agencies are able to do that, the better and more impactful their intelligence products will be. Edge computing technology involves a computing model where edge nodes are used to process and store resources closer to the end users rather than in a centralized location, creating a globally distributed data repository. Employing data mesh architectures, edge nodes are designed to support information-sharing in connected and disconnected environments, ensuring seamless access to data lakes for military and intelligence applications with added support and resiliency for local data processing. However, as this technology proliferates within the intelligence community, there are still many analysts who work in disconnected environments that could largely benefit from the potential speed enhancements a decentralized architecture can provide.
In these cases, the data mesh architectures used by edge nodes can enable rapid information-sharing capabilities in all network states driving both resilience and time-to-decision.
Challenge: Support Decision Making in Disconnected Environments
In edge environments – such as the battlefield or a ship in the middle of the ocean – leaders still need the ability to make decisions without assumptions. This requires accessing data on-demand. But even if an analyst is working in a connected environment, the ability to reduce the time from sensor to effect can still be critically important.
Enter: Data mesh architectures.
Approach: Leverage Content Delivery Networks Enabled by Data Mesh Architectures
Anyone watching Netflix knows you have access to thousands of hours of content – and anything you want is available at any time you want it. How is that possible? Netflix uses content delivery networks that cache its most popular shows at multiple edge nodes around the world. The result: You get access to your shows faster, you watch Netflix longer, they gather more data about you. These content delivery networks are made possible via a data mesh.
In the simplest terms, a data mesh is a decentralized method of storing data. It recognizes data as a product; it supports the notion of multiple users accessing data in a self-serve manner; it federates data governance and drives interoperability of data through standardization; and it facilitates the sharing of data across multiple domains within an organization.
The same principle applies for intelligence agencies. As an example, in the geospatial field, edge computing technology employs data mesh architectures and caches both data and applications that are in high demand among intelligence analysts working at the edge.
Inherently, a data mesh enables a dispersion of data. Rather than having everything in one location, your data can be broken up and distributed globally, which helps with speed and resilience. More importantly, if there's a disaster or any sort of impact to the edge node closest to you, that’s ok. You're not limited to one location to access the data you need; the mesh provides you multiple paths to receive this data.
Impact: Better, Faster, Always-On Intelligence
The result of this design approach is a thriving edge analytics function in a fully disconnected environment and greater resiliency across the board. Priority data – and more of it – reaches analysts at both the edge and working in traditional capacities faster and as they need it. It reduces the time between an analyst getting the data they need and being able to exploit it.
Data mesh architectures underpin a modern data dissemination approach, enabling analysts, delivering on the mission and reducing the friction that can be associated with accessing data. It supports data sharing with other intelligence community and Department of Defense partners by integrating and interfacing at the edge, agency-to-agency.
Said another way: With a data mesh architecture, you're buying time in a time-constricted environment. This decentralization has real, mission-critical value in that it moves data closer to the user and cuts transit time when mere minutes – or even seconds – matter.
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