Five steps the Department of Defense should consider for its data management strategy

The Department of Defense has laid the groundwork for better data management and governance through its Data Strategy and subsequent Data Executive Orders, but there are still improvements to be made.

The DoD Data Strategy focuses on operationalizing data to improve decision-making across the DoD enterprise, which will support mission operations and maintain military advantage.

As part of its strategy, the DoD has established a Chief Data Officer (CDO) to oversee the data governance process, data standards and policies, and improve the sense of data within the DoD workforce. . The DoD Data Strategy also created a CDO Board and Federated Data Catalog for more unified data management. These steps are crucial in determining what data is sensitive and needs to be protected, as well as who can access it and under what circumstances.

In the DataOps and DevOps spaces, the focus has been on balancing security and user access requirements while removing operational bottlenecks. This is accomplished through automation workflows, which simplify data access across cloud architectures. Therefore, the cost and elasticity advantages of available storage and compute will accelerate the modernization of analytics. To do this, data teams must use the DevSecOps approach, which ensures the right balance between data security and usefulness.

To accelerate data modernization, DoD personnel need the right tools, environment, resources, and access to establish data-driven programs. Successful data-driven agencies create enterprise services for data discovery and establish guidelines and safeguards to ensure costs, protection of sensitive information, and legal compliance are effectively managed.

There are opportunities for the DoD to learn these best practices and apply them within agencies. Here are five areas that DoD decision makers should consider when implementing a data management strategy.

Bring in highly skilled experts from outside the DoD who can introduce new ideas and lead innovative efforts.

The DoD assesses the talent pool to identify civilian and military data professionals, the fluidity of data across the DoD, and critical skills gaps within its workforce. The goal here is to establish additional public and private partnerships – especially those outside the typical entrepreneur community – to quickly overcome the perceived shortfall. This presents opportunities for DoD leaders to gain new expertise.

Provide additional innovation funds or special projects to DoD components to develop prototypes and test innovative approaches.

The DoD and military services already use Other Transaction Agreement (OTA) contracts to build prototypes. OTAs cut red tape and speed up the prototyping and delivery of new military capabilities. Agencies should evaluate OTAs and other acquisition and funding programs to build innovative prototypes.

Encourage attendance at conferences and events that highlight successful candidates.

Conferences that provide the latest information on data preparation and analytics, data governance and compliance, data tools, and the transition to data-driven government are on the rise. DoD personnel should attend private and public sector events to stay informed of the latest trends and technologies that improve data-driven decision making.

Invest in workforce training for the cloud.

To operationalize data, agencies need modern cloud infrastructure and native services to catalog and automate the data discovery process while harnessing the power of artificial intelligence (AI) and machine learning technologies. The DoD is moving from a single cloud provider to a multi-cloud provider with the CIA’s Joint Warfighter Cloud Capability (JWCC) contract and Commercial Cloud Enterprise (C2E) contract. This change will provide more services and increase the digital footprint of defense agencies. While the DoD will see benefits during this transition, it will also increase the burden on IT administrators and security teams, who will need more training. Making workforce development a priority is essential.

Automate data access for analytics at the data layer with a focus on zero trust.

Historically, zero trust has focused on automation and continuous network and application monitoring. This works for transactional system architectures, but leaves a security hole in analytical environments, as data from source systems is collocated. The only way to ensure proper access is to deploy granular, attribute-based access control (ABAC) security models at the data layer. This design should consider not only user attributes, but data attributes as well, while using tools to automate access to relevant data, governance, and privacy policies at scale. Role-based access control lacks the necessary granularity and requires significant effort to establish and maintain. By automating access, agencies can reduce current DataOps bottlenecks affecting users.

The Growing Role of AI and the Future of DoD Data

Defense leaders are realizing the promise of applying AI in their agencies as priorities have shifted to nearby adversaries. The successful application of AI has identified cancer cells in medical imaging, and the DoD has had success with predictive maintenance for airplanes and trucks. However, images from remote sensors on satellites or unmanned aerial vehicles present their own challenges, including weather or camouflage. DoD officials need to be realistic about what AI can do. To that end, the DoD’s Joint Artificial Intelligence Center (JAIC) office is launching the Artificial Intelligence and Data Accelerator (AIDA) to help DoD commanders better understand their data to improve decision making. operational decision-making and identify combatant command use cases. The goal here is to advance what is possible with AI while applying the technology to solve operational challenges within the DoD.

DoD agencies are currently deploying a zero-trust architecture on government and partner networks. If the DoD doesn’t find a way to balance security with utility, its data problems will only grow. Automation, cloud services, an authoritative source for managing data access, and a highly skilled workforce are key ingredients in providing the tools analysts need to optimally manage data of the agency.

Danny Holloway is the Director of Public Sector Technology at Immuta.

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