US Federal News Bureau

US Army Launches Unified Data Reference Architecture

UDRA serves as a framework for implementing data mesh principles at the systems level.

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Written by: CDO Magazine Bureau

Updated 4:47 PM UTC, Tue April 16, 2024

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Representative image. Source: U.S. Army

The U.S. Army has officially rolled out its Unified Data Reference Architecture (UDRA) 1.0, following its initial introduction late last year.

This launch marks a significant step in simplifying the Army’s data structure and enhancing the efficiency of data products across mission partnerships.

“After a lot of work and collaboration with industry, UDRA 1.0 is officially co-signed by [Assistant Secretary of the Army (Acquisition, Logistics and Technology] ASA(ALT) and CIO, and on the street,” wrote Jennifer Swanson, Deputy Assistant Secretary of the Army (Data – Engineering – Software) DASA(DES) in a LinkedIn post.

“This UDRA aligns with the Department of Defense (DoD) Data Strategy goals, (DoD) Chief Digital and Artificial Intelligence Officer (CDAO) data mesh approach, the U.S. Army Data Plan, and Decision-Driven Data Concept of Operations (CONOPS),” the Army said.

The Army’s Chief Data Officer (CDAO) and Army Data Board hold responsibility for the organization and formulation of data governance policies within the Army. UDRA does not aim to oppose or override their existing policies and directives. 

Instead, the UDRA serves as a framework for implementing data mesh principles at the systems level, facilitating the efficient and effective execution of Army CDAO data governance. Particularly, Computational Governance empowers systems to autonomously enforce the policies set forth by the appropriate data governance authorities.

Earlier this year, the Army revealed its plan to deploy Chief Data Officers (CDOs) across various commands to act as a point of contact (POC) for mission-critical data management, according to Breaking Defense.

Their roles will revolve around overseeing and managing data within their respective commands, making critical decisions on data sharing, curation, and retention.

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