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Federal Enterprise Architecture Framework (FEAF): Data Reference Model (DRM)
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Enterprise Architecture (EA) conveys management best practices for positioning business and technology resources to fulfil strategic goals, enhance Organizational Performance, and guide departments to achieve their core missions more successfully via Operational Excellence.
The Federal Enterprise Architecture Framework (FEAF) realizes this goal for U.S. Federal agencies and assists systems surpass interagency boundaries. FEAF facilitates through documentation and information, and conveys a summarized outlook of an enterprise at various tiers of scope and detail.
The FEAF comprises of 6 interconnected Reference Models, linked through Consolidated Reference Model (CRM), each relating to a sub-architectural domain of the FEA framework.
Data Reference Model (DRM) is a FEA tool for ascertaining the data that the Federal government has and the process through which that data will be shared when business/mission requirements occur.
DRM is propounded as a theoretical framework from which actual implementations may be derived.
DRM offers a uniform way to describe, categorize, manage, share, and reuse data/information within and across the Federal government. DRM also enables detection and communication of core information across organizational boundaries.
What DRM is not is static and invariable nor is it a data management manual for how to build and maintain data architectures. It is neither a pan-government conceptual data model nor an all-embracing / fully attributed logical data model. DRM is not supposed to be a comprehensive collection of XML schemas or a substitute of prevailing data structures within the agencies.
DRM works in consonance with other reference models in various ways. For example, it identifies opportunities for strategic coordination through relationships among data sources by linking with Performance Reference Model (PRM) while improving business processes and decision-making performance through data sharing with Business Reference Model (BRM).
Data Reference Model arrangement is demarcated by a 3 layered hierarchy. The 3-layer arrangement of the Data Reference Model delineates domains, subjects, and topics.
- Domains – Uppermost level of the hierarchy comprises of 4 Domains.
- Subjects – Central level of the hierarchy covers 22 Subject elements.
- Topics – Lowermost level of the hierarchy consists of 144 Topic elements.
DRM refers to data and information required to execute Federal business and mission functions. In order to assist agencies in consistently categorizing, describing, and exchanging their data, there are 3 fundamental method areas associated with the DRM:
- Data Description
- Data Context
- Data Sharing
Let us delve a little deeper into the DRM methods.
Data Description
Data Description offers an approach to consistently arrange, portray, and share data. Customarily, Data Description was exclusively concentrated on arranging and describing structured data. To tackle the challenge of unstructured data, DRM Data Description section was revised to focus on Metadata.
Metadata is broadly classified into 2 types, business or technical.
Data Context
Data Context is any information that gives added sense to data and a perception of the reason for which it was created. Data Context permits Data Governance and forms the basis for exhaustive Data Description. Data categorization methods such as Data Asset Catalog and Information Discovery and Search portray common data architecture artifacts.
Data Sharing
Data Sharing concentrates on architectural patterns for sharing and exchanging data. Data Sharing assists in retrieving and swapping of data, where access involves supplementary requests and exchange involves permanent, repeating transactions between interest groups.
Interested in learning more about the Data Reference Model? You can download an editable PowerPoint on FEAF: Data Reference Model (DRM) here on the Flevy documents marketplace.
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About Mark Bridges
Mark Bridges is a Senior Director of Strategy at Flevy. Flevy is your go-to resource for best practices in business management, covering management topics from Strategic Planning to Operational Excellence to Digital Transformation (view full list here). Learn how the Fortune 100 and global consulting firms do it. Improve the growth and efficiency of your organization by leveraging Flevy's library of best practice methodologies and templates. Prior to Flevy, Mark worked as an Associate at McKinsey & Co. and holds an MBA from the Booth School of Business at the University of Chicago. You can connect with Mark on LinkedIn here.Top 10 Recommended Documents