In performing their missions, Federal agencies produce records that are important business assets supporting Government operations. Agencies must manage their records throughout the records life cycle from creation through final disposition. By identifying and embedding records management requirements within their enterprise architectures, agencies will realize benefits such as compliance with relevant laws and regulations, consistent records management practices across the agency, improved customer service, and real cost savings.
3. Build records management requirements into agency information technology (IT) governance processes for capital planning, enterprise architecture, business process design, and the systems development life cycle.
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NARA, OMB, and the Federal CIO Council's AIC envision the RM Profile as a framework to ensure that agencies incorporate statutory records management requirements and sound records management principles seamlessly into agency work processes, enterprise architectures, and information systems. The RM Profile is a cross-cutting guide that uses relevant FEA reference model information (i.e., context and conditions) to help business process owners identify and integrate records management requirements into all aspects of agency business operations.
Objective 1: Use the FEA as the common Government-wide framework for identifying records management requirements. By combining records management policies and procedures with the foundation of the FEA reference models, the RM Profile promotes a standardized means of implementing records management in agency enterprise architectures across the Government. Every line of business in the FEA should incorporate records management requirements and functionality.
Objective 3: Build records management requirements into agency IT governance processes for capital planning, enterprise architecture, business process design, and the systems development life cycle. For agency IT managers and enterprise architects in particular, the RM Profile is a useful guide for building records management requirements into IT governance processes for capital planning, enterprise architecture, business process design, and the systems development life cycle.
RMSCs will allow the management of records to begin much earlier in the business or mission process. (Current solutions, such as records management applications currently on the market, are usually add-ons to agency business processes and IT systems, rather than integral elements of the processes and systems.) Records management services would be available to users within the agency's enterprise architecture from their point of creation or receipt and possibly within their native applications. This will allow more efficient and effective management of records throughout their life cycle.
The Technical Reference Model (TRM) provides a foundation to describe the standards, specifications, and technologies supporting business and service components and E-Government solutions. The model identifies the technology elements that collectively support the adoption and implementation of technical architectures, and provides the foundation to advance the re-use of technology and component services across the Federal Government through standardization.
The advantage to using components is that they are "plug and play" and re-usable in many different business processes within and across Federal agencies. Components promote adaptive and resilient agency enterprise architectures and the consistent application of business rules. Staff can share records, and information in general, more easily throughout the enterprise and across agencies. Exhibit 4.1 illustrates the utility of building an application using a CBA, in that agencies can implement components, and therefore services, in many different applications as stand-alone units of functionality, independent of business rules and data.
Component-based Architecture: an enterprise architecture based upon categorizing business, service, performance, technical, and data entities, at their lowest level, as components, then recognizing larger lines of business, service, and technology infrastructures as combinations of components, enabling the design of enterprise solutions using pre-manufactured components.
For example, data architecture might input daily marketing and sales data into applications like marketing dashboards, which then further integrate and analyze the information to reveal relationships between ad spend and sales by region. Your data strategy provides the framework within which data engineers make architectural decisions that meet business goals.
The Gartner Analytic Ascendancy Model defines four steps in analytical maturity. Organizations typically start with descriptive and diagnostic analytics to understand what happened and why. Analytical maturity comes when the organization transitions to predictive analytics that use data to answer what will happen. Organizations in the final stage of maturity use prescriptive analytics to achieve predetermined results. A data strategy thus lays out a detailed plan to help your organization move from making decisions based on foresight instead of hindsight. It lays the foundation for implementing advanced technology like artificial intelligence (AI) and machine learning (ML) for improved business intelligence.
Successful data strategies typically include plans for both data and analytics management within an organization. Data analysis requires existing datasets as input for ML and AI software. An enterprise data strategy aims to minimize bias by outlining the best datasets to use for analytics and how to train employees in data operations. For example, suppose your organization plans to use AI to sort job applications automatically. In that case, you will need to carefully select a diverse dataset of past and present employees to avoid creating unconscious bias in the software.
Enterprise Architecture Requirements are required by federal law, IRS enterprise architecture principals, and vision and strategy mandates. The Enterprise Architecture Requirements initiative include programmatic, security, and privacy requirements. In addition, EA manages performance, functional, and system management requirements and provides traceability of data and functional requirements to business processes.
The IRS EA provides an overview of the Technical Architecture from the perspective of the three technical views in the Enterprise Lifecycle (ELC) methodology. It provides high-level perspectives of the application architecture, the data architecture, and the conceptual technology architecture views. While the business architecture covers concepts related to business process, organization, and location, the technical architecture covers concepts and strategies related to data, applications, and technology. The ELC Domains of Change view of the EA is really a summarization of all the technical components of the EA as they guide the development of systems. Business drivers defined in the business architecture lead to the elaboration of functional and technical requirements. These are then used to develop a set of abstract systems, which in turn define a set of conceptual target-state applications that manage enterprise data on enterprise-approved technology platforms. The common architecture decisions for technology, application, and data model views (that is, the Technical Architecture) are documented in the Application Architecture (Official Use Only), Data Architecture, and Conceptual Technology Architecture models provided by the EA. The goals of defining these common decisions are to: 2ff7e9595c
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