Business Architecture definition and relations within the Enterprise Architecture framework Sample Clauses

Business Architecture definition and relations within the Enterprise Architecture framework. The definition of Business Architecture should be included in the general framework of Enterprise Architecture. EA is the process of translating business vision and strategy into effective enterprise change by creating, communicating and improving the key requirements, principles and models that describe the enterprise’s future state and enable its evolution (Gartner 2012). Therefore EA can be defined as the reference model by which an organisation operates and is structured to achieve its objectives, whereby each lower layer is governed by a higher one by means of a requirement chain and of modelling processes. In this way, it is possible to move from a conceptual representation to increasingly operational and technological levels (Xxxxx and Xxxx 2012). In other words, Enterprise Architecture is about understanding all the different elements that make up the enterprise and how those elements interrelate. It is an approach to enabling the vision and strategy of an organisation, by providing a clear, cohesive, and achievable picture of what is required to achieve this target (Statistical Network BA Team Project 2013). As agreed within the Statistical Network and shared among CSPA, EA can be split in four different layers (see Figure 1), with the following definitions: 1. Business Architecture (BA) that covers all the activities undertaken by an NSI, including those carried out to conceptualise, design, build and maintain information and application assets used in the production of statistical outputs. BA drives Information, Application and Technology Architectures for an NSI. 2. Information Architecture (IA) that classifies the information and knowledge assets gathered, produced and used within the BA. It also describes the information standards and frameworks that underpin statistical information (e.g. GSIM, DDI, SDMX). IA facilitates discoverability and accessibility of available data and metadata, leading to greater reuse and sharing.
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