Overview of how enterprise architecture translates business vision
In these sections, the goal is to cover an overview of how enterprise architectures, business vision, and strategy translate together and produce enterprise IT solutions. Enterprise architectures are well understood frameworks evolved overtime to assist large organizations to adopt processes and guidelines that are well established (Overview of EA, n.d). If followed correctly, they can provide IT professionals with proven methods to manage and design enterprise systems. First, the types of enterprise architecture domains will be highlighted and compared at a high level. These include business, data, application, and technology architectures. An elaboration on the architecture domains and how cloud computing fits in each of these domains will be explored.
Types of Enterprise Architecture
The first to discuss is the business architecture. This domain investigates how businesses utilize a cloud framework to encompass the requirements for the organization (Overview of EA, n.d). The primary focus is to ensure all business constraints are captured in requirement gathering sessions. If these requirements are gathered correctly, then the next phases can occur with greater success. This would allow better business and IT alignment, increased business agility, gains in business process efficiencies, and reduce time to market. Generally, business architecture can sometimes be the most difficult to capture, as business and IT are known to communicate at different levels.
Data Architecture explains how businesses can place a framework around their data environment (Overview of EA, n.d). Since the power of data is growing every year, how an organization ingests, cleanses, organizes, and consumes data can determine its ability to succeed in its industry. Organizations have to consider the cost of storing data, securing the data, managing the appropriate number of compute resources, and selecting the appropriate data stores. Fortunate for businesses, the cost of storing data is decreasing every year.
Big data is specifically defined where a business is required to consume and analyze high-volume, high-velocity, and high variety of data. Big data pushes the limitations of tradition data processing tools and computing powers of existing servers. As all businesses are investing heavily in their business intelligence platforms, data is multiplying at rates that are too fast for businesses to manage. Businesses are forced to transition from having an architecture that is not backward-looking, but able to see the business as it is now.
Application Architecture discusses cloud application frameworks which outline the entire application: endpoints, connections, dependencies, and required libraries (Overview of EA, n.d). As CTOs and CIOs are challenged with transforming their business and become more agile, they focus on the risks and benefits of application modernization projects. Some risks include the high maintenance costs, misalignment of technology and business, lack of resources with legacy or cloud skillsets, and lastly, slow development speed causing delays and missed project deadlines. The benefits of migrating include lower costs, closer alignment to business and IT, and improved portfolio synergy. Considering migrating applications to the cloud takes the existing EA framework for application architecture and adjusts it slightly to ensure that the application works equal to or better on the cloud than it does on-premise. This can be achieved by appropriately performing an application assessment prior to migration.
The last and final enterprise architecture framework compares the technology frameworks for on-premise and cloud solutions. This framework ensures that IT has the correct guidelines when making decisions on selecting cloud solutions to meet the demands of the businesses’ current and future needs, as well as is compatible with current on-premise technologies (Overview of EA, n.d). Furthermore, this framework provides the ability for IT to place governance around connecting on-premise and cloud resources, how multi-cloud applications and resources integrate, what services not to use, and many considerations.
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