BI Solution Architecture
The end-to-end process of your data lifecycle is defined by your Business Intelligence Solution Architecture. This plan and framework outline how data is created, moved, stored, accessed, visualized, secured, governed, and managed within your organization.
Having a visions and a map of your technology and data eco-system is a very powerful tool for getting organized and staying on track with your goals and your purpose. Having the correct architecture is also critical to your organizations success; a best practices architecture can position you for extreme comparative advantages over your competition when it comes to leveraging your core value proposition. Whereas, the wrong architecture can leave you vulnerable to operational risk, inefficiency, and outright obsolesce. Technology can boost marginal productivity if it is deployed properly and effectively.
Bi Solution Architecture gives you the full view and understanding of your data eco-system. It will help you understand which systems and people are managing what data and how they are using it. It will help you understand that stages, phases and level of control and access in your data management process. Mapping out your solution Architecture from a conceptual level will allow you to align and coordinate better across your organization because people will be able to see and better understand what is happening at every stage and who is responsible. It is a map of your organizations technology solutions and how they interact.
BI Solution Architecture takes the form of systems and process mapping, of doing research to determine what solutions are available, and of defining the current environment so that potential future state solutions will be feasible within the current context of your organization technical environment and culture. There are tools, exercises, and best practices for developing the BI Solution Architecture. There should be collaboration with respect to the proper RACI Model (Responsible, Accountable, Consulted, Informed) to make sure all the aspects of your organizations data life-cycle, processes, and risks are taken into account.