The desire to obtain value and justify investments from the different Information Systems in place in organizations has been around for a long time. Organizations constantly theorize and implement different approaches that provide some sort of alignment between their different business objectives and Information Systems. Unfortunately, the environments in which these organizations operate are often dynamic, constantly changing with influence from external and internal factors that require continual realignment of the Information Systems with business objectives to provide value.

When businesses evolve, leading to changes in business requirements, it is hard to know what direct Information System changes are needed to respond to the new requirements. Similarly, when there are changes in the Information System, it is not often easy to discern which business objectives are directly affected. Whilst the different Enterprise Architecture frameworks available today provide and propose some form of alignment, in their implementation, they do not show links between business objectives and Information Systems, i.e., indicating what Information System is directly responsible for different business objectives thereby allowing for anticipation and support of changes as the business evolves.

This thesis utilizes insights from Business Intelligence and uses the User Requirements Notation (URN), which enables modeling of business processes and goals, to provide a framework that exploits links between business objectives and Information Systems. This Business Intelligence - Enabled Adaptive Enterprise Architecture framework allows for anticipating and supporting proactively the adaptation of Enterprise Architecture as and when the business evolves. The thesis also identifies and models levels within the enterprise where responses to change as the business evolves are needed and the ways the changes are presented. The tool-supported framework is evaluated against the different levels and types of changes on a realistic Enterprise Architecture at a Government of Canada department, with encouraging results.

-- Daniel Amyot - 01 May 2014


  • The thesis is available online at http://hdl.handle.net/10393/31012
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Title Business Intelligence - Enabled Adaptive Enterprise Architecture
Authors Okhaide Samson Akhigbe
Type Thesis
Conference/Journal Title M.Sc. in Systems Science
Publisher University of Ottawa, Canada
Month April
Year 2014
Pages 155
Keywords Adaptive enterprise architectures, Business Intelligence, GRL, indicators, information systems, profile, URN
Topic revision: r2 - 02 May 2014 - 17:01:55 - Daniel Amyot
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