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Introduction Organizations need to be aligned with the wants and needs of clients in order to deliver value-added products. To do this, organizations attempt to engage the business with a mindset of continuous improvement through business process management. Business process management has four key components:
1. Process engine – a platform for executing process-based applications
2. Business analytics – identifying business trends through reports and dashboards
3. Content management – allows a system to store secure documents, files, etc.
4. Collaboration tools – removes communication barriers via forums, message boards, etc.
Senior executives now want business run on data-driven decisions (Hopkins et al 2011). For the purpose of this paper we will focus on business analytics and how technology is used to create business intelligence for the company. Enterprises are increasingly adopting BI technology to boost the analytical and decision-making processes that underpin their overall success (Decker 2010).
Business intelligence is not a new concept; it was derived from computer-aided models during the 1970’s and 1980’s. Howard Dresner (formerly of the Gartner Group) is considered the father of business intelligence and saw the need for companies to create performance-directed cultures in which the business and IT worked together. Adoption of BI technologies is likely to double in the next five years (Brannon 2010).
Business intelligence (BI) is a technology-based decision support system used to serve different organizational levels in management, operations, and planning. It uses computer-based information for spotting, digging out, and analyzing data. Business intelligence (BI) systems are widely viewed as the innovation that can leverage the wealth of data encapsulated in an enterprise system and support the anticipated transformation to a

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