The most common mistakes made by companies attempting to implement business intelligence (BI) solutions today can be traced directly to a lack of understanding of the analytic end users. Very little energy is spent on understanding "how" the end users will use the BI solution; rather, development cycles and user surveys concentrate on "what" the BI solution should do. The key to a successful business intelligence solution implementation is aligning the solution to the appropriate end-user constituencies. To do this, companies must first create an analytic end-user profile, defining who the users are (e.g., information technology [IT], power users, business users, casual users, extended enterprise users) and whether they are consumers of information or producers of analysis. Once defined, this master profile can be used to associate analytic functionality –­ such as OLAP, data mining, statistical analysis, analytic reporting, visualization, enterprise reporting, scorecarding and metrics –­ to individual groups of users, increasing the likelihood of a successful BI implementation. Lacking an appropriate profile of the different analytic end users ­– including criteria for usage –­ IT will continue to build great solutions that are used by no one.

Companies both large and small are implementing BI solutions to gain a competitive advantage by analyzing the data captured within enterprise applications (ERP, CRM, SCM, finance), data warehouses and data marts. The conventional approach used to develop and implement these BI solutions has two distinct phases:

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