Successful business intelligence (BI) and data warehouse projects share at least one common characteristic: explicit consideration of risk. BI projects are peppered with risks, from data quality to analytic value and scalability. Furthermore, these risks often bring entire projects to a halt, leaving planners scrambling for cover, sponsors looking for remedies, and budgets wiped out.

This white paper describes two methods for minimizing the risk associated with BI iterations: Rule-Based Audits and Proof-of-Concepts. Independently used, each will help you clarify and better understand risk points associated with your project. Implemented together, they represent a continuum of risk mitigating techniques. Their presence in projects is a demonstration of the professionalism and discipline found only in seasoned, successful BI teams.