Angel, Hope2011-07-062011-07-062011-07-06https://hdl.handle.net/1794/11384This paper was completed as part of the final research component in the University of Oregon Applied Information Management Master's Degree Program [see htpp://aim.uoregon.edu].As business intelligence systems increase the amount of information stored in data warehouses, quality of content becomes more critical (Fisher, Lauria, Chengalur-Smith, & Wang, 2008). Selected literature published between 2001 and 2011 is analyzed to define key dimensions of information quality for consideration in the pre-processing stage, before data reach the warehouse, to ensure maximum quality assurance. The goal is to provide a framework to prioritize dimensions that align with business intelligence goals and objectives.en-USData miningBusiness intelligenceInformation qualityInformation quality assuranceCompetitive advantageKnowledge discoveryData analyticsData warehousingApplied Information ManagementAIMDataOther