dc.contributor.author |
Angel, Hope |
|
dc.date.accessioned |
2011-07-06T16:08:51Z |
|
dc.date.available |
2011-07-06T16:08:51Z |
|
dc.date.issued |
2011-07-06 |
|
dc.identifier.uri |
http://hdl.handle.net/1794/11384 |
|
dc.description |
This 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]. |
en_US |
dc.description.abstract |
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_US |
dc.language.iso |
en_US |
en_US |
dc.relation.ispartofseries |
AIM Capstone 2011;Hope Angel |
|
dc.subject |
Data mining |
en_US |
dc.subject |
Business intelligence |
|
dc.subject |
Information quality |
|
dc.subject |
Information quality assurance |
|
dc.subject |
Competitive advantage |
|
dc.subject |
Knowledge discovery |
|
dc.subject |
Data analytics |
|
dc.subject |
Data warehousing |
|
dc.subject |
Applied Information Management |
|
dc.subject |
AIM |
|
dc.subject |
Data |
|
dc.title |
Identifying and Prioritizing Information Quality Dimensions for Assurance in the Pre- Processing Stage of Data Storage for Business Intelligence |
en_US |
dc.type |
Other |
en_US |