data quality dimensions

This is a very well written article on Data quality .
http://www.information-management.com/issues/2007_58/master_data_management_mdm_quality-10015358-1.html?ET=informationmgmt:e963:2046487a:&st=email

The most challenging aspect in any MDM initiative is to bring awareness among business and IT community about data qualty. In my current assignment , I interviewed few Data stewards and realized that data collection process is still not streamlined in many industries. Data is extracted from spreadsheet, various design documents before entering it into the system. In a engineering organization, a proper SDLC cycle is followed to design,develop,test and release the actual product. And during this process product related information is captured from various departmetns like Product Managers, Marketing, Finance, Release , Legal etc and most of the information is either in human head or documented in some unstructured formats. And extracting such information from human head and putting it into system consumes considerable amount of time and effort.  Also, non availability of information leads to inconsistent and incomplete data. Data collection process is a multi step and iterative process. And having SLAs defined for each step of the process will yield timely and accurate data.

Also data definition,dimension, domain values changes over period and not having a well defined roadmap or process to manage such changes is also cause of inconsistent information.