Data Quality dimensions are useful concepts for improving the quality of data assets. Although Data Quality dimensions have been promoted for many years, descriptions of how to actually use them have often been somewhat vague.
Data that is considered to be of high quality is consistent and unambiguous. Poor Data Quality results in inconsistent and ambiguous data — data from different sources may show different addresses, inconsistent preferences, etc. Poor Data Quality can be the result of merged databases or from new information being combined with old information, instead of having replaced it.
