As much as we would like to believe that all data in organizational databases is of consistently high quality, this is typically not true. The objective of a data warehouse is to provide information on business problems that were not the original focus of the data system that collected the source records. This means that some of the critical data may not be of good quality. Correcting this for every attribute collected by an organization over several years is usually not feasible so there must be a strategy to manage data quality. This strategy includes problem selection, assessment, selective sampling, and the use of robust tools.
Atomic queries extract collections of records that meet several properties.
The records themselves are the desired results. Such queries are not valuable if they are not based on a relatively complete population of detailed records such as a data deposit. Atomic queries are very poor choices for initial data package problems. Good data mining tools can help automate exploratory queries based on a well planned data mine. Raw data is not usually necessary.