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. Initial queries should be confirmatory, since sampling techniques using moderate quantities of extracted data can be used to produce them from a data package. In order to avoid compromising the reputation of a particular pilot or subsequent project, it is important to start the development project with a data assay . By data assay we mean a formal program to determine the quality of the data required for a particular application.