Through the use of sophisticated algorithms, non-statistician users have the opportunity to identify key attributes of business processes and target opportunities. However, abdicating control of this process from the statistician to the machine may result in false-positives or no useful results at all.

Metadata, or data about a given data set, are often expressed in a condensed data-minable format, or one that facilitates the practice of data mining. Common examples include executive summaries and scientific abstracts.

Data mining is particularly useful for validating integrity of data on an IT system. Missing information, inconsistent information, errors etc are identified for correction. Data validating is often used when data are migrated between IT systems.

This service is often overlooked by clients despite the adverse consequences of incorrect information for decision making.