These people are charged with preventing the propagation of inferior quality data throughout the enterprise, and thus, the decision-making processes. Therefore, it is their responsibility to perform regular data audits on business data, metadata, and data models, and to be involved in data reconciliation efforts by helping to identify and resolve the root causes of data quality issues. The findings of the audits and reconciliation efforts should feed back into a continuous data quality improvement cycle.