17 - Inspection, Monitoring, Auditing, and Tracking

Abstract

The concepts of instituting metrics and associated measurements for monitoring conformance to the data quality expectations of all data consumers, published via a data quality scorecard, are the fundamental facets of data quality control and management. This chapter considers the technical requirements to enable the inspection, monitoring, and auditing conformance to expectations as well as reporting and tracking data quality issues. The need for evaluating and reporting compliance of a data set with data quality rules that correspond to defined data consumer expectations is considered and two approaches, auditing and monitoring, are suggested. Auditing is performed on complete data sets, isolated from other processing activities, outside of any information processing flow. Monitoring identifies rule noncompliance in process, as part of the operational system. In both cases, there is a need for techniques for defining data quality rules, either as a result of the data quality requirements analysis or the data quality assessment. Tools are employed to validate the data values against these defined rules and notify the appropriate stakeholders when an exception has been identified. This chapter reviews the concept of the data quality service level agreement and then considers the technologies used for deployment.