13 - Data Quality Service Level Agreements

Abstract

This chapter examines how to translate the information needs derived from the business drivers into data quality controls, and how users convert measured observance of those controls into data quality metrics based on the business objectives. These metrics provide the quantification for reporting a data quality scorecard. This scorecard can be a valuable management tool for observing more than just the quality of the data; one can also determine how well the data stewards are performing in remediation efforts to maintain data quality control. This chapter also describes a target state for operational data quality management that is achieved using a data quality scorecard that communicates: the qualified oversight of data quality along business lines, the degree of levels of trust in the data in use across the application infrastructure, and the ability for data stewards to drill down to identify the area of measurement that contributes the most to missed expectations. Processes can be put in place to facilitate the definition of DQ SLAs and the metrics that support those SLAs. Providing a data quality scorecard provides transparency to the data quality management process by summarizing the usability of the data as defined by the business users. The processes for instituting data quality business rules and data validation can be used to demonstrate an auditable process for governing the quality of organizational data.