Data quality assessments support the development and attainment of predefined quality expectations and measure data quality for the most important business data attributes, organized by subject area. Initiation of assessments is driven by business priorities, often focused on highly shared data required by multiple business areas, data required for accurate financial statements, and data sets supporting critical business processes.
Quality assessments should be performed against those data elements that are deemed critical to the organization; for example, data that contribute directly to the success of the organizational objectives, are used as part of regulatory or internal compliance reporting, are designated as critical employee data, or are necessary for operational decision making. It is important to ensure that policies provide guidance for what are determined to be critical data sets and data elements.
Targets (the level of quality desired); thresholds (the level of quality tolerated); and metrics are established for attributes in the selected data sets. These measures and metrics are typically captured and published in a scorecard or dashboard format. Assessment results facilitate root cause analysis and are key inputs into the organiza- tion’s data quality improvement plans.
To support these e orts and determine benefits, it is helpful to categorize the data quality impacts as part of the assessment process. Categorizing impacts such as cost, risk, compliance, productivity, etc. will also assist with prioritizing data cleansing plans.
The organization may move toward a subject area-based approach to data quality assessment as the governance function and target data architecture matures. For example, in the subject area approach, the data stewards for customer information would accept responsibility for developing and monitoring data quality rules for shared customer data on behalf of the organization, and would be the “owners” of that portion of the organization’s data quality dashboard. Key data stores that create or update customer information would be regularly monitored to determine if the acceptable quality thresholds and targets are being met; if not, the customer data stewards would initiate root cause analysis and sponsor the resulting improvements for remediation and defect prevention.