Category: C – DATA QUALITY

Best practices for defining and implementing a collaborative approach for detecting, assessing, and cleansing data defects to ensure fitness for intended uses in business operations, decision making, and planning.
The Data Quality category encompasses process areas designed to provide the means for an organization to fully understand the nature and quality of the data under management, as well as mechanisms to evaluate, prevent, and remediate defects, to assure that the quality of data meets business purposes and the organization’s strategic objectives. In short, these process areas collectively describe a comprehensive data quality program, driven by a data quality strategy.
The Data Quality Strategy is foundational to all data quality management activities. It describes activities designed to help the organization develop a defined, approved integrated plan to ensure that the quality of data meets business needs. Data Profiling and Data Quality Assessment contain activities that help the organization assess the data under management against a set of quality objectives, which are defined in the Data Quality Strategy. Achieving e ciencies and successful, repeatable processes for Data Cleansing activities reduces e ort and lowers costs, enabling the organization to assure “fit for purpose” data assets across its data sets and physical data stores.
Maturity of the practices described in this category will help to translate business goals and priorities into actionable plans designed to execute as an organization-wide program to actively manage data across all dimensions of quality. This enables the organization to realize maximum value from its data assets and to capitalize on opportunities that require accurate, trusted data.