The document discusses data quality assessment, highlighting its dimensions and how it relates to various data types and quality standards. It emphasizes the importance of managing data quality through automation and validation processes, as well as the need for good tool support. Strategies for improvement focus on identifying errors close to the source and ensuring fitness for use in diverse applications.
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