Data quality checks are systematic processes employed to ensure that data is accurate, consistent, and reliable for decision-making. These checks assess various dimensions of data quality, including completeness, validity, accuracy, and consistency, which are crucial for maintaining trust in the data used for analysis and reporting. By implementing robust data quality checks, organizations can effectively manage their data assets and support effective data governance and advanced modeling techniques.
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