Applying a data quality check on Glue tables

Glue Data Quality is crucial for maintaining the integrity and reliability of data within the AWS Glue environment. It ensures that data conforms to specified quality standards, allowing organizations to trust and rely on the accuracy of their data-driven insights and decision-making processes. Implementing data quality checks helps identify and rectify issues, such as missing values, inconsistencies, and inaccuracies in datasets, promoting data reliability and reducing the risk of making decisions based on flawed information. AWS Data Quality allows you to enforce quality checks on your data on transit and rest using Data Quality Definition Language (DQDL). This allows you to proactively apply data quality rules to your jobs and tables, helping to identify potential issues early. Additionally, you can enforce rules on multiple tables and configure actions or alarms based on detected quality issues, preventing larger problems, such as making...