Identify assets for cleanup in AWS S3 with Secoda. Learn more about how you can automate workflows to turn hours into seconds. Do more with less and scale without the chaos.
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Integration with AWS S3 allows for effective tag data processing to identify stale data that has not been accessed for a specific duration. By tagging this data as 'for review', it becomes easier to perform data cleanup activities. Data cleanup plays a crucial role in maintaining accurate, reliable, and consistent datasets. It ensures the validity and informedness of analyses and decisions made using this data, thereby improving overall data quality.
The integration with AWS S3 in Secoda allows you to automate tasks through triggers and actions. Triggers can be scheduled on a regular basis or customized to activate the workflow. Actions consist of different operations, such as filtering and updating metadata. You can combine multiple actions to create customized workflows based on your team's requirements. In the case of tagging data from AWS S3, you can use this integration to mark data that hasn't been accessed within a specified period as 'for review' for cleanup.
Secoda, a data management platform, offers integration with AWS S3. By connecting Secoda with AWS S3, data teams can efficiently scale their data cleanup practices. This integration streamlines the process of prioritizing assets, making it convenient for data teams to manage their data catalog, lineage, documentation, and monitoring within a single platform. With Secoda and AWS S3 integration, data teams can enhance their data knowledge and optimize data management practices.
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