Identify assets for cleanup in Amazon Glue 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 Amazon Glue allows for effective data cleanup by tagging data that has not been accessed within a specific timeframe as "for review." This process helps in maintaining the accuracy, reliability, and consistency of datasets. By identifying and flagging unused data, organizations can ensure that their analyses and decisions are based on valid and informed information, ultimately enhancing the overall quality of their data.
Integration with Amazon Glue in Secoda allows you to automate tasks using triggers and actions. Triggers activate the workflow based on predefined schedules, enabling you to structure the frequency of subsequent actions. Actions in Amazon Glue integration encompass various operations such as filtering and updating metadata. By stacking these actions, you can create customized and detailed workflows that meet the specific requirements of your team. With Secoda, you can efficiently perform bulk updates to metadata in Amazon Glue. In the context of tagging data from Amazon Glue, Secoda enables you to identify data that has not been accessed within a certain period. You can easily tag this data as "for review" to facilitate cleanup processes.
Secoda's integration with Amazon Glue enhances data teams' ability to scale their data cleanup practices. By leveraging Amazon Glue's capabilities, Secoda enables easy prioritization of assets, streamlining the organization and management of data catalog, lineage, documentation, and monitoring. This integration empowers companies to efficiently handle their data knowledge within a centralized data management platform.
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