Identify assets for cleanup in Mode 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 Mode allows for the efficient tagging of data that has not been accessed within a specific timeframe. This tagging labels the data as "for review" and enables easy identification for cleanup. Performing regular data cleanup is crucial to uphold the accuracy and reliability of datasets. By ensuring that data is updated and free from errors, organizations can make informed decisions based on trustworthy information. Implementing data cleanup processes enhances the overall quality of the data, guaranteeing valid and reliable analyses.
With Secoda's integration with Mode, you can automate the process of tagging data that hasn't been accessed within a specific period as 'for review' for cleanup. By setting up triggers, you can schedule when this automation should run, whether it's hourly, daily, or on a customized basis. Once triggered, you can define actions to filter and update metadata in Mode. This integration allows you to efficiently perform bulk updates to metadata, ensuring your team can easily identify and clean up outdated or unused data.
Secoda integrates seamlessly with Mode, a data management platform, to enable data teams to efficiently scale their data cleanup practices. By leveraging the power of Secoda's index of your company's data knowledge, Mode users can easily prioritize their data assets. This integration simplifies the process of consolidating data catalog, lineage, documentation, and monitoring into a centralized platform provided by Secoda, enhancing the overall efficiency and effectiveness of data management for organizations.
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