Automations

Identify assets for cleanup in Polytomic

⚡️ Automation

Identify assets for cleanup in Polytomic 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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Automations

Identify assets for cleanup in Polytomic

⚡️ Automation

Identify assets for cleanup in Polytomic 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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Overview

Integration with Polytomic is a valuable tool for data cleanup. By tagging data that hasn't been accessed within a specific timeframe as "for review," it allows for efficient and targeted cleanup to maintain the accuracy, reliability, and consistency of datasets. This process ensures that any analyses or decisions made based on this data are valid and well-informed, ultimately improving the overall quality of the data.

How it works

Using Secoda's automation features, you can integrate Polytomic and tag data for review to ensure cleanliness. The automation process consists of triggers and actions. Triggers are responsible for initiating the workflow according to defined schedules such as hourly, daily, or custom timeframes. Actions encompass a range of operations, including filtering and updating metadata, allowing you to create customized workflows to suit your team's requirements. In the context of Polytomic, Secoda enables you to perform bulk updates to metadata efficiently. By integrating these tools, you can easily identify and tag data from Polytomic that has not been accessed within a specific period for review and cleanup.

About Secoda

By integrating Polytomic with Secoda, data teams can effectively scale their data cleanup practices. This integration simplifies the process of prioritizing assets, allowing users to easily identify and focus on the most important data. Secoda serves as a comprehensive data management platform, consolidating your company's data catalog, lineage, documentation, and monitoring into a centralized index. This integration enhances data organization and enables efficient data cleanup efforts.

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