Automations

Identify assets for cleanup in Redash

⚡️ Automation

Identify assets for cleanup in Redash 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 Redash

⚡️ Automation

Identify assets for cleanup in Redash 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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Redash
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Overview

Integration with Redash allows for efficient data cleanup by tagging data that has not been accessed within a specified period as "for review". Data cleanup is crucial for maintaining accurate, reliable, and consistent datasets. It ensures that analyses and decisions based on the data are valid and informed, enhancing overall data quality. With Redash integration, organizations can easily identify and address outdated or irrelevant data, contributing to more reliable and effective data management.

How it works

Secoda offers integration with Redash, a platform that allows you to create automated workflows consisting of triggers and actions. Triggers in Redash can be set up to activate workflows based on specific schedules, such as hourly or custom intervals. Actions in Redash encompass a variety of operations, such as filtering and updating metadata. By stacking actions, you can design detailed workflows customized to your team's requirements. In the context of tag data from Redash, Secoda enables you to tag any data that has not been accessed within a specified period as "for review," facilitating a cleanup process.

About Secoda

Secoda's integration with Redash provides data teams with the ability to efficiently enhance their data cleanup practices. By seamlessly combining your company's data catalog, lineage, documentation, and monitoring into a single data management platform, Secoda acts as a comprehensive index of your data knowledge. This integration empowers data teams to easily prioritize assets and effectively scale their data cleanup efforts.

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