Automations

Identify orphaned data in Dagster

⚡️ Automation

Identify orphaned data in Dagster 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 orphaned data in Dagster

⚡️ Automation

Identify orphaned data in Dagster 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 Dagster allows for the identification of data that no longer has an assigned team or user. This uncategorized data can be tagged for further review. The process of identifying orphaned data is essential in data cleanup practices. It helps prevent data integrity issues, optimize storage utilization, enhance system performance, and ensure accurate data analysis and reporting. By integrating with Dagster, organizations can effectively manage their data and maintain a streamlined and efficient data infrastructure.

How it works

In order to identify data from Dagster that no longer has an assigned team or user and tag it for review, you can utilize the integration with Secoda. Secoda offers automation capabilities through triggers and actions. Triggers enable you to set schedules for the workflow, allowing subsequent actions to be executed at specific intervals. Actions encompass various operations like metadata updates and filtering. By leveraging Secoda's integration with Dagster, you can efficiently perform bulk updates to metadata, enabling you to identify unassigned data for further review.

About Secoda

Integrating Secoda with Dagster empowers data teams to enhance their data enablement strategies effectively. Secoda acts as a centralized data management platform that consolidates vital components such as data catalog, lineage, documentation, and monitoring. This integration facilitates seamless scalability as it simplifies the process of maintaining trust scorecards. By streamlining these practices, data teams can efficiently scale their operations and ensure the reliable management of their company's data knowledge.

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