Automations

Identify assets for cleanup in Dagster

⚡️ Automation

Identify assets for cleanup 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 assets for cleanup in Dagster

⚡️ Automation

Identify assets for cleanup 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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Dagster
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Overview

Integration of Dagster into data cleanup processes is valuable for maintaining data accuracy and reliability. By tagging data from Dagster that has not been accessed within a designated period as "for review," it enables efficient cleanup. This cleanup process plays a crucial role in enhancing overall data quality, ensuring the validity and informed decision-making based on the datasets.

How it works

Secoda is an integration platform that enables users to automate tasks in Dagster. It consists of Triggers and Actions that work together to streamline workflows. Triggers can be customized to activate the automation at specific intervals, such as hourly or daily, providing a structured framework for subsequent actions. Actions, on the other hand, encompass a range of operations, including filtering and updating metadata. By stacking actions, users can design intricate workflows tailored to their team's requirements. With Secoda, users can efficiently perform bulk updates to metadata in Dagster. In the context of cleaning up data, users can utilize Secoda to tag data from Dagster that has not been accessed within a defined period as "for review." This tagging process simplifies the identification and cleanup of outdated data.

About Secoda

By integrating Dagster with Secoda, data teams can enhance their data cleanup practices and improve scalability. Secoda functions as a central hub for your company's data knowledge, consolidating data catalog, lineage, documentation, and monitoring within a single platform. This integration makes it convenient to prioritize assets, allowing data teams to efficiently manage and organize their data resources.

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