Automations

Automatically tag your most used assets in Databricks

⚡️ Automation

Automatically tag your most used assets 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

Automatically tag your most used assets in Databricks

⚡️ Automation

Automatically tag your most used assets 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
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Databricks
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Overview

Secoda seamlessly integrates with Databricks, enabling you to effortlessly tag your frequently accessed assets. By automating this process, Secoda helps you save valuable time and ensures that your data literacy and enablement practices can scale effortlessly. Additionally, Secoda's advanced algorithms identify and prioritize the most frequently used assets, allowing you to focus on maintaining and updating them accordingly. This integration empowers you to streamline your data management workflows and optimize your data assets effectively.

How it works

Secoda offers seamless integration with Databricks, allowing you to effortlessly tag your frequently used assets involving data sources. By automating this process, you save valuable time while ensuring that your data literacy and enablement practices remain scalable and up-to-date. Secoda's integration with Databricks enables you to define triggers based on specific schedules, such as hourly, daily, or custom time intervals. These triggers activate subsequent actions, which can include operations like filtering and updating metadata. By stacking these actions together, you can create comprehensive workflows tailored to your team's unique requirements. Furthermore, Secoda empowers you to perform bulk updates to metadata in Databricks, streamlining your data management processes.

About Secoda

The integration of Databricks and Secoda offers a powerful solution for scalable data literacy and enablement practices. By combining these two platforms, organizations can effectively manage and consolidate their data catalog, lineage, documentation, and monitoring. This integration enhances data knowledge by providing a single data management platform, enabling users to easily access and analyze data.

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