Automations

Automatically tag your most used assets in Azure Synapse

⚡️ 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 Azure Synapse

⚡️ 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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Azure Synapse
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Overview

Secoda's integration with Azure Synapse allows for seamless tagging of frequently utilized assets. By automating this process, valuable time is saved while ensuring that data literacy and enablement practices remain scalable and current. With the ability to effortlessly identify the most commonly used assets, Secoda enables effective prioritization of maintenance tasks.

How it works

Azure Synapse integration with Secoda automates the tagging process for frequently used assets, streamlining data source management. This integration ensures data literacy and scalability by keeping your practices up-to-date. Azure Synapse integration allows you to define triggers based on specific schedules, such as hourly or daily, to activate workflows. Actions within the integration include filtering and updating metadata, among others, enabling you to customize workflows to meet your team's requirements. Additionally, with Secoda, you have the ability to perform bulk updates to metadata in Azure Synapse.

About Secoda

Azure Synapse and Secoda can be integrated to enhance data literacy and enablement practices. By combining these platforms, your company can benefit from a more scalable approach to managing data knowledge. Secoda acts as an index, bringing together your data catalog, lineage, documentation, and monitoring into a centralized data management platform. This integration allows for effective organization and access to critical data information, empowering users with comprehensive data insights and improving overall data management efficiency.

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