Automated completeness checks for Databricks 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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Secoda integration with Databricks enables the automation of completeness checks for data stored in Databricks. This integration is designed to ensure a smooth and secure migration process. By utilizing Secoda, users can automate the scanning of datasets and apply tags to indicate their completeness after migration. This feature streamlines the process of verifying data integrity and enhances the efficiency of data management in Databricks.
Integration with Databricks allows users to automate completeness checks using the Secoda Automations feature. Automations consist of Triggers and Actions. Triggers determine when the workflow is activated, and users can set schedules such as hourly, daily, or custom intervals. Actions encompass various operations, such as filtering and updating metadata. Users can stack multiple actions to create customized workflows. Secoda enables bulk updates to metadata in Databricks.
Secoda's integration with Databricks enables the automation of completeness checks for data residing in Databricks. By consolidating data catalog, lineage, documentation, and monitoring into a single platform, Secoda serves as an index of your company's data knowledge. With this integration, you can ensure an efficient and safe migration by automatically scanning datasets and tagging them as complete once they have been migrated. Secoda allows you to automate completeness checks in your data catalog, providing a streamlined process for managing and verifying data integrity.
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