Usage monitoring for Oracle

Usage monitoring for Oracle 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

To monitor the usage levels of data resources and metadata from Oracle through Secoda, integration with Oracle Database can be utilized. Oracle Database is a well-known, multi-model database management system developed by Oracle Corporation. It offers reliable and scalable performance, making it suitable for various tasks such as online transaction processing, data warehousing, and mixed database workloads. Oracle Database supports different data types, including structured and unstructured data. By integrating Oracle Database with Secoda, you can ensure a smooth and secure migration process, optimizing resource utilization.

How it works

Secoda's integration with Oracle allows you to efficiently monitor the usage levels of data resources through the Automations feature. The Automations feature is comprised of two components: Triggers and Actions. Triggers are responsible for initiating the workflow based on predefined schedules such as hourly, daily, or custom intervals. This ensures a systematic and structured framework for subsequent actions. Actions, on the other hand, encompass a range of operations like filtering and updating metadata. You can stack actions on top of one another to create customized workflows that cater to your team's specific requirements. With this integration, you can also perform bulk updates to metadata in Oracle, enabling streamlined processes and improved efficiency.

About Secoda

Secoda, in conjunction with Oracle, provides a comprehensive solution for data migration and monitoring. By leveraging the capabilities of both platforms, users can effectively monitor the usage levels of data resources. Secoda acts as a centralized data management platform, consolidating the data catalog, lineage, documentation, and monitoring functionalities. This integration enables businesses to efficiently manage their data knowledge and ensure optimal utilization of data resources.

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