dbt Cloud is a scalable data transformation platform that helps data teams build, deploy, monitor, and discover data assets, providing a browser-based UI for developing, testing, scheduling, documenting, and investigating data models.This integration enables users to trigger and monitor their dbt Cloud Jobs directly from UAC.Key FeaturesTrigger and Monitor dbt Cloud Jobs with the capability to provide optional configuration run settings.Real‑Time Job Monitoring that provides continuous feedback displaying detailed Job and Step status updates throughout the execution lifecycle.What's NewEnhancementsAdded: Improved compatibility with future agent releases.Added: New pattern for triggering dbt Cloud Jobs using the Job ID.FixesFixed: Issue where selecting the “Include Run Results” Extension Output Option resulted in task instance failure.

DBT (Data Build Tool) Core is an open-source tool and it is designed to help data engineers and analysts manage and transform data in a reliable and scalable manner. Some key features of DBT Core include version control integration, automated testing, documentation generation, and dependency management. These features enable teams to collaborate effectively, ensure the quality of their data transformations, and maintain documentation for their data pipelines. DBT Core simplifies the process of transforming data in a data warehouse environment, providing a structured and scalable approach that helps teams manage their data transformation workflows effectively.This integration provides an interface to call the DBT Core CLI and enables users to execute DBT Core CLI tasks in Universal Controller. This is particularly useful when UC acts as a data pipeline orchestrator and DBT is a step within a data pipeline Universal Controller workflow. Key Features: Show DBT version and DBT environment variables information as Task Instance STDOUT. Enables users to retrieve Information on the dbt core installation. Execute a given DBT command. DBT output is displayed as task instance STDOUT Artifacts can be collected, and related information can be published within Universal Controller for subsequent workflow tasks to use.Ability to safely store and pass UC Credentials as DBT environment variables. What's New in V1.0.1:Include integration icon on Universal Template.

Fivetran is a cloud-based data integration platform that helps businesses automate the process of extracting data from various sources, transforming it, and loading it into a data warehouse for analysis. It offers a wide range of pre-built connectors to popular data sources such as databases, marketing platforms, CRMs, and more. Fivetran's connectors are designed to be easy to set up and use, allowing businesses to focus on data analysis rather than data integration. The platform also offers features such as data transformation, scheduling, monitoring, and access control to help organizations manage their data pipelines more efficiently. Fivetran supports a variety of data warehouses, including Amazon Redshift, Google BigQuery, Snowflake, and Microsoft Azure. This integration allows to create and execute Fivetran Tasks in Universal Controller.   Key Features: Trigger a Sync action on a Connector. Optionally, wait until Sync is completed. Trigger a Re-sync (Historical Sync) action on a Connector. Optionally, wait until Re-sync is completed.What's New Deprecations and Breaking Changes Breaking Change: Dropping support for Agents with version <= 7.6 and for Python 3.7.ImprovementsAdded: New field to limit maximum number of polls to do while waiting for a on Fivetran to finish. Added: Improved compatibility with future agent releases. Fixes Fixed: Bug where a failed Fivetran sync incorrectly resulted in a successful task instance.

This integration can complete various administrative tasks, including publishing reports and moving reports from one server to another server. It's based on the SQL Server Reporting Services 'rs.exe' command-line utility, which can perform many scripted operations related to SQL Server Reporting Services (SSRS). The rs.exe utility requires an input file to tell rs.exe what to do.The list of actual tasks that can be performed includes among others: Deploying / Publishing reports Moving reports Exporting reports to a file Adjust security Cancel a running job Configure SSRS system properties

SQL Server Agent jobs help to schedule and execute tasks within the SQL Server environment for example to trigger the nightly backups, SSIS package executions, and Database applications and administration activities.This extension simplifies interacting with SQL Server Agent jobs. It allows users to:Browse and Select Jobs - Easily list and choose the desired SQL Server Agent job and its specific stepsAutomated Execution - Trigger the selected job on the Microsoft SQL Server.Monitoring and Logging - Monitor the job's execution status and retrieve logs upon completion, providing insights into the process.The dependencies of the SQL server agent jobs with other platforms or applications can also be managed easily via UAC workflows.Key FeaturesThis Universal Extension provides the following main features:Dynamic Choice field to list the Database(select msdb), SQL server Agent job, and SQL Server Agent Job step nameTrigger a MSSQL Server agent jobTrigger and Wait until the SQL server agent Job Reaches the status "Success" or "Failed"Read the status of an existing Batch JobRestart the job from a specific if failedWhat's NewFixes:Fixed: Removed the pymSSQL package from the extension.Fixed: Template fix

This Universal Task provides the capabilities for submitting Oracle EBS Concurrent Requests by using CONCSUB CLI Command with additional capabilities like fetching the logs and output files, validating successful execution, and running the EBS environment script before running the concurrent request.The CONCSUB command is an operating system utility used to submit concurrent requests in Oracle E-Business Suite. It allows users to submit requests without having to log in to the Oracle E-Business Suite application. Key Features:The Universal Task provides the following key features: Submit Concurrent RequestFetch LogsExecute Environment ScriptResult validation based on output messages

SAP HANA Cloud, data lake is the storage tier of SAP HANA Cloud for large volumes of structured and unstructured data. Its Files service keeps data in file containers secured by client certificates, and its Relational Engine runs SQL analytics over data loaded into tables or held in those files.This integration transfers files between a Universal Agent and a data lake Files container, and runs SQL scripts against the data lake Relational Engine, so ingestion, export and housekeeping can be scheduled and chained with other tasks from the Universal Controller.Key FeaturesUpload, download, list and delete data lake files, selected by a glob pattern and an optional recursion depth that mirrors directory trees in both directions.Copy or move files, and choose how an existing file at the destination is handled: replace it, keep it, or write the new file under a timestamped or numbered name.Authenticate to data lake Files with mutual TLS using a client certificate and private key, with an optional key passphrase held in a UAC Credential.Run multi-statement SQL scripts against the Relational Engine, including LOAD TABLE and UNLOAD, stopping at the first failure and committing once all statements succeed.Return transferred, skipped and deleted file paths, and per-statement row counts and result rows, as Extension Output for downstream tasks.

This Universal Extension provides the capability to integrate with ODBC compliant database, by running single or multiple SQL commands and retrieving the resulting data. While it is designed to work with any ODBC-compliant database, it is thoroughly tested against MySQL, MSSQL Server PostgreSQL, and Oracle databases. As opposed to the native UAC SQL Task, which runs on the Controller, this integration allows the user to run an SQL Task from the Agent.Key FeaturesFlexibility in database connection definition supporting DSN, FILE DNS and Connection String.Rich metadata information.Capability to store SQL results in files (CSV or JSON formats).Rich Observability capabilitiesWhat's New v 4.0.0Deprecation and Breaking ChangesBreaking change: Dropping support for Agents with versions <7.5 and for Python 3.7 Enhancements Added: Improving Python compatibility with future Agent versions Fixes Fixed: Fix issue that lead to exception when using "Use Quotes: Never" and data contained "