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SQL Server databases are commonly used to store enterprise records. It is often necessary to move this data to other locations. The CData SSIS Task for SAS Data Sets allows you to easily transfer SAS Data Sets data. In this article you will export data from SQL Server to SAS Data Sets.
To get started, add a new ADO.NET Source control and a new SAS Data Sets Destination control to the data flow task.
π The source and destination components used in this example.Follow the steps below to specify properties required to connect to the SQL Server instance.
Follow the steps below to set required connection properties in the Connection Manager.
Set the following connection properties to connect to your SAS DataSet files:
While the driver is capable of pulling data from SAS DataSet files hosted on a variety of cloud data stores, INSERT, UPDATE, and DELETE are not supported outside of local files in this driver.
Set the Connection Type to the service hosting your SAS DataSet files. A unique prefix at the beginning of the URI connection property is used to identify the cloud data store and the remainder of the path is a relative path to the desired folder (one table per file) or single file (a single table). For more information, refer to the Getting Started section of the Help documentation.
In the destination component Connection Manager, define mappings from the SQL Server source table into the SAS Data Sets destination table and the action you want to perform on the SAS Data Sets data. In this article, you will insert restaurants entities to SAS Data Sets.
You can now run the project. After the SSIS Task has finished executing, data from your SQL table will be exported to the chosen table.
π The SQL Server table to export into SAS Data Sets.Download a free trial of the SAS Data Sets SSIS Component to get started:
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π SAS Data Sets IconPowerful SSIS Source & Destination Components that allows you to easily connect SQL Server with SAS Data Sets through SSIS Workflows.
Use the SAS Data Sets Data Flow Components to synchronize with SAS Data Sets. Perfect for data synchronization, local back-ups, workflow automation, and more!