Import SAS Data Sets Data Using Azure Data Factory

Microsoft Azure Data Factory (ADF) is a completely managed, serverless data integration service. When combined with CData Connect AI, ADF enables immediate cloud-to-cloud access to SAS Data Sets data within data flows. This article outlines the process of connecting to SAS Data Sets through Connect AI and accessing SAS Data Sets data within ADF.

CData Connect AI offers a cloud-to-cloud interface tailored for SAS Data Sets, granting you the ability to access live data from SAS Data Sets data within Azure Data Factory without the need for data replication to a natively supported database. Equipped with optimized data processing capabilities by default, CData Connect AI seamlessly channels all supported SQL operations, including filters and JOINs, directly to SAS Data Sets. This harnesses server-side processing to expedite the retrieval of the desired SAS Data Sets data.

Configure SAS Data Sets Connectivity for ADF

Connectivity to SAS Data Sets from Azure Data Factory is made possible through CData Connect AI. To work with SAS Data Sets data from Azure Data Factory, we start by creating and configuring a SAS Data Sets connection.

CData Connect AI uses a straightforward, point-and-click interface to connect to data sources.

1. Log into Connect AI, click Sources, and then click Add Connection

2. Select "SAS Data Sets" from the Add Connection panel

3. Enter the necessary authentication properties to connect to SAS Data Sets.

   Set the following connection properties to connect to your SAS DataSet files:

   Connecting to Local Files

   • Set the Connection Type to "Local." Local files support SELECT, INSERT, and DELETE commands.
   • Set the URI to a folder containing SAS files, e.g. C:\PATH\TO\FOLDER\.

   Connecting to Cloud-Hosted 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.

   
4. Click Save & Test
5. Navigate to the Permissions tab in the Add SAS Data Sets Connection page and update the User-based permissions.

Add a Personal Access Token

When connecting to Connect AI through the REST API, the OData API, or the Virtual SQL Server, a Personal Access Token (PAT) is used to authenticate the connection to Connect AI. It is best practice to create a separate PAT for each service to maintain granularity of access.

1. Click on the Gear icon () at the top right of the Connect AI app to open the settings page.
2. On the Settings page, go to the Access Tokens section and click Create PAT.
3. Give the PAT a name and click Create.
4. The personal access token is only visible at creation, so be sure to copy it and store it securely for future use.

With the connection configured and a PAT generated, you are ready to connect to SAS Data Sets data from Azure Data Factory.

Access Live SAS Data Sets Data in Azure Data Factory

To establish a connection from Azure Data Factory to the CData Connect AI Virtual SQL Server API, follow these steps.

1. Login to Azure Data Factory.

2. If you have not yet created a Data Factory, Click New -> Dataset.

3. In the search bar, enter SQL Server and select it when it appears. On the following screen, enter a name for the server. In the Linked service field, select New.

4. Enter the connection settings.
   • Name - enter a name of your choice.
   • Server name - enter the Virtual SQL Server endpoint and port separated by a comma: tds.cdata.com,14333
   • Database name - enter the Connection Name of the CData Connect AI data source you want to connect to (for example, SASDataSets1).
   • User Name - enter your CData Connect AI username. This is displayed in the top-right corner of the CData Connect AI interface. For example, [email protected].
   • Password - select Password (not Azure Key Vault) and enter the PAT you generated on the Settings page.
   • Click Create.

5. In Set properties, set the Name, choose the Linked service we just created, select a Table name from those available, and Import schema from connection/store. Click OK.

6. After creating the linked service, the following screen should appear:

7. Click preview data to see the imported SAS Data Sets table.
You can now use this dataset when creating data flows in Azure Data Factory.

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