This section describes how you interact through the  with your SQL DW data warehouse.

• SQL DW is a scalable data warehouse solution available through Microsoft Azure. For more information, see https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-overview-what-is. 

Limitations

• Microsoft SQL DW connections are available only if you have deployed the  onto Azure.

• No data validation is performed during publication to SQL DW. Your job fails if the schema for the   varies from the target schema.

  NOTE: In this release, this connection cannot be created through the CLI or APIs. Please create connections of this type through the application.

• When using the SQL DW read-write connection, the defined length of a table row cannot exceed 1 MB.

Uses of SQL DW

The  can use SQL DW for the following tasks:

1. Create datasets by reading from SQL DW tables.

2. Write to SQL DW tables with your job results.

3. Ad-hoc publication of data to SQL DW.

Before You Begin Using SQL DW

• Enable SQL DW Access: SQL DW integration requires the following:

  • Installation of the  on Microsoft Azure.
  • Either ADL or WASB is supported as the base storage layer. For more information, see Set Base Storage Layer.

• Read Access: Your SQL DW administrator must configure read permissions. Your administrator should provide a database for upload to your SQL DW datastore.

• Write Access: You can write and publish jobs results to SQL DW. 

Secure Access

SQL DW connections require SSL access.

Storing Data in SQL DW

Your SQL DW administrator should provide database access for storing datasets. Users should know where shared data is located and where personal data can be saved without interfering with or confusing other users. 

Reading from SQL DW

You can create a  from a table stored in SQL DW.

For more information, see Database Browser.

Writing to SQL DW

You can write back data to SQL DW using one of the following methods:

• Job results can be written directly to SQL DW as part of the normal job execution. Create a new publishing action to write to SQL DW. See Run Job Page.

• As needed, you can export results to SQL DW for previously executed jobs.

  NOTE: You cannot re-publish results to SQL DW if the original job published to SQL DW. However, if the dataset was transformed but publication to SQL DW failed, you can publish from the Export Results window.

  NOTE: To publish from the Export Results window, the source results must be Parquet format.

  See Export Results Window.

• For more information on how data is converted to SQL DW, see SQL DW Data Type Conversions.

Data Validation issues:

• No validation is performed for the connection and any required permissions during job execution. So, you can be permitted to launch your job even if you do not have sufficient connectivity or permissions to access the data. The corresponding publish job fails at runtime. 
• No data validation is performed during writing and publication to SQL DW. Your job fails if the schema for the varies from the target schema.
• Prior to publication, no validation is performed on whether a target is a table or a view, so the job that was launched fails at runtime.