This section describes how you interact through  with your Redshift data warehouse.


Uses of Redshift

The  can use Redshift for the following tasks:

  1. Create datasets by reading from Redshift tables.
  2. Write to Redshift tables with your job results.

  3. Ad-hoc publication of data to Redshift.

Before You Begin Using Redshift

Secure Access

SSL is required.

Storing Data in Redshift

Your Redshift 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. 

NOTE: does not modify source data in Redshift. Datasets sourced from Redshift are read without modification from their source locations.

Reading from Redshift

You can create a  from a table or view stored in Redshift.

NOTE: The Redshift cluster must be in the same region as the default S3 bucket.

NOTE: If a Redshift connection has an invalid iamRoleArn, you can browse, import datasets, and open the data in the Transformer page. However, any jobs executed using this connection fail. If the iamRoleArn is invalid, the only samples that you can generate are Quick Random samples; other sampling jobs fail.

For more information, see Redshift Browser.

Writing to Redshift

NOTE: You cannot publish to a Redshift database that is empty. The database must contain at least one table.

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


Data Validation issues: