You can load the ETL into a CSV file, and save the new file to a shared folder location. When the ETL is run, the data will be loaded into the given file. Each table in the data flow will be saved to a separate CSV file. To use a CSV file as a target, add the CSV node from the Targets panel to the data flow.

Configure a CSV Target

From the target's Properties panel, name the new database that will be created, and provide a pointer to a shared folder where the file will be located:

  • Shared Folder Path: provide a pointer to a shared folder where the new database will be saved.
    • Expression: create a dynamic PQL expression to point to the shared folder path.
  • Add Date Time Folder: create a folder named according to the date and time at which the ETL is run, and save the database file inside this folder.
  • Folder for each Table: create a separate folder for each table node.
  • Automatic File Naming: assign the names of the data flow tables as file names. Disable to manually provide file name, or create an expression to provide file names.
    • If you add multiple tables, this option will be enabled by default.
    • File Name: if automatic file naming is disabled, you'll need to enter the file name. This can be a static value or a PQL expression.
  • Append .csv: append the CSV file extension to each file.
  • Separator: select the value separator from the drop-down.

Finally, click 'Connect All' to connect the target node to the data flow. As usual, you can add a description to the node's Properties panel.


Expand the Description window to add a description or notes to the node. The description is visible only from the Properties panel of the node, and does not produce any outputs. This is a useful way to document the ETL pipeline for yourself and other users.

Run the ETL

As there is no database or in-memory destination, the Data Model and Security stages are not relevant. Skip these steps and simply run the ETL from the Data Flow.

  • Click here to learn how to process the ETL.