When this feature is enabled, any user can upload a CSV file to analyze in Sigma. The data from the file is written back to the organization's data warehouse and can be joined to other data stored in that warehouse. To enable this feature, an admin must allow the feature in Advanced Settings and set up write access to the data warehouse.
When uploading a CSV, Sigma lets you select the delimiter, quote character, and escape character. You have a preview of how the data will display in Sigma to help guide your choices.
CSV Upload is available for Snowflake, Redshift and BigQuery. It is not available for Postgres.
Upload a CSV File
- Click the blue plus sign at the top of the left-hand navigation panel and click “New Worksheet”.
- Choose CSV as the data source. This option will only be available if your admin has set up write access to the data warehouse.
- Use the drop-down in the upper left to pick which data warehouse to upload the CSV to. If only one data warehouse has write access enabled, it will be chosen by default.
- Upload your CSV file.
- Check the preview of the CSV. Adjust the parsing options and address errors if necessary.
- Click ‘Get Started’ in the upper right of the screen.
Share a CSV File
- Create a new Sigma Worksheet and choose CSV as the source.
- Move the worksheet to a team folder or the organization folder.
- Share the link to the worksheet with your coworker.
Enable CSV Upload on Your Connection
- Go to Settings
- Click Advanced Settings
- Turn on the switch to allow CSV Upload
- Go to the Connections tab
- Set up a new connection, or enable write access to the connection
CSV Files in the Database
When a CSV is uploaded via Sigma, Sigma creates a table in the database. This table is only accessible in Sigma through the worksheet created by the CSV upload. To share a data in a CSV file, the user needs to share the Sigma worksheet. Other users cannot access the table directly in the database through Sigma.
If there are no longer worksheets referencing a table that was created by CSV upload, that table will be removed from the data warehouse within 24 hours, during scheduled clean up jobs.