Create a data stream by bringing in data from a local CSV file into Data 360.
Required Editions
| Available in: All Editions supported by Data 360. See Data 360 edition availability. |
| User Permissions Needed | |
|---|---|
| To upload data using a file |
Permission set:
|
Before You Begin
- Verify that your file is less than 2 GB and has a maximum of 1,050 columns.
- Use the four-digit (“yyyy”) format for date and time records that include a year. When data from an ingested file uses the two-digit (“yy”) format, additional date and time pattern rules for the “year” are applied. This can result in an unexpected date value.
- Use a supported format when your file contains date or date-time values. See Date and Datetime Formats.
- If you create or update a sandbox org, activate the UploadedFiles connection from Setup, in Other Connectors.
Watch this video or follow the steps to use this feature.
- In Data Cloud, go to the Data Streams tab and click New.
- Select the File Upload tile, and click Next.

- Select the CSV file with your data.
- Specify your data lake object (DLO), and API name.

- In the Properties section, select the category for your data stream and primary key.

- To change a field's data type, click the Supported Fields tab.

- Click Next.
- (Optional) If needed, change the data stream name. The data stream uses the uploaded file name.
- (Optional) If needed, choose a data space and set filters.
-
To create your data stream, click Deploy. This ingests your data
into the DLO.

NoteWhen you install a File Upload Stream in a target org using a Data Kit, the stream is inactive and returns the error "INVALID_ARGUMENT: Invalid tenantId in FullyQualifiedPath". This issue occurs because the stream points to file storage in the source org, which the target org can't access. To resolve the issue, open the stream in the target org, click Update File, and upload the file to reconnect it to the target org's storage.
- Data Stream Updates Using File Upload
Update the data of an existing data stream created using File Upload. Quickly update your data by re-uploading the revised CSV file with added or removed records. Updating data replaces the data that was previously stored in the associated Data Lake Object (DLO). It also ensures that the data stream is always current with the latest information.