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Delete Ingested Records in Data 360
You can delete data ingested into Data 360. Your data stream must have an upsert refresh mode. The deletion process depends on the type of connector that you’re using.
Amazon S3, Google Cloud Storage, and Microsoft Azure Storage connectors—The records that you’re deleting must be read from the same source directory that the corresponding data stream is ingesting from. When a data stream has multiple upsert and deletion files, the files are processed in the order of their last modified time. Row versioning isn’t supported for deletes.
Ingestion API connector—The API provides a delete operation for both streaming and bulk interaction patterns. To delete up to 200 records, refer to Delete Records. To delete more than 200 records in a request, use bulk ingestion operations. For more information, see Upload Job Data and Delete a Job. After the delete requests are received programmatically, they're processed asynchronously.
SFTP connector—The records that you’re deleting must be read from the same source parent directory that the corresponding data stream is ingesting from. When a data stream has multiple upsert and deletion files, the order of processing isn't guaranteed. Row versioning isn’t supported for deletes.
Salesforce CRM connector—The connector manages the deletion requests. After data is deleted on the source org, it’s removed from Data 360 with the next incremental refresh. You can store deleted records that have been in the Salesforce Recycle Bin for up to 15 days by creating a Deleted Record Data Lake Object, see https://developer.salesforce.com/docs/atlas.en-us.c360a_api.meta/c360a_api/c360a_api_upload_job_data.htm.
Data 360 doesn’t support cascading deletes. If you delete a profile record, its related engagement or other profile records aren’t deleted. Delete these records manually from each table.
- Delete Records Using a Delete File
You can delete data records that are ingested using the AWS S3, Google Cloud Storage (GCS), Microsoft Azure, Ingestion API, or SFTP connector by creating a delete file in either CSV or Parquet file format. S3, GCS, and Azure data streams support Parquet file ingestion.
