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afv-library/skills/data360-prepare/README.md

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data360-prepare

Ingestion and lake-preparation workflows for Salesforce Data Cloud.

Use this skill for

  • data streams
  • Data Lake Objects (DLOs)
  • data transforms
  • Document AI setup and extraction
  • unstructured ingestion and re-scan workflows
  • deciding how a source dataset should enter Data Cloud
  • classifying a dataset as Profile, Engagement, or Other
  • using the Ingestion API send-data example after connector setup

Example requests

"Create a Data Cloud stream from Contact"
"Inspect the DLO created by this stream"
"Help me create a transform for ingested data"
"Re-run this SharePoint document stream so it picks up new files"
"Show me how to send records to Data Cloud through the Ingestion API"

Common commands

sf data360 data-stream list -o myorg 2>/dev/null
sf data360 data-stream create-from-object -o myorg --object Contact --connection SalesforceDotCom_Home 2>/dev/null
sf data360 data-stream run -o myorg --name Contact_Home 2>/dev/null
sf data360 dlo get -o myorg --name Contact_Home__dll 2>/dev/null
sf data360 transform list -o myorg 2>/dev/null
sf data360 connection run-existing -o myorg --name <connection-id> 2>/dev/null

Key reminders

  • confirm whether a dataset should be treated as Profile, Engagement, or Other before creating the stream
  • data-stream run is the preferred re-scan path for unstructured document ingestion
  • connection run-existing is a connection-level rerun and is not a full substitute for stream refresh
  • some external database and Ingestion API stream-creation flows still require UI setup
  • initial unstructured DLO setup can be richer in the UI than in a minimal CLI payload
  • use the local examples/ingestion-api/ folder for the send-data flow

References