Data Warehouse
You can send CRM Analytics data to warehouses like BigQuery or Snowflake using built-in connectors, dataflows with output nodes, or third-party ETL tools. The process typically involves creating an output connection in Data Manager, then configuring a dataflow or recipe to push transformed dataset data on a schedule.
Methods
Use output connections in Analytics Studio → Data Manager → Connections. Set up Snowflake or BigQuery as an external output (requires "Enable Data Sync and Connections" permission in Analytics Settings). Then, in a dataflow, add an "Output to Snowflake/BigQuery" node bound to your dataset, specifying schema/table and credentials (OAuth/JDBC for Snowflake, service account for BigQuery).
Alternatively, export datasets as CSV via Data Manager or APIs, then load via warehouse tools such as Snowflake Snowpipe or BigQuery Load Jobs; or leverage ETL like Fivetran/CData Sync for automated replication.
Data Schemas
Schemas mirror your dataset structure — tabular with rows as records and columns as fields from Salesforce objects, recipes, or blends.
CRM Analytics preserves data types (string, number, date, boolean) and adds metadata like row IDs or timestamps; no rigid standard schema exists.
Comparison
| Method | Best For | Schema Handling |
|---|---|---|
| Output Connections | Native, scheduled pushes | Auto-maps dataset |
| Dataflow Export | Transformed data | Custom via nodes |
| ETL Tools (CData) | Full automation | Replicates exactly |