Copper → Mode
AI-first ETL from Copper into Mode. Governed entities, incremental sync, typed landing tables.
How Datrise loads Copper into Mode
Datrise syncs Copper's Google Workspace CRM entities, opportunities, and relationship timelines into Mode as warehouse tables Mode queries with SQL. Flexible or custom fields land in flattened columns for SQL and notebooks, and timestamps such as created, updated, and status changes are typed as temporal columns.
Sync is incremental: Datrise uses incremental refresh of the queried tables, so re-runs update only what changed. Date-partitioned facts for report queries. Mode runs analyst-written SQL, so Datrise lands stable, documented tables that won't break saved reports.
Ideal for SQL-first analysis with Python and R notebooks.
Endpoints
Copper: Google Workspace-native CRM.
Mode: Collaborative analytics workspace for SQL, Python, and shared reports.
How Copper entities map to Mode
| Copper entity | Mode object | Notes |
|---|---|---|
| Google Workspace CRM entities | copper_google_workspace_crm_entities | id PK · custom fields → flattened columns for SQL and notebooks |
| opportunities | copper_opportunities | id PK · linked to copper_google_workspace_crm_entities |
| relationship timelines | copper_relationship_timelines | temporal columns events |
FAQ
How does Datrise handle Copper's custom fields in Mode?
Flexible values are stored as flattened columns for SQL and notebooks, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Mode types.
How does the Copper to Mode sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the queried tables.
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