DatriseAI-first ETL

Close Mode

AI-first ETL from Close into Mode. Governed entities, incremental sync, typed landing tables.

How Datrise loads Close into Mode

Datrise syncs Close's leads, opportunities, calls, SMS events, and sequence performance 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

Close: Inside-sales CRM with calling and sequences.

Mode: Collaborative analytics workspace for SQL, Python, and shared reports.

How Close entities map to Mode

Close entityMode objectNotes
leadsclose_leadsid PK · custom fields → flattened columns for SQL and notebooks
opportunitiesclose_opportunitiesid PK · linked to close_leads
callsclose_callsid PK · linked to close_leads
SMS eventsclose_sms_eventstemporal columns events

FAQ

How does Datrise handle Close'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 Close to Mode sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the queried tables.

Related pipelines

Early access

Connect Close to Mode the easy way

Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.