Nutshell → Looker
AI-first ETL from Nutshell into Looker. Governed entities, incremental sync, typed landing tables.
How Datrise loads Nutshell into Looker
Datrise syncs Nutshell's pipeline records, activity history, and conversion-focused sales metrics into Looker as governed warehouse tables with LookML-ready naming. Flexible or custom fields land in flattened columns (nested fields expanded for modeling), and timestamps such as created, updated, and status changes are typed as date/time dimension columns.
Sync is incremental: Datrise uses incremental refresh of the underlying warehouse tables Looker explores, so re-runs update only what changed. Date-partitioned fact tables for PDT performance. Looker models live in LookML on top of SQL, so Datrise lands clean, stable column names rather than churn that would break your views.
Ideal for governed, version-controlled BI on a warehouse.
Endpoints
Nutshell: Sales CRM for teams that need simple reporting and pipeline velocity.
Looker: Google Cloud BI with LookML semantic models and governed dashboards.
How Nutshell entities map to Looker
| Nutshell entity | Looker object | Notes |
|---|---|---|
| pipeline records | nutshell_pipeline_records | id PK · custom fields → flattened columns (nested fields expanded for modeling) |
| activity history | nutshell_activity_history | date/time dimension columns events |
| conversion-focused sales metrics | nutshell_conversion_focused_sales_metrics | id PK · linked to nutshell_pipeline_records |
FAQ
How does Datrise handle Nutshell's custom fields in Looker?
Flexible values are stored as flattened columns (nested fields expanded for modeling), so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Looker types.
How does the Nutshell to Looker sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the underlying warehouse tables Looker explores.
Related pipelines
More destinations for Nutshell
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