Nutshell → Looker Studio
AI-first ETL from Nutshell into Looker Studio. Governed entities, incremental sync, typed landing tables.
How Datrise loads Nutshell into Looker Studio
Datrise syncs Nutshell's pipeline records, activity history, and conversion-focused sales metrics into Looker Studio as warehouse tables Looker Studio connects to. Flexible or custom fields land in flattened columns for chart fields, and timestamps such as created, updated, and status changes are typed as date dimension columns.
Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned tables to keep extract refresh fast. Looker Studio performs best on pre-aggregated tables, so Datrise lands tidy, report-shaped tables rather than raw API payloads.
Ideal for free, shareable dashboards on Google data sources.
Endpoints
Nutshell: Sales CRM for teams that need simple reporting and pipeline velocity.
Looker Studio: Google self-service dashboards and reporting (formerly Data Studio).
How Nutshell entities map to Looker Studio
| Nutshell entity | Looker Studio object | Notes |
|---|---|---|
| pipeline records | nutshell_pipeline_records | id PK · custom fields → flattened columns for chart fields |
| activity history | nutshell_activity_history | date 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 Studio?
Flexible values are stored as flattened columns for chart fields, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Looker Studio types.
How does the Nutshell to Looker Studio sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables.
Related pipelines
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