Apollo → Looker Studio
AI-first ETL from Apollo into Looker Studio. Governed entities, incremental sync, typed landing tables.
How Datrise loads Apollo into Looker Studio
Datrise syncs Apollo's sales intelligence records, account engagement, and outbound activity 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
Apollo: Sales intelligence and engagement platform with account-level activity.
Looker Studio: Google self-service dashboards and reporting (formerly Data Studio).
How Apollo entities map to Looker Studio
| Apollo entity | Looker Studio object | Notes |
|---|---|---|
| sales intelligence records | apollo_sales_intelligence_records | id PK · custom fields → flattened columns for chart fields |
| account engagement | apollo_account_engagement | id PK · linked to apollo_sales_intelligence_records |
| outbound activity | apollo_outbound_activity | date dimension columns events |
FAQ
How does Datrise handle Apollo'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 Apollo to Looker Studio sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables.
Related pipelines
More destinations for Apollo
More sources for Looker Studio
Early access
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