DatriseAI-first ETL

HubSpot Service Hub Looker Studio

AI-first ETL from HubSpot Service Hub into Looker Studio. Governed entities, incremental sync, typed landing tables.

How Datrise loads HubSpot Service Hub into Looker Studio

Datrise syncs HubSpot Service Hub's contacts, accounts, deals, activities, and lifecycle events 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

HubSpot Service Hub: Customer service platform with ticket and conversation context.

Looker Studio: Google self-service dashboards and reporting (formerly Data Studio).

How HubSpot Service Hub entities map to Looker Studio

HubSpot Service Hub entityLooker Studio objectNotes
contactshubspot_service_contactsid PK · custom fields → flattened columns for chart fields
accountshubspot_service_accountsid PK · linked to hubspot_service_contacts
dealshubspot_service_dealsid PK · linked to hubspot_service_contacts
activitieshubspot_service_activitiesdate dimension columns events

FAQ

How does Datrise handle HubSpot Service Hub'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 HubSpot Service Hub 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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