DatriseAI-first ETL

Salesforce Pardot Looker Studio

AI-first ETL from Salesforce Pardot into Looker Studio. Governed entities, incremental sync, typed landing tables.

How Datrise loads Salesforce Pardot into Looker Studio

Datrise syncs Salesforce Pardot'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

Salesforce Pardot: Marketing automation platform with CRM and lifecycle engagement.

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

How Salesforce Pardot entities map to Looker Studio

Salesforce Pardot entityLooker Studio objectNotes
contactssalesforce_pardot_contactsid PK · custom fields → flattened columns for chart fields
accountssalesforce_pardot_accountsid PK · linked to salesforce_pardot_contacts
dealssalesforce_pardot_dealsid PK · linked to salesforce_pardot_contacts
activitiessalesforce_pardot_activitiesdate dimension columns events

FAQ

How does Datrise handle Salesforce Pardot'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 Salesforce Pardot 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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