DatriseAI-first ETL

Salesforce Pardot to Looker Studio Integration

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 prospects, campaigns, list emails, forms, lead scores, and engagement history 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: B2B marketing automation scoring and nurturing leads.

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

How Salesforce Pardot entities map to Looker Studio

Salesforce Pardot entityLooker Studio objectNotes
prospectssalesforce_pardot_prospectsid PK · custom fields → flattened columns for chart fields
campaignssalesforce_pardot_campaignsid PK · linked to salesforce_pardot_prospects
list emailssalesforce_pardot_list_emailsid PK · linked to salesforce_pardot_prospects
formssalesforce_pardot_formsid PK · linked to salesforce_pardot_prospects

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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