DatriseAI-first ETL

Practifi to Looker Studio Integration

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

How Datrise loads Practifi into Looker Studio

Datrise syncs Practifi's clients, households, entities, service requests, opportunities, and review meetings 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

Practifi: Salesforce-based platform for advisory firm operations.

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

How Practifi entities map to Looker Studio

Practifi entityLooker Studio objectNotes
clientspractifi_clientsid PK · custom fields → flattened columns for chart fields
householdspractifi_householdsid PK · linked to practifi_clients
entitiespractifi_entitiesid PK · linked to practifi_clients
service requestspractifi_service_requestsid PK · linked to practifi_clients

FAQ

How does Datrise handle Practifi'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 Practifi 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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