Mindbody to Looker Studio Integration
AI-first ETL from Mindbody into Looker Studio. Governed entities, incremental sync, typed landing tables.
How Datrise loads Mindbody into Looker Studio
Datrise syncs Mindbody's clients, class bookings, memberships, staff, sales, and appointments 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
Mindbody: Booking and membership platform for wellness studios.
Looker Studio: Google self-service dashboards and reporting (formerly Data Studio).
How Mindbody entities map to Looker Studio
| Mindbody entity | Looker Studio object | Notes |
|---|---|---|
| clients | mindbody_clients | id PK · custom fields → flattened columns for chart fields |
| class bookings | mindbody_class_bookings | id PK · linked to mindbody_clients |
| memberships | mindbody_memberships | id PK · linked to mindbody_clients |
| staff | mindbody_staff | id PK · linked to mindbody_clients |
FAQ
How does Datrise handle Mindbody'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 Mindbody 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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