Mindbody to Birst Integration
AI-first ETL from Mindbody into Birst. Governed entities, incremental sync, typed landing tables.
How Datrise loads Mindbody into Birst
Datrise syncs Mindbody's clients, class bookings, memberships, staff, sales, and appointments into Birst as warehouse tables for Birst's automated star schema. Flexible or custom fields land in flattened columns, and timestamps such as created, updated, and status changes are typed as date/time dimensions.
Sync is incremental: Datrise uses incremental refresh of the source tables Birst ingests, so re-runs update only what changed. Date-partitioned facts. Birst builds its own semantic layer, so Datrise lands conformed, well-keyed tables it can automate against.
Ideal for networked, governed enterprise BI.
Endpoints
Mindbody: Booking and membership platform for wellness studios.
Birst: Cloud BI with networked analytics and enterprise semantic layers.
How Mindbody entities map to Birst
| Mindbody entity | Birst object | Notes |
|---|---|---|
| clients | mindbody_clients | id PK · custom fields → flattened columns |
| 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 Birst?
Flexible values are stored as flattened columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Birst types.
How does the Mindbody to Birst sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the source tables Birst ingests.
Related pipelines
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Early access
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