DatriseAI-first ETL

Mindbody Birst

AI-first ETL from Mindbody into Birst. Governed entities, incremental sync, typed landing tables.

How Datrise loads Mindbody into Birst

Datrise syncs Mindbody's contacts, accounts, deals, activities, and lifecycle events 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: Wellness and fitness CRM for members, bookings, and retention.

Birst: Cloud BI with networked analytics and enterprise semantic layers.

How Mindbody entities map to Birst

Mindbody entityBirst objectNotes
contactsmindbody_contactsid PK · custom fields → flattened columns
accountsmindbody_accountsid PK · linked to mindbody_contacts
dealsmindbody_dealsid PK · linked to mindbody_contacts
activitiesmindbody_activitiesdate/time dimensions events

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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