Mindbody → Mode
AI-first ETL from Mindbody into Mode. Governed entities, incremental sync, typed landing tables.
How Datrise loads Mindbody into Mode
Datrise syncs Mindbody's contacts, accounts, deals, activities, and lifecycle events into Mode as warehouse tables Mode queries with SQL. Flexible or custom fields land in flattened columns for SQL and notebooks, and timestamps such as created, updated, and status changes are typed as temporal columns.
Sync is incremental: Datrise uses incremental refresh of the queried tables, so re-runs update only what changed. Date-partitioned facts for report queries. Mode runs analyst-written SQL, so Datrise lands stable, documented tables that won't break saved reports.
Ideal for SQL-first analysis with Python and R notebooks.
Endpoints
Mindbody: Wellness and fitness CRM for members, bookings, and retention.
Mode: Collaborative analytics workspace for SQL, Python, and shared reports.
How Mindbody entities map to Mode
| Mindbody entity | Mode object | Notes |
|---|---|---|
| contacts | mindbody_contacts | id PK · custom fields → flattened columns for SQL and notebooks |
| accounts | mindbody_accounts | id PK · linked to mindbody_contacts |
| deals | mindbody_deals | id PK · linked to mindbody_contacts |
| activities | mindbody_activities | temporal columns events |
FAQ
How does Datrise handle Mindbody's custom fields in Mode?
Flexible values are stored as flattened columns for SQL and notebooks, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Mode types.
How does the Mindbody to Mode sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the queried tables.
Related pipelines
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Early access
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