Vitally to Holistics Integration
AI-first ETL from Vitally into Holistics. Governed entities, incremental sync, typed landing tables.
How Datrise loads Vitally into Holistics
Datrise syncs Vitally's accounts, users, health scores, tasks, playbooks, and product usage into Holistics as warehouse tables modeled in Holistics. Flexible or custom fields land in flattened columns for the modeling layer, and timestamps such as created, updated, and status changes are typed as date/time dimensions.
Sync is incremental: Datrise uses incremental refresh of the modeled tables, so re-runs update only what changed. Date-partitioned facts for fast aggregates. Holistics models data as code on top of SQL, so Datrise lands stable column names to keep your models from drifting.
Ideal for as-code BI modeling on a warehouse.
Endpoints
Vitally: Customer success health and account analytics.
Holistics: Self-service BI with modeling layers and scheduled report delivery.
How Vitally entities map to Holistics
| Vitally entity | Holistics object | Notes |
|---|---|---|
| accounts | vitally_accounts | id PK · custom fields → flattened columns for the modeling layer |
| users | vitally_users | id PK · linked to vitally_accounts |
| health scores | vitally_health_scores | id PK · linked to vitally_accounts |
| tasks | vitally_tasks | id PK · linked to vitally_accounts |
FAQ
How does Datrise handle Vitally's custom fields in Holistics?
Flexible values are stored as flattened columns for the modeling layer, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Holistics types.
How does the Vitally to Holistics sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the modeled tables.
Related pipelines
More destinations for Vitally
Early access
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