folk → Yellowfin
AI-first ETL from folk into Yellowfin. Governed entities, incremental sync, typed landing tables.
How Datrise loads folk into Yellowfin
Datrise syncs folk's contacts, accounts, deals, activities, and lifecycle events into Yellowfin as warehouse tables Yellowfin builds views on. 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 connected tables, so re-runs update only what changed. Date-partitioned facts. Yellowfin views reference columns by name, so Datrise lands stable, well-typed columns to keep reports valid.
Ideal for dashboards with automated data storytelling.
Endpoints
folk: AI-native CRM for relationship data, enrichment, and workflow automation.
Yellowfin: BI suite with dashboards, automated insights, and data storytelling.
How folk entities map to Yellowfin
| folk entity | Yellowfin object | Notes |
|---|---|---|
| contacts | folk_contacts | id PK · custom fields → flattened columns |
| accounts | folk_accounts | id PK · linked to folk_contacts |
| deals | folk_deals | id PK · linked to folk_contacts |
| activities | folk_activities | date/time dimensions events |
FAQ
How does Datrise handle folk's custom fields in Yellowfin?
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 Yellowfin types.
How does the folk to Yellowfin sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables.
Related pipelines
More destinations for folk
Early access
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