folk to Sisense Integration
AI-first ETL from folk into Sisense. Governed entities, incremental sync, typed landing tables.
How Datrise loads folk into Sisense
Datrise syncs folk's contacts, groups, deals, custom fields, interactions, and reminders into Sisense as modeled tables for a Sisense ElastiCube (or live connection). Flexible or custom fields land in flattened columns for the cube, and timestamps such as created, updated, and status changes are typed as date/time fields.
Sync is incremental: Datrise uses incremental ElastiCube builds on changed rows, so re-runs update only what changed. Date-partitioned facts to speed cube builds. ElastiCube is an in-memory model, so Datrise lands incremental, build-friendly tables rather than forcing full rebuilds.
Ideal for embedded analytics on an in-memory engine.
Endpoints
folk: Lightweight relationship CRM built on shared contact groups.
Sisense: Analytics platform with elastic data models and embedded analytics.
How folk entities map to Sisense
| folk entity | Sisense object | Notes |
|---|---|---|
| contacts | folk_contacts | id PK · custom fields → flattened columns for the cube |
| groups | folk_groups | id PK · linked to folk_contacts |
| deals | folk_deals | id PK · linked to folk_contacts |
| custom fields | folk_custom_fields | id PK · linked to folk_contacts |
FAQ
How does Datrise handle folk's custom fields in Sisense?
Flexible values are stored as flattened columns for the cube, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Sisense types.
How does the folk to Sisense sync stay up to date?
It runs incrementally — Datrise uses incremental ElastiCube builds on changed rows.
Related pipelines
More destinations for folk
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