DatriseAI-first ETL

Referral Saasquatch Sisense

AI-first ETL from Referral Saasquatch into Sisense. Governed entities, incremental sync, typed landing tables.

How Datrise loads Referral Saasquatch into Sisense

Datrise syncs Referral Saasquatch's records, events, and configuration objects 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

Referral Saasquatch: SaaS or API data source for analytics and warehouse sync.

Sisense: Analytics platform with elastic data models and embedded analytics.

How Referral Saasquatch entities map to Sisense

Referral Saasquatch entitySisense objectNotes
recordsreferral_saasquatch_recordsid PK · custom fields → flattened columns for the cube
eventsreferral_saasquatch_eventsdate/time fields events
configuration objectsreferral_saasquatch_configuration_objectsid PK · linked to referral_saasquatch_records

FAQ

How does Datrise handle Referral Saasquatch'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 Referral Saasquatch to Sisense sync stay up to date?

It runs incrementally — Datrise uses incremental ElastiCube builds on changed rows.

Related pipelines

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