DatriseAI-first ETL

Zendesk Sunshine to Sisense Integration

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

How Datrise loads Zendesk Sunshine into Sisense

Datrise syncs Zendesk Sunshine's custom objects, object records, profiles, events, relationships, and attributes 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

Zendesk Sunshine: Custom objects and unified customer profiles.

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

How Zendesk Sunshine entities map to Sisense

Zendesk Sunshine entitySisense objectNotes
custom objectszendesk_sunshine_custom_objectsid PK · custom fields → flattened columns for the cube
object recordszendesk_sunshine_object_recordsid PK · linked to zendesk_sunshine_custom_objects
profileszendesk_sunshine_profilesid PK · linked to zendesk_sunshine_custom_objects
eventszendesk_sunshine_eventsdate/time fields events

FAQ

How does Datrise handle Zendesk Sunshine'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 Zendesk Sunshine to Sisense sync stay up to date?

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

Related pipelines

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