DatriseAI-first ETL

Klaviyo Sisense

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

How Datrise loads Klaviyo into Sisense

Datrise syncs Klaviyo's profiles, segments, flows, campaigns, and attributed revenue 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

Klaviyo: E-commerce marketing automation with email and SMS.

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

How Klaviyo entities map to Sisense

Klaviyo entitySisense objectNotes
profilesklaviyo_profilesid PK · custom fields → flattened columns for the cube
segmentsklaviyo_segmentsid PK · linked to klaviyo_profiles
flowsklaviyo_flowsid PK · linked to klaviyo_profiles
campaignsklaviyo_campaignsid PK · linked to klaviyo_profiles

FAQ

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

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

Related pipelines

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