DatriseAI-first ETL

kvCORE Sisense

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

How Datrise loads kvCORE into Sisense

Datrise syncs kvCORE's contacts, accounts, deals, activities, and lifecycle events 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

kvCORE: Real estate CRM for leads, listings, and agent follow-up.

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

How kvCORE entities map to Sisense

kvCORE entitySisense objectNotes
contactskvcore_contactsid PK · custom fields → flattened columns for the cube
accountskvcore_accountsid PK · linked to kvcore_contacts
dealskvcore_dealsid PK · linked to kvcore_contacts
activitieskvcore_activitiesdate/time fields events

FAQ

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

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

Related pipelines

Early access

Connect kvCORE to Sisense the easy way

Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.