DatriseAI-first ETL

EngageBay Sisense

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

How Datrise loads EngageBay into Sisense

Datrise syncs EngageBay'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

EngageBay: CRM for SMB teams managing pipeline, contacts, and customer activity.

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

How EngageBay entities map to Sisense

EngageBay entitySisense objectNotes
contactsengagebay_contactsid PK · custom fields → flattened columns for the cube
accountsengagebay_accountsid PK · linked to engagebay_contacts
dealsengagebay_dealsid PK · linked to engagebay_contacts
activitiesengagebay_activitiesdate/time fields events

FAQ

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

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

Related pipelines

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