DatriseAI-first ETL

WorkRamp to Sisense Integration

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

How Datrise loads WorkRamp into Sisense

Datrise syncs WorkRamp's courses, learners, enrollments, completions, assignments, and certifications 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

WorkRamp: Employee training, courses, and completion tracking.

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

How WorkRamp entities map to Sisense

WorkRamp entitySisense objectNotes
coursesworkramp_coursesid PK · custom fields → flattened columns for the cube
learnersworkramp_learnersid PK · linked to workramp_courses
enrollmentsworkramp_enrollmentsid PK · linked to workramp_courses
completionsworkramp_completionsid PK · linked to workramp_courses

FAQ

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

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

Related pipelines

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