Impartner to Sisense Integration
AI-first ETL from Impartner into Sisense. Governed entities, incremental sync, typed landing tables.
How Datrise loads Impartner into Sisense
Datrise syncs Impartner's partners, deal registrations, opportunities, tiers, MDF requests, and partner contacts 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
Impartner: Channel management for partner tiers and co-sell.
Sisense: Analytics platform with elastic data models and embedded analytics.
How Impartner entities map to Sisense
| Impartner entity | Sisense object | Notes |
|---|---|---|
| partners | impartner_partners | id PK · custom fields → flattened columns for the cube |
| deal registrations | impartner_deal_registrations | id PK · linked to impartner_partners |
| opportunities | impartner_opportunities | id PK · linked to impartner_partners |
| tiers | impartner_tiers | id PK · linked to impartner_partners |
FAQ
How does Datrise handle Impartner'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 Impartner to Sisense sync stay up to date?
It runs incrementally — Datrise uses incremental ElastiCube builds on changed rows.
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