Agendor → Sisense
AI-first ETL from Agendor into Sisense. Governed entities, incremental sync, typed landing tables.
How Datrise loads Agendor into Sisense
Datrise syncs Agendor'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
Agendor: CRM widely used in Latin America for sales pipeline and customer ops.
Sisense: Analytics platform with elastic data models and embedded analytics.
How Agendor entities map to Sisense
| Agendor entity | Sisense object | Notes |
|---|---|---|
| contacts | agendor_contacts | id PK · custom fields → flattened columns for the cube |
| accounts | agendor_accounts | id PK · linked to agendor_contacts |
| deals | agendor_deals | id PK · linked to agendor_contacts |
| activities | agendor_activities | date/time fields events |
FAQ
How does Datrise handle Agendor'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 Agendor to Sisense sync stay up to date?
It runs incrementally — Datrise uses incremental ElastiCube builds on changed rows.
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