Totango → Sisense
AI-first ETL from Totango into Sisense. Governed entities, incremental sync, typed landing tables.
How Datrise loads Totango into Sisense
Datrise syncs Totango'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
Totango: Customer success platform for health scores, playbooks, and renewals.
Sisense: Analytics platform with elastic data models and embedded analytics.
How Totango entities map to Sisense
| Totango entity | Sisense object | Notes |
|---|---|---|
| contacts | totango_contacts | id PK · custom fields → flattened columns for the cube |
| accounts | totango_accounts | id PK · linked to totango_contacts |
| deals | totango_deals | id PK · linked to totango_contacts |
| activities | totango_activities | date/time fields events |
FAQ
How does Datrise handle Totango'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 Totango to Sisense sync stay up to date?
It runs incrementally — Datrise uses incremental ElastiCube builds on changed rows.
Related pipelines
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