Google Analytics 4 to Sisense Integration
AI-first ETL from Google Analytics 4 into Sisense. Governed entities, incremental sync, typed landing tables.
How Datrise loads Google Analytics 4 into Sisense
Datrise syncs Google Analytics 4's events, users, sessions, traffic sources, conversions, and audiences 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
Google Analytics 4: Event-based web and app analytics from Google.
Sisense: Analytics platform with elastic data models and embedded analytics.
How Google Analytics 4 entities map to Sisense
| Google Analytics 4 entity | Sisense object | Notes |
|---|---|---|
| events | ga4_events | date/time fields events |
| users | ga4_users | id PK · linked to ga4_events |
| sessions | ga4_sessions | id PK · linked to ga4_events |
| traffic sources | ga4_traffic_sources | id PK · linked to ga4_events |
FAQ
How does Datrise handle Google Analytics 4'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 Google Analytics 4 to Sisense sync stay up to date?
It runs incrementally — Datrise uses incremental ElastiCube builds on changed rows.
Related pipelines
More destinations for Google Analytics 4
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Early access
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