Oracle CX → Looker
AI-first ETL from Oracle CX into Looker. Governed entities, incremental sync, typed landing tables.
How Datrise loads Oracle CX into Looker
Datrise syncs Oracle CX's enterprise CX entities across sales, service, and customer operations into Looker as governed warehouse tables with LookML-ready naming. Flexible or custom fields land in flattened columns (nested fields expanded for modeling), and timestamps such as created, updated, and status changes are typed as date/time dimension columns.
Sync is incremental: Datrise uses incremental refresh of the underlying warehouse tables Looker explores, so re-runs update only what changed. Date-partitioned fact tables for PDT performance. Looker models live in LookML on top of SQL, so Datrise lands clean, stable column names rather than churn that would break your views.
Ideal for governed, version-controlled BI on a warehouse.
Endpoints
Oracle CX: Enterprise customer experience suite with sales and service data.
Looker: Google Cloud BI with LookML semantic models and governed dashboards.
How Oracle CX entities map to Looker
| Oracle CX entity | Looker object | Notes |
|---|---|---|
| enterprise CX entities across sales | oracle_cx_enterprise_cx_entities_across_sales | id PK · custom fields → flattened columns (nested fields expanded for modeling) |
| service | oracle_cx_service | id PK · linked to oracle_cx_enterprise_cx_entities_across_sales |
| customer operations | oracle_cx_customer_operations | id PK · linked to oracle_cx_enterprise_cx_entities_across_sales |
FAQ
How does Datrise handle Oracle CX's custom fields in Looker?
Flexible values are stored as flattened columns (nested fields expanded for modeling), so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Looker types.
How does the Oracle CX to Looker sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the underlying warehouse tables Looker explores.
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