Nimble → GoodData
AI-first ETL from Nimble into GoodData. Governed entities, incremental sync, typed landing tables.
How Datrise loads Nimble into GoodData
Datrise syncs Nimble's relationship records, deals, tasks, and activity intelligence into GoodData as warehouse tables GoodData maps into its logical data model. Flexible or custom fields land in flattened columns, and timestamps such as created, updated, and status changes are typed as date dimensions.
Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts. GoodData's LDM maps datasets by keys, so Datrise lands stable primary and foreign id columns to keep the model valid.
Ideal for embedded, multi-tenant analytics.
Endpoints
Nimble: Relationship-focused CRM for SMB sales teams.
GoodData: Composable analytics platform with headless BI and embedded dashboards.
How Nimble entities map to GoodData
| Nimble entity | GoodData object | Notes |
|---|---|---|
| relationship records | nimble_relationship_records | id PK · custom fields → flattened columns |
| deals | nimble_deals | id PK · linked to nimble_relationship_records |
| tasks | nimble_tasks | id PK · linked to nimble_relationship_records |
| activity intelligence | nimble_activity_intelligence | date dimensions events |
FAQ
How does Datrise handle Nimble's custom fields in GoodData?
Flexible values are stored as flattened columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native GoodData types.
How does the Nimble to GoodData sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables.
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