LookML to GoodData Integration
AI-first ETL from LookML into GoodData. Governed entities, incremental sync, typed landing tables.
How Datrise loads LookML into GoodData
Datrise syncs LookML's models, explores, views, dimensions, measures, and joins 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
LookML: Semantic model definitions behind Looker content.
GoodData: Composable analytics platform with headless BI and embedded dashboards.
How LookML entities map to GoodData
| LookML entity | GoodData object | Notes |
|---|---|---|
| models | lookml_models | id PK · custom fields → flattened columns |
| explores | lookml_explores | id PK · linked to lookml_models |
| views | lookml_views | id PK · linked to lookml_models |
| dimensions | lookml_dimensions | id PK · linked to lookml_models |
FAQ
How does Datrise handle LookML'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 LookML to GoodData sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables.
Related pipelines
More destinations for LookML
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