DatriseAI-first ETL

LookML to Birst Integration

AI-first ETL from LookML into Birst. Governed entities, incremental sync, typed landing tables.

How Datrise loads LookML into Birst

Datrise syncs LookML's models, explores, views, dimensions, measures, and joins into Birst as warehouse tables for Birst's automated star schema. Flexible or custom fields land in flattened columns, and timestamps such as created, updated, and status changes are typed as date/time dimensions.

Sync is incremental: Datrise uses incremental refresh of the source tables Birst ingests, so re-runs update only what changed. Date-partitioned facts. Birst builds its own semantic layer, so Datrise lands conformed, well-keyed tables it can automate against.

Ideal for networked, governed enterprise BI.

Endpoints

LookML: Semantic model definitions behind Looker content.

Birst: Cloud BI with networked analytics and enterprise semantic layers.

How LookML entities map to Birst

LookML entityBirst objectNotes
modelslookml_modelsid PK · custom fields → flattened columns
exploreslookml_exploresid PK · linked to lookml_models
viewslookml_viewsid PK · linked to lookml_models
dimensionslookml_dimensionsid PK · linked to lookml_models

FAQ

How does Datrise handle LookML's custom fields in Birst?

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 Birst types.

How does the LookML to Birst sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the source tables Birst ingests.

Related pipelines

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