LookML to Holistics Integration
AI-first ETL from LookML into Holistics. Governed entities, incremental sync, typed landing tables.
How Datrise loads LookML into Holistics
Datrise syncs LookML's models, explores, views, dimensions, measures, and joins into Holistics as warehouse tables modeled in Holistics. Flexible or custom fields land in flattened columns for the modeling layer, and timestamps such as created, updated, and status changes are typed as date/time dimensions.
Sync is incremental: Datrise uses incremental refresh of the modeled tables, so re-runs update only what changed. Date-partitioned facts for fast aggregates. Holistics models data as code on top of SQL, so Datrise lands stable column names to keep your models from drifting.
Ideal for as-code BI modeling on a warehouse.
Endpoints
LookML: Semantic model definitions behind Looker content.
Holistics: Self-service BI with modeling layers and scheduled report delivery.
How LookML entities map to Holistics
| LookML entity | Holistics object | Notes |
|---|---|---|
| models | lookml_models | id PK · custom fields → flattened columns for the modeling layer |
| 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 Holistics?
Flexible values are stored as flattened columns for the modeling layer, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Holistics types.
How does the LookML to Holistics sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the modeled tables.
Related pipelines
More destinations for LookML
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