Google Cloud Storage to Looker Integration
AI-first ETL from Google Cloud Storage into Looker. Governed entities, incremental sync, typed landing tables.
How Datrise loads Google Cloud Storage into Looker
Datrise syncs Google Cloud Storage's buckets, objects, prefixes, object metadata, generations, and storage classes 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
Google Cloud Storage: Object storage for files and data lake exports on GCP.
Looker: Google Cloud BI with LookML semantic models and governed dashboards.
How Google Cloud Storage entities map to Looker
| Google Cloud Storage entity | Looker object | Notes |
|---|---|---|
| buckets | google_cloud_storage_f_buckets | id PK · custom fields → flattened columns (nested fields expanded for modeling) |
| objects | google_cloud_storage_f_objects | id PK · linked to google_cloud_storage_f_buckets |
| prefixes | google_cloud_storage_f_prefixes | id PK · linked to google_cloud_storage_f_buckets |
| object metadata | google_cloud_storage_f_object_metadata | id PK · linked to google_cloud_storage_f_buckets |
FAQ
How does Datrise handle Google Cloud Storage'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 Google Cloud Storage to Looker sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the underlying warehouse tables Looker explores.
Related pipelines
More destinations for Google Cloud Storage
- Google Cloud Storage → Looker Studio
- Google Cloud Storage → Microsoft Power BI
- Google Cloud Storage → Tableau
- Google Cloud Storage → Apache Superset
- Google Cloud Storage → Metabase
- Google Cloud Storage → Amazon QuickSight
- Google Cloud Storage → Domo
- Google Cloud Storage → Sisense
- Google Cloud Storage → ThoughtSpot
- Google Cloud Storage → Qlik
- Google Cloud Storage → Mode
- Google Cloud Storage → Redash
Early access
Connect Google Cloud Storage to Looker the easy way
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