DatriseAI-first ETL

Google Drive Looker Studio

AI-first ETL from Google Drive into Looker Studio. Governed entities, incremental sync, typed landing tables.

How Datrise loads Google Drive into Looker Studio

Datrise syncs Google Drive's files, folders, permissions, and revision metadata into Looker Studio as warehouse tables Looker Studio connects to. Flexible or custom fields land in flattened columns for chart fields, and timestamps such as created, updated, and status changes are typed as date dimension columns.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned tables to keep extract refresh fast. Looker Studio performs best on pre-aggregated tables, so Datrise lands tidy, report-shaped tables rather than raw API payloads.

Ideal for free, shareable dashboards on Google data sources.

Endpoints

Google Drive: Cloud file storage often used for operational exports.

Looker Studio: Google self-service dashboards and reporting (formerly Data Studio).

How Google Drive entities map to Looker Studio

Google Drive entityLooker Studio objectNotes
filesgoogle_drive_filesid PK · custom fields → flattened columns for chart fields
foldersgoogle_drive_foldersid PK · linked to google_drive_files
permissionsgoogle_drive_permissionsid PK · linked to google_drive_files
revision metadatagoogle_drive_revision_metadataid PK · linked to google_drive_files

FAQ

How does Datrise handle Google Drive's custom fields in Looker Studio?

Flexible values are stored as flattened columns for chart fields, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Looker Studio types.

How does the Google Drive to Looker Studio sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the connected tables.

Related pipelines

Early access

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