DatriseAI-first ETL

Google Directory to Looker Studio Integration

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

How Datrise loads Google Directory into Looker Studio

Datrise syncs Google Directory's users, groups, group members, organizational units, devices, and roles 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 Directory: Workspace user, group, and device directory.

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

How Google Directory entities map to Looker Studio

Google Directory entityLooker Studio objectNotes
usersgoogle_directory_usersid PK · custom fields → flattened columns for chart fields
groupsgoogle_directory_groupsid PK · linked to google_directory_users
group membersgoogle_directory_group_membersid PK · linked to google_directory_users
organizational unitsgoogle_directory_organizational_unitsid PK · linked to google_directory_users

FAQ

How does Datrise handle Google Directory'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 Directory to Looker Studio sync stay up to date?

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

Related pipelines

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