DatriseAI-first ETL

Google Directory to Amazon QuickSight Integration

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

How Datrise loads Google Directory into Amazon QuickSight

Datrise syncs Google Directory's users, groups, group members, organizational units, devices, and roles into Amazon QuickSight as warehouse tables or a SPICE-loaded dataset. Flexible or custom fields land in flattened columns for analyses, and timestamps such as created, updated, and status changes are typed as date/time fields.

Sync is incremental: Datrise uses incremental refresh of the tables behind SPICE or direct query, so re-runs update only what changed. Date-partitioned facts to bound SPICE refresh. QuickSight SPICE is an in-memory copy, so Datrise keeps the backing tables incremental so refreshes stay cheap.

Ideal for AWS-native dashboards with pay-per-session pricing.

Endpoints

Google Directory: Workspace user, group, and device directory.

Amazon QuickSight: AWS serverless BI with SPICE and embedded analytics.

How Google Directory entities map to Amazon QuickSight

Google Directory entityAmazon QuickSight objectNotes
usersgoogle_directory_usersid PK · custom fields → flattened columns for analyses
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 Amazon QuickSight?

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

How does the Google Directory to Amazon QuickSight sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the tables behind SPICE or direct query.

Related pipelines

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