DatriseAI-first ETL

Google Cloud SQL Tableau

AI-first ETL from Google Cloud SQL into Tableau. Governed entities, incremental sync, typed landing tables.

How Datrise loads Google Cloud SQL into Tableau

Datrise syncs Google Cloud SQL's records, events, and configuration objects into Tableau as warehouse tables or a refreshed .hyper extract. Flexible or custom fields land in flattened columns for Tableau fields, and timestamps such as created, updated, and status changes are typed as date/datetime fields.

Sync is incremental: Datrise uses incremental refresh of the tables behind a live connection or extract, so re-runs update only what changed. Date-partitioned facts to keep extract refresh quick. Tableau .hyper extracts snapshot data, so Datrise keeps the source tables incremental and lets you choose live vs extract.

Ideal for visual analytics and dashboards in Tableau.

Endpoints

Google Cloud SQL: SaaS or API data source for analytics and warehouse sync.

Tableau: Salesforce analytics platform for interactive dashboards and visual exploration.

How Google Cloud SQL entities map to Tableau

Google Cloud SQL entityTableau objectNotes
recordsgoogle_cloud_sql_recordsid PK · custom fields → flattened columns for Tableau fields
eventsgoogle_cloud_sql_eventsdate/datetime fields events
configuration objectsgoogle_cloud_sql_configuration_objectsid PK · linked to google_cloud_sql_records

FAQ

How does Datrise handle Google Cloud SQL's custom fields in Tableau?

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

How does the Google Cloud SQL to Tableau sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the tables behind a live connection or extract.

Related pipelines

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