DatriseAI-first ETL

Glassfrog to Tableau Integration

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

How Datrise loads Glassfrog into Tableau

Datrise syncs Glassfrog's circles, roles, people, accountabilities, projects, and governance records 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

Glassfrog: Holacracy roles, circles, and governance records.

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

How Glassfrog entities map to Tableau

Glassfrog entityTableau objectNotes
circlesglassfrog_circlesid PK · custom fields → flattened columns for Tableau fields
rolesglassfrog_rolesid PK · linked to glassfrog_circles
peopleglassfrog_peopleid PK · linked to glassfrog_circles
accountabilitiesglassfrog_accountabilitiesid PK · linked to glassfrog_circles

FAQ

How does Datrise handle Glassfrog'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 Glassfrog 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

Early access

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