DatriseAI-first ETL

Insightly Tableau

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

How Datrise loads Insightly into Tableau

Datrise syncs Insightly's contacts, organizations, opportunities, projects, and delivery milestones 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

Insightly: CRM and lightweight project delivery.

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

How Insightly entities map to Tableau

Insightly entityTableau objectNotes
contactsinsightly_contactsid PK · custom fields → flattened columns for Tableau fields
organizationsinsightly_organizationsid PK · linked to insightly_contacts
opportunitiesinsightly_opportunitiesid PK · linked to insightly_contacts
projectsinsightly_projectsid PK · linked to insightly_contacts

FAQ

How does Datrise handle Insightly'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 Insightly 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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