DatriseAI-first ETL

Salesforce Health Cloud to Tableau Integration

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

How Datrise loads Salesforce Health Cloud into Tableau

Datrise syncs Salesforce Health Cloud's patients, care plans, care teams, clinical encounters, cases, and consents 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

Salesforce Health Cloud: Patient and member relationship management on Salesforce.

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

How Salesforce Health Cloud entities map to Tableau

Salesforce Health Cloud entityTableau objectNotes
patientssalesforce_health_cloud_patientsid PK · custom fields → flattened columns for Tableau fields
care planssalesforce_health_cloud_care_plansid PK · linked to salesforce_health_cloud_patients
care teamssalesforce_health_cloud_care_teamsid PK · linked to salesforce_health_cloud_patients
clinical encounterssalesforce_health_cloud_clinical_encountersid PK · linked to salesforce_health_cloud_patients

FAQ

How does Datrise handle Salesforce Health Cloud'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 Salesforce Health Cloud 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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