Apollo → Tableau
AI-first ETL from Apollo into Tableau. Governed entities, incremental sync, typed landing tables.
How Datrise loads Apollo into Tableau
Datrise syncs Apollo's sales intelligence records, account engagement, and outbound activity 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
Apollo: Sales intelligence and engagement platform with account-level activity.
Tableau: Salesforce analytics platform for interactive dashboards and visual exploration.
How Apollo entities map to Tableau
| Apollo entity | Tableau object | Notes |
|---|---|---|
| sales intelligence records | apollo_sales_intelligence_records | id PK · custom fields → flattened columns for Tableau fields |
| account engagement | apollo_account_engagement | id PK · linked to apollo_sales_intelligence_records |
| outbound activity | apollo_outbound_activity | date/datetime fields events |
FAQ
How does Datrise handle Apollo'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 Apollo 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
More destinations for Apollo
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