Apollo → Yellowfin
AI-first ETL from Apollo into Yellowfin. Governed entities, incremental sync, typed landing tables.
How Datrise loads Apollo into Yellowfin
Datrise syncs Apollo's sales intelligence records, account engagement, and outbound activity into Yellowfin as warehouse tables Yellowfin builds views on. Flexible or custom fields land in flattened columns, and timestamps such as created, updated, and status changes are typed as date/time dimensions.
Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts. Yellowfin views reference columns by name, so Datrise lands stable, well-typed columns to keep reports valid.
Ideal for dashboards with automated data storytelling.
Endpoints
Apollo: Sales intelligence and engagement platform with account-level activity.
Yellowfin: BI suite with dashboards, automated insights, and data storytelling.
How Apollo entities map to Yellowfin
| Apollo entity | Yellowfin object | Notes |
|---|---|---|
| sales intelligence records | apollo_sales_intelligence_records | id PK · custom fields → flattened columns |
| account engagement | apollo_account_engagement | id PK · linked to apollo_sales_intelligence_records |
| outbound activity | apollo_outbound_activity | date/time dimensions events |
FAQ
How does Datrise handle Apollo's custom fields in Yellowfin?
Flexible values are stored as flattened columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Yellowfin types.
How does the Apollo to Yellowfin sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables.
Related pipelines
More destinations for Apollo
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