Chorus.ai to Holistics Integration
AI-first ETL from Chorus.ai into Holistics. Governed entities, incremental sync, typed landing tables.
How Datrise loads Chorus.ai into Holistics
Datrise syncs Chorus.ai's calls, transcripts, deals, trackers, speakers, and engagement moments into Holistics as warehouse tables modeled in Holistics. Flexible or custom fields land in flattened columns for the modeling layer, and timestamps such as created, updated, and status changes are typed as date/time dimensions.
Sync is incremental: Datrise uses incremental refresh of the modeled tables, so re-runs update only what changed. Date-partitioned facts for fast aggregates. Holistics models data as code on top of SQL, so Datrise lands stable column names to keep your models from drifting.
Ideal for as-code BI modeling on a warehouse.
Endpoints
Chorus.ai: Conversation intelligence over recorded sales calls.
Holistics: Self-service BI with modeling layers and scheduled report delivery.
How Chorus.ai entities map to Holistics
| Chorus.ai entity | Holistics object | Notes |
|---|---|---|
| calls | chorus_calls | id PK · custom fields → flattened columns for the modeling layer |
| transcripts | chorus_transcripts | id PK · linked to chorus_calls |
| deals | chorus_deals | id PK · linked to chorus_calls |
| trackers | chorus_trackers | id PK · linked to chorus_calls |
FAQ
How does Datrise handle Chorus.ai's custom fields in Holistics?
Flexible values are stored as flattened columns for the modeling layer, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Holistics types.
How does the Chorus.ai to Holistics sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the modeled tables.
Related pipelines
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Early access
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