Dixa → Yellowfin
AI-first ETL from Dixa into Yellowfin. Governed entities, incremental sync, typed landing tables.
How Datrise loads Dixa into Yellowfin
Datrise syncs Dixa's conversations, agents, customers, tags, and resolution metrics 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
Dixa: Customer service platform for conversations across channels.
Yellowfin: BI suite with dashboards, automated insights, and data storytelling.
How Dixa entities map to Yellowfin
| Dixa entity | Yellowfin object | Notes |
|---|---|---|
| conversations | dixa_conversations | id PK · custom fields → flattened columns |
| agents | dixa_agents | id PK · linked to dixa_conversations |
| customers | dixa_customers | id PK · linked to dixa_conversations |
| tags | dixa_tags | id PK · linked to dixa_conversations |
FAQ
How does Datrise handle Dixa'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 Dixa to Yellowfin sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables.
Related pipelines
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