DatriseAI-first ETL

Freshcaller to GoodData Integration

AI-first ETL from Freshcaller into GoodData. Governed entities, incremental sync, typed landing tables.

How Datrise loads Freshcaller into GoodData

Datrise syncs Freshcaller's calls, agents, queues, phone numbers, call metrics, and recordings into GoodData as warehouse tables GoodData maps into its logical data model. Flexible or custom fields land in flattened columns, and timestamps such as created, updated, and status changes are typed as date dimensions.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts. GoodData's LDM maps datasets by keys, so Datrise lands stable primary and foreign id columns to keep the model valid.

Ideal for embedded, multi-tenant analytics.

Endpoints

Freshcaller: Cloud call center for support and sales.

GoodData: Composable analytics platform with headless BI and embedded dashboards.

How Freshcaller entities map to GoodData

Freshcaller entityGoodData objectNotes
callsfreshcaller_callsid PK · custom fields → flattened columns
agentsfreshcaller_agentsid PK · linked to freshcaller_calls
queuesfreshcaller_queuesid PK · linked to freshcaller_calls
phone numbersfreshcaller_phone_numbersid PK · linked to freshcaller_calls

FAQ

How does Datrise handle Freshcaller's custom fields in GoodData?

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 GoodData types.

How does the Freshcaller to GoodData sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the connected tables.

Related pipelines

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