Freshdesk → GoodData
AI-first ETL from Freshdesk into GoodData. Governed entities, incremental sync, typed landing tables.
How Datrise loads Freshdesk into GoodData
Datrise syncs Freshdesk's tickets, contacts, agents, SLA events, and satisfaction scores 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
Freshdesk: Customer support helpdesk with tickets, SLAs, and agent workflows.
GoodData: Composable analytics platform with headless BI and embedded dashboards.
How Freshdesk entities map to GoodData
| Freshdesk entity | GoodData object | Notes |
|---|---|---|
| tickets | freshdesk_tickets | id PK · custom fields → flattened columns |
| contacts | freshdesk_contacts | id PK · linked to freshdesk_tickets |
| agents | freshdesk_agents | id PK · linked to freshdesk_tickets |
| SLA events | freshdesk_sla_events | date dimensions events |
FAQ
How does Datrise handle Freshdesk'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 Freshdesk to GoodData sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables.
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