Toggl to GoodData Integration
AI-first ETL from Toggl into GoodData. Governed entities, incremental sync, typed landing tables.
How Datrise loads Toggl into GoodData
Datrise syncs Toggl's time entries, projects, clients, workspaces, tags, and users 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
Toggl: Time tracking with projects, clients, and reports.
GoodData: Composable analytics platform with headless BI and embedded dashboards.
How Toggl entities map to GoodData
| Toggl entity | GoodData object | Notes |
|---|---|---|
| time entries | toggl_time_entries | id PK · custom fields → flattened columns |
| projects | toggl_projects | id PK · linked to toggl_time_entries |
| clients | toggl_clients | id PK · linked to toggl_time_entries |
| workspaces | toggl_workspaces | id PK · linked to toggl_time_entries |
FAQ
How does Datrise handle Toggl'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 Toggl to GoodData sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables.
Related pipelines
More destinations for Toggl
Early access
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