DatriseAI-first ETL

Timely to Birst Integration

AI-first ETL from Timely into Birst. Governed entities, incremental sync, typed landing tables.

How Datrise loads Timely into Birst

Datrise syncs Timely's time entries, projects, clients, users, tags, and billable hours into Birst as warehouse tables for Birst's automated star schema. 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 source tables Birst ingests, so re-runs update only what changed. Date-partitioned facts. Birst builds its own semantic layer, so Datrise lands conformed, well-keyed tables it can automate against.

Ideal for networked, governed enterprise BI.

Endpoints

Timely: Automatic time tracking for teams and projects.

Birst: Cloud BI with networked analytics and enterprise semantic layers.

How Timely entities map to Birst

Timely entityBirst objectNotes
time entriestimely_time_entriesid PK · custom fields → flattened columns
projectstimely_projectsid PK · linked to timely_time_entries
clientstimely_clientsid PK · linked to timely_time_entries
userstimely_usersid PK · linked to timely_time_entries

FAQ

How does Datrise handle Timely's custom fields in Birst?

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 Birst types.

How does the Timely to Birst sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the source tables Birst ingests.

Related pipelines

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