YouTube Analytics to Birst Integration

How Datrise loads YouTube Analytics into Birst

Datrise syncs YouTube Analytics's videos, channels, views, watch time, subscribers, and traffic sources 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

YouTube Analytics: Channel and video performance reporting.

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

How YouTube Analytics entities map to Birst

YouTube Analytics entity	Birst object	Notes
videos	`youtube_analytics_videos`	id PK · custom fields → flattened columns
channels	`youtube_analytics_channels`	id PK · linked to youtube_analytics_videos
views	`youtube_analytics_views`	id PK · linked to youtube_analytics_videos
watch time	`youtube_analytics_watch_time`	id PK · linked to youtube_analytics_videos

FAQ

How does Datrise handle YouTube Analytics'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 YouTube Analytics 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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