DatriseAI-first ETL

Google Analytics CSV Files

AI-first ETL from Google Analytics into CSV Files. Governed entities, incremental sync, typed landing tables.

How Datrise loads Google Analytics into CSV Files

Datrise syncs Google Analytics's sessions, events, channels, conversions, and behavior cohorts into CSV Files as one CSV per source entity. Flexible or custom fields land in JSON-encoded strings for nested fields, and timestamps such as created, updated, and status changes are typed as ISO-8601 timestamp columns.

Sync is incremental: Datrise uses writes a fresh, fully-typed CSV per entity each run, so re-runs update only what changed. Optional date-suffixed files for change tracking. CSV has no types, so Datrise emits a companion schema and quotes/escapes consistently so downstream loaders don't misparse commas and newlines.

Ideal for portable hand-off into any tool that ingests delimited files.

Endpoints

Google Analytics: Web and product analytics for behavior and traffic insights.

CSV Files: Flat-file destination for exports and lightweight data sharing.

How Google Analytics entities map to CSV Files

Google Analytics entityCSV Files objectNotes
sessionsgoogle_analytics_sessionsid PK · custom fields → JSON-encoded strings for nested fields
eventsgoogle_analytics_eventsISO-8601 timestamp columns events
channelsgoogle_analytics_channelsid PK · linked to google_analytics_sessions
conversionsgoogle_analytics_conversionsid PK · linked to google_analytics_sessions

FAQ

How does Datrise handle Google Analytics's custom fields in CSV Files?

Flexible values are stored as JSON-encoded strings for nested fields, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native CSV Files types.

How does the Google Analytics to CSV Files sync stay up to date?

It runs incrementally — Datrise uses writes a fresh, fully-typed CSV per entity each run.

Related pipelines

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