Snowplow → Spreadsheets
AI-first ETL from Snowplow into Spreadsheets. Governed entities, incremental sync, typed landing tables.
How Datrise loads Snowplow into Spreadsheets
Datrise syncs Snowplow's records, events, and configuration objects into Spreadsheets as a tab per source entity. Flexible or custom fields land in JSON-stringified cells for nested fields, and timestamps such as created, updated, and status changes are typed as ISO-8601 text or serial date cells.
Sync is incremental: Datrise uses refreshes the tab's rows each run, preserving header order, so re-runs update only what changed. Sheets caps out around the low millions of cells, so Datrise lands a curated column set rather than every raw field.
Ideal for lightweight, shareable reporting for non-technical teams.
Endpoints
Snowplow: SaaS or API data source for analytics and warehouse sync.
Spreadsheets: Business-friendly spreadsheet destination for collaborative analysis.
How Snowplow entities map to Spreadsheets
| Snowplow entity | Spreadsheets object | Notes |
|---|---|---|
| records | snowplow_records | id PK · custom fields → JSON-stringified cells for nested fields |
| events | snowplow_events | ISO-8601 text or serial date cells events |
| configuration objects | snowplow_configuration_objects | id PK · linked to snowplow_records |
FAQ
How does Datrise handle Snowplow's custom fields in Spreadsheets?
Flexible values are stored as JSON-stringified cells for nested fields, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Spreadsheets types.
How does the Snowplow to Spreadsheets sync stay up to date?
It runs incrementally — Datrise uses refreshes the tab's rows each run, preserving header order.
Related pipelines
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Early access
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