Zendesk Sell → Google BigQuery
AI-first ETL from Zendesk Sell into Google BigQuery. Governed entities, incremental sync, typed landing tables.
How Datrise loads Zendesk Sell into Google BigQuery
Datrise syncs Zendesk Sell's leads, deals, activities, and Zendesk-aligned sales operations into Google BigQuery as a partitioned table per source entity. Flexible or custom fields land in JSON or nested/repeated (STRUCT) columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP.
Sync is incremental: Datrise uses appends to a staging table, then MERGE on stable id into the partitioned target, so re-runs update only what changed. Partition by ingestion or event date and cluster by entity id to keep scanned bytes low. BigQuery bills by bytes scanned, so Datrise partitions and clusters every table to keep query costs predictable.
Ideal for Google-stack analytics and ML on serverless infrastructure.
Endpoints
Zendesk Sell: Sales CRM for lead and deal tracking in Zendesk ecosystems.
Google BigQuery: Serverless analytics warehouse on GCP.
How Zendesk Sell entities map to Google BigQuery
| Zendesk Sell entity | Google BigQuery object | Notes |
|---|---|---|
| leads | zendesk_sell_leads | id PK · custom fields → JSON or nested/repeated (STRUCT) columns |
| deals | zendesk_sell_deals | id PK · linked to zendesk_sell_leads |
| activities | zendesk_sell_activities | TIMESTAMP events |
| Zendesk-aligned sales operations | zendesk_sell_zendesk_aligned_sales_operations | id PK · linked to zendesk_sell_leads |
FAQ
How does Datrise handle Zendesk Sell's custom fields in Google BigQuery?
Flexible values are stored as JSON or nested/repeated (STRUCT) columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Google BigQuery types.
How does the Zendesk Sell to Google BigQuery sync stay up to date?
It runs incrementally — Datrise uses appends to a staging table, then MERGE on stable id into the partitioned target.
Related pipelines
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Early access
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