DatriseAI-first ETL

Bigin by Zoho Looker

AI-first ETL from Bigin by Zoho into Looker. Governed entities, incremental sync, typed landing tables.

How Datrise loads Bigin by Zoho into Looker

Datrise syncs Bigin by Zoho's SMB leads, contacts, deals, and day-to-day activity tracking into Looker as governed warehouse tables with LookML-ready naming. Flexible or custom fields land in flattened columns (nested fields expanded for modeling), and timestamps such as created, updated, and status changes are typed as date/time dimension columns.

Sync is incremental: Datrise uses incremental refresh of the underlying warehouse tables Looker explores, so re-runs update only what changed. Date-partitioned fact tables for PDT performance. Looker models live in LookML on top of SQL, so Datrise lands clean, stable column names rather than churn that would break your views.

Ideal for governed, version-controlled BI on a warehouse.

Endpoints

Bigin by Zoho: SMB CRM source for leads, deals, and activity tracking.

Looker: Google Cloud BI with LookML semantic models and governed dashboards.

How Bigin by Zoho entities map to Looker

Bigin by Zoho entityLooker objectNotes
SMB leadsbigin_by_zoho_smb_leadsid PK · custom fields → flattened columns (nested fields expanded for modeling)
contactsbigin_by_zoho_contactsid PK · linked to bigin_by_zoho_smb_leads
dealsbigin_by_zoho_dealsid PK · linked to bigin_by_zoho_smb_leads
day-to-day activity trackingbigin_by_zoho_day_to_day_activity_trackingdate/time dimension columns events

FAQ

How does Datrise handle Bigin by Zoho's custom fields in Looker?

Flexible values are stored as flattened columns (nested fields expanded for modeling), so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Looker types.

How does the Bigin by Zoho to Looker sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the underlying warehouse tables Looker explores.

Related pipelines

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