DatriseAI-first ETL

Vincle to Looker Studio Integration

AI-first ETL from Vincle into Looker Studio. Governed entities, incremental sync, typed landing tables.

How Datrise loads Vincle into Looker Studio

Datrise syncs Vincle's customers, visits, orders, product assortments, promotions, and sales routes into Looker Studio as warehouse tables Looker Studio connects to. Flexible or custom fields land in flattened columns for chart fields, and timestamps such as created, updated, and status changes are typed as date dimension columns.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned tables to keep extract refresh fast. Looker Studio performs best on pre-aggregated tables, so Datrise lands tidy, report-shaped tables rather than raw API payloads.

Ideal for free, shareable dashboards on Google data sources.

Endpoints

Vincle: Field sales and trade execution for consumer goods.

Looker Studio: Google self-service dashboards and reporting (formerly Data Studio).

How Vincle entities map to Looker Studio

Vincle entityLooker Studio objectNotes
customersvincle_customersid PK · custom fields → flattened columns for chart fields
visitsvincle_visitsid PK · linked to vincle_customers
ordersvincle_ordersid PK · linked to vincle_customers
product assortmentsvincle_product_assortmentsid PK · linked to vincle_customers

FAQ

How does Datrise handle Vincle's custom fields in Looker Studio?

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

How does the Vincle to Looker Studio sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the connected tables.

Related pipelines

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