DatriseAI-first ETL

Sendgrid Core Looker

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

How Datrise loads Sendgrid Core into Looker

Datrise syncs Sendgrid Core's records, events, and configuration objects 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

Sendgrid Core: SaaS or API data source for analytics and warehouse sync.

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

How Sendgrid Core entities map to Looker

Sendgrid Core entityLooker objectNotes
recordssendgrid_core_recordsid PK · custom fields → flattened columns (nested fields expanded for modeling)
eventssendgrid_core_eventsdate/time dimension columns events
configuration objectssendgrid_core_configuration_objectsid PK · linked to sendgrid_core_records

FAQ

How does Datrise handle Sendgrid Core'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 Sendgrid Core to Looker sync stay up to date?

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

Related pipelines

Early access

Connect Sendgrid Core to Looker the easy way

Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.