Meta Ads → Looker
AI-first ETL from Meta Ads into Looker. Governed entities, incremental sync, typed landing tables.
How Datrise loads Meta Ads into Looker
Datrise syncs Meta Ads's campaign spend, impressions, clicks, conversions, and audience segments 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
Meta Ads: Facebook and Instagram ad source for spend and engagement.
Looker: Google Cloud BI with LookML semantic models and governed dashboards.
How Meta Ads entities map to Looker
| Meta Ads entity | Looker object | Notes |
|---|---|---|
| campaign spend | meta_ads_campaign_spend | id PK · custom fields → flattened columns (nested fields expanded for modeling) |
| impressions | meta_ads_impressions | id PK · linked to meta_ads_campaign_spend |
| clicks | meta_ads_clicks | id PK · linked to meta_ads_campaign_spend |
| conversions | meta_ads_conversions | id PK · linked to meta_ads_campaign_spend |
FAQ
How does Datrise handle Meta Ads'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 Meta Ads to Looker sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the underlying warehouse tables Looker explores.
Related pipelines
More destinations for Meta Ads
Early access
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