DatriseAI-first ETL

Microsoft Advertising Looker

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

How Datrise loads Microsoft Advertising into Looker

Datrise syncs Microsoft Advertising's campaigns, ad groups, keywords, spend, and conversion metrics 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

Microsoft Advertising: Paid search and audience ads on Microsoft properties.

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

How Microsoft Advertising entities map to Looker

Microsoft Advertising entityLooker objectNotes
campaignsbing_ads_campaignsid PK · custom fields → flattened columns (nested fields expanded for modeling)
ad groupsbing_ads_ad_groupsid PK · linked to bing_ads_campaigns
keywordsbing_ads_keywordsid PK · linked to bing_ads_campaigns
spendbing_ads_spendid PK · linked to bing_ads_campaigns

FAQ

How does Datrise handle Microsoft Advertising'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 Microsoft Advertising 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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