DatriseAI-first ETL

StackAdapt to Looker Studio Integration

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

How Datrise loads StackAdapt into Looker Studio

Datrise syncs StackAdapt's campaigns, line items, creatives, spend, impressions, and conversions 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

StackAdapt: Programmatic advertising across native and display.

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

How StackAdapt entities map to Looker Studio

StackAdapt entityLooker Studio objectNotes
campaignsstackadapt_campaignsid PK · custom fields → flattened columns for chart fields
line itemsstackadapt_line_itemsid PK · linked to stackadapt_campaigns
creativesstackadapt_creativesid PK · linked to stackadapt_campaigns
spendstackadapt_spendid PK · linked to stackadapt_campaigns

FAQ

How does Datrise handle StackAdapt'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 StackAdapt 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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