DatriseAI-first ETL

Pinterest Ads to Sisense Integration

AI-first ETL from Pinterest Ads into Sisense. Governed entities, incremental sync, typed landing tables.

How Datrise loads Pinterest Ads into Sisense

Datrise syncs Pinterest Ads's campaigns, ad groups, pin promotions, spend, impressions, and conversions into Sisense as modeled tables for a Sisense ElastiCube (or live connection). Flexible or custom fields land in flattened columns for the cube, and timestamps such as created, updated, and status changes are typed as date/time fields.

Sync is incremental: Datrise uses incremental ElastiCube builds on changed rows, so re-runs update only what changed. Date-partitioned facts to speed cube builds. ElastiCube is an in-memory model, so Datrise lands incremental, build-friendly tables rather than forcing full rebuilds.

Ideal for embedded analytics on an in-memory engine.

Endpoints

Pinterest Ads: Paid pin campaigns and shopping performance.

Sisense: Analytics platform with elastic data models and embedded analytics.

How Pinterest Ads entities map to Sisense

Pinterest Ads entitySisense objectNotes
campaignspinterest_ads_campaignsid PK · custom fields → flattened columns for the cube
ad groupspinterest_ads_ad_groupsid PK · linked to pinterest_ads_campaigns
pin promotionspinterest_ads_pin_promotionsid PK · linked to pinterest_ads_campaigns
spendpinterest_ads_spendid PK · linked to pinterest_ads_campaigns

FAQ

How does Datrise handle Pinterest Ads's custom fields in Sisense?

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

How does the Pinterest Ads to Sisense sync stay up to date?

It runs incrementally — Datrise uses incremental ElastiCube builds on changed rows.

Related pipelines

Early access

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