LinkedIn Ads → Redash
AI-first ETL from LinkedIn Ads into Redash. Governed entities, incremental sync, typed landing tables.
How Datrise loads LinkedIn Ads into Redash
Datrise syncs LinkedIn Ads's B2B campaign metrics, spend, clicks, leads, and audience performance into Redash as SQL tables Redash queries and visualizes. Flexible or custom fields land in flattened columns for query results, and timestamps such as created, updated, and status changes are typed as temporal columns.
Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts for scheduled queries. Redash caches query results on a schedule, so Datrise keeps tables incrementally fresh so cached dashboards reflect reality.
Ideal for lightweight, query-driven dashboards.
Endpoints
LinkedIn Ads: B2B advertising metrics for pipeline and attribution reporting.
Redash: Open-source SQL client for queries, visualizations, and dashboards.
How LinkedIn Ads entities map to Redash
| LinkedIn Ads entity | Redash object | Notes |
|---|---|---|
| B2B campaign metrics | linkedin_ads_b2b_campaign_metrics | id PK · custom fields → flattened columns for query results |
| spend | linkedin_ads_spend | id PK · linked to linkedin_ads_b2b_campaign_metrics |
| clicks | linkedin_ads_clicks | id PK · linked to linkedin_ads_b2b_campaign_metrics |
| leads | linkedin_ads_leads | id PK · linked to linkedin_ads_b2b_campaign_metrics |
FAQ
How does Datrise handle LinkedIn Ads's custom fields in Redash?
Flexible values are stored as flattened columns for query results, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Redash types.
How does the LinkedIn Ads to Redash sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables.
Related pipelines
More destinations for LinkedIn Ads
Early access
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