DatriseAI-first ETL

LinkedIn Ads Microsoft SQL Server

AI-first ETL from LinkedIn Ads into Microsoft SQL Server. Governed entities, incremental sync, typed landing tables.

How Datrise loads LinkedIn Ads into Microsoft SQL Server

Datrise syncs LinkedIn Ads's B2B campaign metrics, spend, clicks, leads, and audience performance into Microsoft SQL Server as a typed table per source entity. Flexible or custom fields land in NVARCHAR(MAX) JSON columns, and timestamps such as created, updated, and status changes are typed as datetime2.

Sync is incremental: Datrise uses a watermark on updated-at, applied with a MERGE statement, so re-runs update only what changed. Optional partitioned tables on a date partition function. SQL Server defaults to a case-insensitive collation, so Datrise preserves original casing in a metadata column to avoid silent key collisions.

Ideal for Microsoft-stack analytics and Power BI Import models.

Endpoints

LinkedIn Ads: B2B advertising metrics for pipeline and attribution reporting.

Microsoft SQL Server: Microsoft relational DB with enterprise features.

How LinkedIn Ads entities map to Microsoft SQL Server

LinkedIn Ads entityMicrosoft SQL Server objectNotes
B2B campaign metricslinkedin_ads_b2b_campaign_metricsid PK · custom fields → NVARCHAR(MAX) JSON columns
spendlinkedin_ads_spendid PK · linked to linkedin_ads_b2b_campaign_metrics
clickslinkedin_ads_clicksid PK · linked to linkedin_ads_b2b_campaign_metrics
leadslinkedin_ads_leadsid PK · linked to linkedin_ads_b2b_campaign_metrics

FAQ

How does Datrise handle LinkedIn Ads's custom fields in Microsoft SQL Server?

Flexible values are stored as NVARCHAR(MAX) JSON columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Microsoft SQL Server types.

How does the LinkedIn Ads to Microsoft SQL Server sync stay up to date?

It runs incrementally — Datrise uses a watermark on updated-at, applied with a MERGE statement.

Related pipelines

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