LinkedIn Ads → Amazon S3 Data Lake
AI-first ETL from LinkedIn Ads into Amazon S3 Data Lake. Governed entities, incremental sync, typed landing tables.
How Datrise loads LinkedIn Ads into Amazon S3 Data Lake
Datrise syncs LinkedIn Ads's B2B campaign metrics, spend, clicks, leads, and audience performance into Amazon S3 Data Lake as columnar Parquet objects partitioned per source entity. Flexible or custom fields land in nested struct/map fields in Parquet, and timestamps such as created, updated, and status changes are typed as ISO-8601 timestamp columns.
Sync is incremental: Datrise uses writes new date partitions and compacts small files on a schedule, so re-runs update only what changed. Hive-style path partitioning (entity/date) for engine-agnostic reads. A lake has no schema enforcement, so Datrise writes a schema manifest alongside the data to keep downstream engines consistent.
Ideal for an open, engine-neutral storage layer for Spark, Athena, Trino, or DuckDB.
Endpoints
LinkedIn Ads: B2B advertising metrics for pipeline and attribution reporting.
Amazon S3 Data Lake: Object storage landing zone for parquet and snapshots.
How LinkedIn Ads entities map to Amazon S3 Data Lake
| LinkedIn Ads entity | Amazon S3 Data Lake object | Notes |
|---|---|---|
| B2B campaign metrics | linkedin_ads_b2b_campaign_metrics | id PK · custom fields → nested struct/map fields in Parquet |
| 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 Amazon S3 Data Lake?
Flexible values are stored as nested struct/map fields in Parquet, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Amazon S3 Data Lake types.
How does the LinkedIn Ads to Amazon S3 Data Lake sync stay up to date?
It runs incrementally — Datrise uses writes new date partitions and compacts small files on a schedule.
Related pipelines
More destinations for LinkedIn Ads
- LinkedIn Ads → Azure Data Lake Storage
- LinkedIn Ads → Azure Synapse
- LinkedIn Ads → Spreadsheets
- LinkedIn Ads → Airtable
- LinkedIn Ads → CSV Files
- LinkedIn Ads → MongoDB
- LinkedIn Ads → Supabase
- LinkedIn Ads → Neon
- LinkedIn Ads → PlanetScale
- LinkedIn Ads → Amazon DynamoDB
- LinkedIn Ads → Looker
- LinkedIn Ads → Looker Studio
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Early access
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