Google Analytics 360 → Azure Data Lake Storage
AI-first ETL from Google Analytics 360 into Azure Data Lake Storage. Governed entities, incremental sync, typed landing tables.
How Datrise loads Google Analytics 360 into Azure Data Lake Storage
Datrise syncs Google Analytics 360's records, events, and configuration objects into Azure Data Lake Storage as partitioned Parquet in ADLS Gen2 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 to the container and compacts on a schedule, so re-runs update only what changed. Hive-style partitioning by load date, readable by Synapse and Databricks. ADLS hierarchical namespace makes folder layout matter, so Datrise keeps a predictable entity/date path your Azure engines mount directly.
Ideal for Azure lakehouse storage shared across Synapse and Databricks.
Endpoints
Google Analytics 360: SaaS or API data source for analytics and warehouse sync.
Azure Data Lake Storage: ADLS Gen2 object storage for analytics workloads.
How Google Analytics 360 entities map to Azure Data Lake Storage
| Google Analytics 360 entity | Azure Data Lake Storage object | Notes |
|---|---|---|
| records | google_analytics_360_records | id PK · custom fields → nested struct/map fields in Parquet |
| events | google_analytics_360_events | ISO-8601 timestamp columns events |
| configuration objects | google_analytics_360_configuration_objects | id PK · linked to google_analytics_360_records |
FAQ
How does Datrise handle Google Analytics 360's custom fields in Azure Data Lake Storage?
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 Azure Data Lake Storage types.
How does the Google Analytics 360 to Azure Data Lake Storage sync stay up to date?
It runs incrementally — Datrise uses writes new date partitions to the container and compacts on a schedule.
Related pipelines
More destinations for Google Analytics 360
- Google Analytics 360 → Azure Synapse
- Google Analytics 360 → Spreadsheets
- Google Analytics 360 → Airtable
- Google Analytics 360 → CSV Files
- Google Analytics 360 → MongoDB
- Google Analytics 360 → Supabase
- Google Analytics 360 → Neon
- Google Analytics 360 → PlanetScale
- Google Analytics 360 → Amazon DynamoDB
- Google Analytics 360 → Looker
- Google Analytics 360 → Looker Studio
- Google Analytics 360 → Microsoft Power BI
More sources for Azure Data Lake Storage
- Google Cloud SQL → Azure Data Lake Storage
- Google Cloud SQL Postgresql → Azure Data Lake Storage
- Google Cloud Storage F → Azure Data Lake Storage
- Google Directory → Azure Data Lake Storage
- Google Ecommerce → Azure Data Lake Storage
- Google Pagespeed Insights → Azure Data Lake Storage
- Google Webfonts → Azure Data Lake Storage
- Greenhouse → Azure Data Lake Storage
- Gridly → Azure Data Lake Storage
- Gutendex → Azure Data Lake Storage
- Harness → Azure Data Lake Storage
- Harvest Forecast → Azure Data Lake Storage
Early access
Connect Google Analytics 360 to Azure Data Lake Storage the easy way
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