ETL from Google Analytics to any target in a few clicks
- Build scalable, production-ready data pipelines in hours, not days
- Extract and load Google Analytics data into any target without code
- Complete your entire ELT pipeline with SQL or Python transformations
How to get started with our Google Analytics integration
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Ready-Made Data Workflow Kits with Google Analytics
Everything you need to simplify advanced data integration
Zero Infrastructure to Manage
Managed SQL/Python Modeling
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No-Code Any Data Ingestion
Efficient Database Replication
Integrated Data Activation
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Rivery offers a set of Predefined Reports for Google Analytics for rapid data integration. Using these reports, you can quickly analyze the data without having to learn the intricacies of the way the data is organized within the Google Analytics API. Simply provide your Google Analytics credentials and choose the report to load into your cloud data warehouse.
The Google Analytics data source in Rivery comes with the below predefined reports (click to navigate to the full data structure documentation):
- Demographics Report
- Engagement Reports
- E-commerce Purchase Reports
- Monetization E-commerce Purchases Item Brand
- Monetization E-commerce Purchases Item Category
- Monetization E-commerce Purchases Item Category 2
- Monetization E-commerce Purchases Item Category 3
- Monetization E-commerce Purchases Item Category 4
- Monetization E-commerce Purchases Item Category 5
- Monetization E-commerce Purchases Item Category Report Combined
- Monetization E-commerce Purchases Item Id
- Monetization E-commerce Purchases Item Name
- Publisher Ads Reports
- Tech Reports
- Traffic Acquisition Reports
- User Acquisition Reports
Google started sunsetting Universal Analytics (UA was known as Google Analytics) and is now offering Google Analytics 4 (GA4) instead. There are a few differences between UA and GA4 data structures and as a result differences in how GA4 data pipelines should be built. Follow this article to understand the options at hand.
Using Rivery’s data connectors is very straightforward. Just enter your credentials, define the target you want to load the data into (i.e. Snowflake, BigQuery, Databricks or any data lake and auto map the schema to generate on the target end. You can control the data you need to extract from the source and how often to sync your data. To learn more follow the specific docs.
Yes. All data connectors within Rivery comply with the highest security and privacy standards, including: GDPR, HIPPA, SOC2 and ISO 27001. In addition, when the data flows into your target data warehouse, you can configure it to do so via your own cloud files system vs. Rivery.
The most popular data connectors are for use cases like marketing, sales and finance. These include Salesforce, HubSpot, Google Analytics, Google Ads, LinkedIn Ads, Facebook Ads, TikTok and more.
Rivery supports both CDC database replication and Standard SQL extraction so you can choose the method that works best for you. Learn more here.