ETL from YouTube Reporting to Azure Blob Storage in a few clicks
- Leverage YouTube Reporting data in Azure Blob Storage for advanced analytics
- Build scalable, production-ready data pipelines in hours, not days
- Extract data from YouTube Reporting and load into Azure Blob Storage without code
- Complete your entire ELT pipeline with SQL or Python transformations
- Centralize YouTube Reporting data in Azure Blob Storage for unified access and analytics
How to get started with our YouTube Reporting to Azure Blob Storage integration
See YouTube Reporting to Azure Blob Storage in action
Put your YouTube Reporting data to use.Deliver YouTube Reporting data at the right time, to the right people.
Everything you need to simplify advanced data integration
Zero Infrastructure to Manage
Managed SQL/Python Modeling
Predictable Value-Based Pricing
Reduced Data Development Waste
No-Code Any Data Ingestion
Efficient Database Replication
Infinite Scale
Integrated Data Activation
Proactive Troubleshooting
Bring all your data together. Integrate data from anywhere
Greg Robinson
Staff Data Scientist
Load YouTube Reporting to any data lake or warehouse
FAQ
Rivery offers a set of Predefined Reports for YouTube Reporting 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 YouTube Reporting API. Simply provide your YouTube Reporting credentials and choose the report to load into your cloud data warehouse.
The YouTube Reporting data source in Rivery comes with the below predefined reports (click to navigate to the full data structure documentation):
- Dimensions Channels
- Dimensions Videos
- Static Operating System
- Static Sharing Service
- Static Traffic Source Type
- Static Card Type
- Static Device Type
- Static Annotation Type
- Analytics Province
- Analytics Device And OS
- Analytics Traffic Source
- Analytics Demographics
- Analytics User Activity
- Analytics Subtitles
- Analytics Sharing Service
- Analytics Combined
- Analytics Playlist Device And OS
- Analytics Playlist Playback Locations
- Analytics Playlist Traffic Sources
- Analytics Playlist User Activity
- Analytics Playback Locations
- Analytics Playlist Combined
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.