Sync data from Google BigQuery to Amazon S3

Sync your data from Google BigQuery to Amazon S3 with DataChannel in minutes without writing any code or scripts. Select and map the fields you want to load and retain complete control over the data you are moving.

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Amazon S3

About Amazon S3

Amazon Simple Storage Service is an object storage service offering industry-leading scalability, data availability, security, and performance.

Learn more about Amazon S3.

See where you can sync data to in Amazon S3

Export

This sync can be used to request and retrieve data from a user specified data warehouse to the Amazon S3.

Learn more about what data can be integrated into your data warehouse using DataChannel in the documentation here.

Steps to sync data to Amazon S3 from Google BigQuery using DataChannel

1. Setup a Data Warehouse - Go to Data Warehouses Tab and add a BigQuery Warehouse. 

*To understand how to add a BigQuery Data Warehouse check out this video.

2. Setup a Data Model - Navigate to Data Models tab and click on Create New. Name your Data Model and select your data warehouse from the drop down. Write a SQL query to fetch data from your warehouse. 

(Eg. Select * from Schema_Name.Table_Name)

*A simple “select” statement will work, although you can write complex SQL queries in the data model field itself or use our no-code segment builder to filter your data without writing complex SQL Queries.

3. Configure your Data Destination - Navigate to Destinations tab and select Amazon S3.

  • Add Your Credentials using the “+” Button.
  • Click on “+Data Sync ” to start adding Data Syncs to your account. 

Why choose DataChannel to sync data from Google BigQuery to Amazon S3

Granular control over pipeline configuration
Advanced scheduling options
Automated handling of source schema changes
Secure credential management with OAuth2
Activity & change history tracking
Real time alerts & failure notifications
Preview data without ever leaving the platform
Extensive documentation & on-screen help
Extensive Logs & complete visibility of pipeline health

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