Connect VATlayer and Google Bigquery to Build Intelligent Automations
Enable Integrations or automations with these events of VATlayer and Google Bigquery
Enable Integrations or automations with these events of VATlayer and Google Bigquery
Actions
Validate VAT number
Verify a VAT number and get its country and validation status
Get VAT rate
Get the VAT rate for a country or VAT number.
Get VAT rates lists
Retrieve current VAT rates (standard and reduced) for countries.
Delete Rows
Deletes rows from a BigQuery table that match the provided WHERE condition.
Run SQL query
Run a SQL query and return results.
Find Row
Find row(s) by specifying a table, a WHERE clause, an optional ORDER BY, and a LIMIT.
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Frequently Asked Questions
To start, connect both your VATlayer and Google Bigquery accounts to viaSocket. Once connected, you can set up a workflow where an event in VATlayer triggers actions in Google Bigquery (or vice versa).
Absolutely. You can customize how VATlayer data is recorded in Google Bigquery. This includes choosing which data fields go into which fields of Google Bigquery, setting up custom formats, and filtering out unwanted information.
The data sync between VATlayer and Google Bigquery typically happens in real-time through instant triggers. And a maximum of 15 minutes in case of a scheduled trigger.
Yes, viaSocket allows you to add custom logic or use built-in filters to modify data according to your needs.
Yes, you can set conditional logic to control the flow of data between VATlayer and Google Bigquery. For instance, you can specify that data should only be sent if certain conditions are met, or you can create if/else statements to manage different outcomes.
About VATlayer
VATlayer provides a reliable and easy-to-use API for VAT number validation, VAT rates, and VAT compliance. It is designed to help businesses manage their VAT obligations efficiently and accurately.
Learn MoreAbout Google Bigquery
BigQuery is Google's serverless and highly scalable enterprise data warehouse, designed to make all your data analysts productive.
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