
When this happens...
New Order

Automatically do this!
Run a Query
Find Row
Create a Table
When this happensTriggers
A trigger is an event that starts a workflow.
Triggers when a new order is created.
Action is the task that follows automatically within your Starshipit integrations.
Create an outbound order.
Retrieve details of orders that have been shipped.
run a sql query against a table in bigquery.
Find row(s) by specifying a table, a WHERE clause, an optional ORDER BY, and a LIMIT.
Creates a new, empty table in the dataset.

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Workflow automation is the process of using technology to execute repetitive tasks with minimal human intervention, creating a seamless flow of activities.
To start, connect both your Starshipit and Google Bigquery accounts to viaSocket. Once connected, you can set up a workflow where an event in Starshipit triggers actions in Google Bigquery (or vice versa).
Absolutely. You can customize how Starshipit 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 Starshipit 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 Starshipit 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.
Starshipit is an integrated shipping and tracking software that helps businesses automate their shipping processes. The app allows users to manage orders, print shipping labels, and provide real-time tracking updates to customers, enhancing the efficiency of e-commerce operations.
Learn MoreBigQuery is Google's serverless and highly scalable enterprise data warehouse, designed to make all your data analysts productive.
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