
When this happens...

Automatically do this!
Enable Integrations or automations with these events of Scale and Google Cloud Bigtable
Retrieve all the tasks for given project.
Create a new batch in a project to group related tasks for processing.
Pause processing of an in-progress Batch. Only unstarted tasks will be paused.
Resume processing of a paused Batch. Previously paused tasks will be resumed.
Mark a Scale batch as complete so no new tasks can be added.
Cancel processing of a Batch. Unstarted tasks will be cancelled. Completed batches cannot be cancelled.
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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 Scale and Google Cloud Bigtable accounts to viaSocket. Once connected, you can set up a workflow where an event in Scale triggers actions in Google Cloud Bigtable (or vice versa).
Absolutely. You can customize how Scale data is recorded in Google Cloud Bigtable. This includes choosing which data fields go into which fields of Google Cloud Bigtable, setting up custom formats, and filtering out unwanted information.
The data sync between Scale and Google Cloud Bigtable 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 Scale and Google Cloud Bigtable. 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.
Scale provides advanced AI-driven solutions for data labeling and annotation, helping businesses streamline their machine learning workflows.
Learn MoreGoogle Cloud Bigtable is a fully managed, scalable NoSQL database service designed for large analytical and operational workloads. It is ideal for applications that require high throughput and low latency, such as IoT, user analytics, and financial data analysis.
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