Enable Integrations or automations with these events of Flodesk and Google Cloud Bigtable
Triggers when a new subscriber is created.
Trigger when a new subscriber added to a segment.
Triggers when a subscriber is unsubscribed.
Remove subscriber from a specific segments.
Add an subscriber to the specific segments.
Find a subscriber by its email address or id.
Unsubscribe a subscriber.
Creates a new subscriber or updates an existing one.
Retrieve all the details of subscribers.
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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 Flodesk and Google Cloud Bigtable accounts to viaSocket. Once connected, you can set up a workflow where an event in Flodesk triggers actions in Google Cloud Bigtable (or vice versa).
Absolutely. You can customize how Flodesk 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 Flodesk 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 Flodesk 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.
Flowdesk is a comprehensive platform designed to streamline operations and enhance productivity for businesses. It offers a suite of tools for project management, workflow automation, and team collaboration, helping organizations to efficiently manage projects and tasks.
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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