Connect Onsched and KNIME to Build Intelligent Automations
Choose a Trigger
When this happens...
New appointment scheduled
Choose an Action
Automatically do this!
- Request a new Action for KNIME
Enable Integrations or automations with these events of Onsched and KNIME
Enable Integrations or automations with these events of Onsched and KNIME
Triggers
New appointment scheduled
Starts a workflow when a customer books an appointment at the selected location.
Actions
Create Appointment
Create a new appointment for a customer at a selected location, service, and resource(s), specifying start/end date and time and whether it's confirmed.
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Frequently Asked Questions
To start, connect both your Onsched and KNIME accounts to viaSocket. Once connected, you can set up a workflow where an event in Onsched triggers actions in KNIME (or vice versa).
Absolutely. You can customize how Onsched data is recorded in KNIME. This includes choosing which data fields go into which fields of KNIME, setting up custom formats, and filtering out unwanted information.
The data sync between Onsched and KNIME 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 Onsched and KNIME. 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 Onsched
Onsched is a powerful scheduling and booking platform designed to streamline appointment management for businesses. It offers customizable solutions to enhance customer engagement and optimize scheduling processes.
Learn MoreAbout KNIME
KNIME is a powerful open-source platform designed for data analytics, reporting, and integration. It enables users to create data workflows and perform complex data analysis with ease, using a visual programming interface. KNIME is widely used for data mining, machine learning, and predictive analytics, making it a valuable tool for data scientists and analysts.
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