Connect Amazing Marvin and KNIME to Build Intelligent Automations
Enable Integrations or automations with these events of Amazing Marvin and KNIME
Enable Integrations or automations with these events of Amazing Marvin and KNIME
Actions
Create Task
Creates a new task.
Delete one or more reminders hold
Deletes the chosen reminders .
Create Project
Creates a new project.
Set reminder
Set a reminder
Start/Stop time tracking
Start or Stop time tracking of a task by ID.
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Frequently Asked Questions
To start, connect both your Amazing Marvin and KNIME accounts to viaSocket. Once connected, you can set up a workflow where an event in Amazing Marvin triggers actions in KNIME (or vice versa).
Absolutely. You can customize how Amazing Marvin 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 Amazing Marvin 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 Amazing Marvin 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 Amazing Marvin
Amazing Marvin is a customizable task manager and daily planner app designed to help users beat procrastination, feel more in control and finish their to-do list. It combines principles from behavioral psychology with a playful design to make your work more productive and fun.
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About 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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