Connect Timing App and KNIME to Build Intelligent Automations
Enable Integrations or automations with these events of Timing App and KNIME
Enable Integrations or automations with these events of Timing App and KNIME
Actions
List All Projects
Retrieve all the projects.
Show Project
Retrieve the details of project.
Delete Project
Delete the project permanently.
List Reports
Shows all the reports.
List Teams
Retrieve all the teams.
List team members
Show all the members of team.
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Frequently Asked Questions
To start, connect both your Timing App and KNIME accounts to viaSocket. Once connected, you can set up a workflow where an event in Timing App triggers actions in KNIME (or vice versa).
Absolutely. You can customize how Timing App 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 Timing App 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 Timing App 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 Timing App
Timing App is a comprehensive time tracking software designed to help individuals and teams efficiently manage their time and productivity. With features like automatic time tracking, detailed reports, and project management integration, it ensures that users can optimize their workflow and focus on what truly matters.
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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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