
When this happens...

Automatically do this!
Enable Integrations or automations with these events of Timing App and Datawrapper
Retrieve all the projects.
Retrieve the details of project.
Delete the project permanently.
Shows all the reports.
Retrieve all the teams.
Show all the members of team.
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Gain insights into how viaSocket functions through our detailed guide. Understand its key features and benefits to maximize your experience and efficiency.

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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 Timing App and Datawrapper accounts to viaSocket. Once connected, you can set up a workflow where an event in Timing App triggers actions in Datawrapper (or vice versa).
Absolutely. You can customize how Timing App data is recorded in Datawrapper. This includes choosing which data fields go into which fields of Datawrapper, setting up custom formats, and filtering out unwanted information.
The data sync between Timing App and Datawrapper 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 Datawrapper. 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.
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.
Learn MoreDatawrapper is a powerful tool for creating charts, maps, and tables from your data, making it easy to visualize and share insights. It is designed to help users transform raw data into clear, engaging visualizations that can be embedded in websites or shared across platforms.
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