Connect SheetDB and DataRobot to Build Intelligent Automations
Choose a Trigger
When this happens...
- Request a new Trigger for SheetDB
Choose an Action
Automatically do this!
- Request a new Action for DataRobot
Enable Integrations or automations with these events of SheetDB and DataRobot
Enable Integrations or automations with these events of SheetDB and DataRobot
Actions
Create a Rows
Creating Rows.
Update a Row
Update a Row
Know More About Sheetdb and Datarobot Integrations
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Frequently Asked Questions
To start, connect both your SheetDB and DataRobot accounts to viaSocket. Once connected, you can set up a workflow where an event in SheetDB triggers actions in DataRobot (or vice versa).
Absolutely. You can customize how SheetDB data is recorded in DataRobot. This includes choosing which data fields go into which fields of DataRobot, setting up custom formats, and filtering out unwanted information.
The data sync between SheetDB and DataRobot 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 SheetDB and DataRobot. 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 SheetDB
SheetDB is a powerful tool that transforms your Google Sheets into a fully functional RESTful API, allowing you to easily integrate and manage your spreadsheet data with other applications and services. It simplifies the process of connecting your spreadsheets to web and mobile apps, enabling seamless data exchange and automation.
Learn MoreAbout DataRobot
DataRobot is a leading AI platform that enables organizations to harness the power of machine learning and artificial intelligence to drive business insights and decision-making. It offers automated machine learning capabilities, allowing users to build, deploy, and manage AI models efficiently.
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