Connect Microsoft Excel and MonkeyLearn Legacy to Build Intelligent Automations
Enable Integrations or automations with these events of Microsoft Excel and MonkeyLearn Legacy
Enable Integrations or automations with these events of Microsoft Excel and MonkeyLearn Legacy
Actions
Find Row
Find a Row in a table by column and value
Create Spreadsheet
Create a New Spreadsheet
Add Row to Table
Add Row to the End of Specific Table
Update Row
Update Row
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Step by step guides to integrate Microsoft Excel and MonkeyLearn Legacy
Frequently Asked Questions
To start, connect both your Microsoft Excel and MonkeyLearn Legacy accounts to viaSocket. Once connected, you can set up a workflow where an event in Microsoft Excel triggers actions in MonkeyLearn Legacy (or vice versa).
Absolutely. You can customize how Microsoft Excel data is recorded in MonkeyLearn Legacy. This includes choosing which data fields go into which fields of MonkeyLearn Legacy, setting up custom formats, and filtering out unwanted information.
The data sync between Microsoft Excel and MonkeyLearn Legacy 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 Microsoft Excel and MonkeyLearn Legacy. 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 Microsoft Excel
Microsoft Excel is a spreadsheet program included as part of the Microsoft Office suite of applications. It allows users to organize, format, and calculate data with formulas using a spreadsheet system broken up by rows and columns
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About MonkeyLearn Legacy
MonkeyLearn is a Text Analysis platform that allows you to classify and extract actionable data from raw texts like emails, chats, webpages, documents, tweets and more! You can classify texts with custom tags like sentiment or topic, and extract any particular data like organizations or keywords.
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