
When this happens...
Automatically do this!
Enable Integrations or automations with these events of BulkGate and Coursera: Data Science Specialization
Add a Contact in BulkGate Address Book
Update an existing contact by its Phone Number
Get a Contact by Phone Number
Adds a number to blacklist.
Check Number is Blacklisted.
Removes number from black list.
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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 BulkGate and Coursera: Data Science Specialization accounts to viaSocket. Once connected, you can set up a workflow where an event in BulkGate triggers actions in Coursera: Data Science Specialization (or vice versa).
Absolutely. You can customize how BulkGate data is recorded in Coursera: Data Science Specialization. This includes choosing which data fields go into which fields of Coursera: Data Science Specialization, setting up custom formats, and filtering out unwanted information.
The data sync between BulkGate and Coursera: Data Science Specialization 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 BulkGate and Coursera: Data Science Specialization. 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.
Bulkgate is a comprehensive platform designed for businesses to streamline their communication through bulk messaging services. It offers tools for sending SMS, Viber, and other messaging services to engage with customers effectively.
Learn MoreMaster the art of data science with Coursera’s Data Science Specialization, created by Johns Hopkins University. This program guides you through the full data science pipeline—from data wrangling and statistical analysis to machine learning and data visualization—using R and real-world projects.
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