Slack as an Action

We’re excited to announce Slack as part of our pipeline Actions. 

What can it do?

This new Action allows you to send data from your ML pipeline’s outcome directly to a Slack workspace. 

Why is it useful?

One of the main challenges businesses face is sending the output of ML models into the hands of business leaders, fast. Due to this problem, our team of data scientists found it necessary to offer an option for these outputs to be sent out to business APPS like Slack. This powers all teams across the organization with the data they need promptly.

Some examples of data outcomes you can push to Slack are: 

  1. Outcomes from an RFM model
  2. Outcomes from a Recommended product model
  3. Outcomes from a linear regression model
  4. Outcomes from a logistic regression model

A data pipeline example

Introducing Segment as a Data Source

You can now receive Web, Mobile, Server, and Cloud App data stored in Segment, directly into your Datagran account, thanks to or brand new Segment as a Data Source Integration.

What can it do?

Segment as a source of information inside of Datagran, gives you the ability to receive data from any of the Segment libraries to the Datagran platform. Whether that is from Email Marketing, Advertising, or Analytics sources, you can now extract it to use in any of our tools. 

Why is it useful?

While Segment lets you extract and send data to different connections, by sending it to Datagran you can now build ML data workflows with its extraction, as well as sending it to many business Apps. It provides endless possibilities for your teams to create ML models fed by the connections found inside of your Segment account, and it also allows you to choose what dataset to work with, thanks to our Custom SQL Operator. 

Watch the tutorial