Build ML Pipelines

The most advanced visual editor ever built to quickly put Machine Learning pipelines into production.

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an ML model dashboard
an ML model dashboard
ML pipeline diagram
ML pipeline diagram

What are Operators?

Operators are functions embedded in Datagran’s platform that help you interact and process data.

For example, our SQL operator allows you to eliminate duplicate data based on a condition.

What are Actions?

A specific type of operator that communicates with the outer world. In addition to some standard destinations, we also created “Apps” embedded in our system that guarantee the best user experience within our platform without having to go to specific tools outside our environment.

Datagran ML Pipelines are interconnected sources, operators and actions that help you process data to ACHIEVE a specific goal.

ML pipeline diagram
ML pipeline diagram

What are Operators?

Operators are functions embedded in Datagran’s platform that help you interact and process data.

For example, our deduplicate operator allows you to eliminate duplicated data based on a condition.

What are Action Operators?
A specific type of operator that communicates with the outer world. In addition to some standard destinations, we also created “Apps” embedded in our system that guarantee the best user experience within our platform without having to go to specific tools outside our environment.

available operators

How to take advantage of Pipelines?

Algorithm icons

2. Operators

Operators help you interact and process data which will then can be used to make specific actions. Some of the most useful ones are the Aggregate and the SQL operator. The Join Operator allows you to aggregate different sources of data with the option to aggregate it with the KEY the client wants. For example: the key can be the user's email.
ML Pipeline Actions illustration

4. ACTIONs

Set an action for a specific pipeline. For example, send the result of the pipeline to Google Sheets, BigQuery or if you are a Marketing expert, create a cluster in Facebook or send an email.
Learn More >
Rappi driver

How Rappi reduced Customer Acquistion and Churn thanks to Datagran's Pipelines

Rappi is one of the very few Unicorn companies in Latin America. In 2018 it made 11,000 deliveries per hour, and it now serves more than 4 countries and 11 cities. Such growth, demands for the organization to move fast. That is why they teamed up with Datagran: to find a way to put Machine Learning predictions into production fast in order to reduce Customer Acquisition and Churn. Read Case Study >

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