Build ML Pipelines

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

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

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.

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

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

rfm

01

JOIN

02

Deduplicate

04

Custom SQL

05

Recommended product

06

custom
funnel

07

How to take advantage of Pipelines?

read full report

How Rappi reduced Customer Acquistion and Churm 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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