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.

How to take advantage of Pipelines?

1. SOURCES AVAILABLE IN PIPELINES

In pipelines, you have the option to select any data source available in your workspace. Ex: a data source can be a data warehouse, Datagran’s web or app SDK, a source like Hubspot or a source like Mailchimp or Campaign Monitor. Data is stored in Datagran’s BigQuery. Imagine it as an Excel table were your data is organized by rows and columns. Learn More >

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 AI Code Operator and the SQL operator. The SQL 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.

3. 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 >

4. Real-time vs Batch

When you use the Model Upload Operator you will have the option to deploy it in real-time. Default is batch. Just head to the model settings and deploy the model in real-time. For more information please read our documentation here.
Learn More >

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 >

Build DATA
Pipelines

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

available operators

How to take advantage of Pipelines?

1. SOURCES AVAILABLE IN PIPELINES

2. Operators

3. ACTIONs

4. Real-time vs Batch

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

let's talk

Better together

Build DATAPipelines

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

available operators

How to take advantage of Pipelines?

1. SOURCES AVAILABLE IN PIPELINES

2. Operators

3. ACTIONs

4. Real-time vs Batch

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

let's talk

Better together

Integrate

Build DATA
Pipelines