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Azure Data Flow Template

The Azure Data Flow is a diagram that will allow you to combine data and build and deploy custom machine learning models at scale.

About the Azure Data Flow Template

The Azure Data Flow Template will show you how to transform your data into actionable insights using the best-in-class machine learning tools. This architecture allows you to combine data and build and deploy custom machine learning models at scale.

Keep reading to learn more about the Azure Data Flow Template.

What is an Azure Data Flow Template

The Azure Data Flow Template visually shows the data flow to deploy and build custom machine learning models. The Azure Data Flow Template has unique icons categorized into Stencils. Each Stencil focuses on a specific task to make it easier for users to access the right set of icons. 

When to use Azure Data Flow Template

You can use the Azure Data Flow Template to transform your data into actionable insights and better inform decision making. Collect data, analyze it, and use it to make decisions surrounding your architecture, from cost data, to performance, to user load, using data will guide you to make the right choices in your environment.

To build your Azure Data Flow Template, check out these best practices: 

Do’s

  • Use the icon to illustrate how products can work together

  • In diagrams, we recommend to include the product name somewhere close to the icon

  • Use the icons as they would appear within Azure

Don’ts

  • Don’t crop, flip or rotate icons

  • Don’t distort or change icon shape in any way

  • Don’t use Microsoft product icons to represent your product or service.

FAQ about azure Data Flow Template:

How do I make an Azure Data Flow Template?

To make an Azure Data Flow in Miro is easy. You can use our Azure Data Flow Template and customize it as you see fit. Once you have the diagram structure, you can start adding the icons. You can find the icons under our Azure Icon Set integration.

Azure Data Flow Template

Get started with this template right now.

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