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DataRobot API resources > AI accelerators > Ecosystem integration templates > End-to-end modeling workflow with Azure

End-to-end modeling workflow with Azure

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DataRobot offers an in-depth API that allows you to produce fully automated workflows in your coding environment of choice. This accelerator shows how to enable end-to-end processing of data stored natively in Azure.

In this notebook you'll see how data stored in Azure can be used to train a collection of models on DataRobot. You'll then deploy a recommended model and use DataRobot's batch prediction API to produce predictions and write them back to the source Azure container.

This accelerator notebook covers the following activities:

  • Acquire a training dataset from an Azure storage container
  • Build a new DataRobot project
  • Deploy a recommended model
  • Score via DataRobot's batch prediction API
  • Write results back to the source Azure container