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Financial planning and analysis workflow

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This accelerator illustrates an end-to-end financial planning and analysis workflow in DataRobot. Time series forecasting in DataRobot has a huge suite of tools and approaches to handle highly complex multiseries problems. DataRobot is used for the model training, selection, deployment, and creation of forecasts. While this example will leverage a snapshot file as a data source, this workflow applies to any data source, e.g. Redshift, S3, Big Query, Synapse, etc.

This notebook will demonstrate how to use the Python API client to:

  • Connect to DataRobot
  • Import and preparation of data for time series modeling
  • Create a time series forecasting project and run Autopilot
  • Retrieve and evaluate model performance and insights
  • Making forward looking forecasts
  • Evaluating forecasts vs. historical trends
  • Deploy a model

Updated January 31, 2024