Financial planning and analysis workflow¶

Access this AI accelerator on GitHub

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