# Financial planning analysis
URL: https://docs.datarobot.com/en/docs/api/dev-learning/accelerators/time-series/fin-plan.html

> This accelerator illustrates an end-to-end financial planning and analysis workflow in DataRobot.

# Financial planning analysis

[Access this AI accelerator on GitHub](https://github.com/datarobot-community/ai-accelerators/blob/main/use_cases_and_horizontal_approaches/FP%26A/FP%26A.ipynb)

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

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