# Data enrichment and preparation
URL: https://docs.datarobot.com/en/docs/api/dev-learning/accelerators/data-enrichment-prep/index.html

> Data enrichment and preparation accelerators that you can add to your experiment workflow.

# Data enrichment and preparation

| Topic | Description |
| --- | --- |
| Enrich with Hyperscaler API | Call the GCP API and enrich a modeling dataset that predicts customer churn. |
| GCP sentiment enrichment | Demo the usage of the Google Cloud Natural Language API for sentiment analysis to enrich a customer churn dataset. |
| Churn problem framing | Discover the problem framing and data management steps required to successfully model for churn, using a B2C retail example and a B2B example based on a DataRobot’s churn model. |
| Churn insights with Streamlit | Use the Streamlit churn predictor app to present the drivers and predictions of your DataRobot model. |
| Synthetic training data | Learn how to generate synthetic datasets that mimic real-world data for training, validation, and testing—enabling safe data sharing and model development when access to real data is limited due to privacy or regulatory constraints. |
| Feature engineering for molecular SMILES data | Execute a feature engineering pipeline tailored for SMILES-formatted molecular data. |

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