Data preparation¶
Data integrity and quality are cornerstones for creating highly accurate predictive models. These sections describe the tools and visualizations DataRobot provides to ensure that your project doesn't suffer the "garbage in, garbage out" outcome.
DataRobot’s wrangling capabilities give you the ability to prepare data and engineer features with a no-code interface to see transformations in real time—reducing the time from data to model.
This section covers the following topics:
| Topic | Description |
|---|---|
| Explore data | Manage datasets and wrangling recipes linked to your Use Case, and access exploratory data insights. |
| Add data | Add datasets to your Use Case from a local file, data connection, or the Data Registry. |
| Wrangle data | Interactively prepare data for modeling without moving it from your data source to generate a new output dataset. |
| Feature Discovery | Perform multi-dataset, interaction-based feature creation. |
| Data preparation reference | View connection capabilities, feature considerations, and other reference material for data preparation. |
Updated February 20, 2025
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