Data¶
Data integrity and quality are cornerstones for creating highly accurate predictive models. These sections describe the tools and visualizations provided to ensure that your project doesn’t suffer the “garbage in, garbage out” outcome.
| Resource | Description |
|---|---|
| Create and manage datasets | Ingest, transform, and store your data for experimentation. |
| Build data connections | Integrate with a variety of enterprise databases. |
| Recipes | Clean and wrangle data with reusable recipes for data preparation. |
| Features | How to work with features and retrieve their statistics in your projects. |
| Feature Discovery | Deploy, monitor, manage, and govern all your models in production, regardless of how they were created or when and where they were deployed. |