# AI Catalog

> AI Catalog - The AI Catalog is a searchable collection of registered objects that contains
> definitions and relationships between various object types. Items stored in the catalog include data
> connections, data sources, data metadata, and blueprints.

This Markdown file sits beside the HTML page at the same path (with a `.md` suffix). It summarizes the topic and lists links for tools and LLM context.

Companion generated at `2026-04-24T16:03:56.535216+00:00` (UTC).

## Primary page

- [AI Catalog](https://docs.datarobot.com/en/docs/classic-ui/data/ai-catalog/index.html): Full documentation for this topic (HTML).

## Related documentation

- [Classic UI documentation](https://docs.datarobot.com/en/docs/classic-ui/index.html): Linked from this page.
- [Data](https://docs.datarobot.com/en/docs/classic-ui/data/index.html): Linked from this page.
- [Import data and create projects](https://docs.datarobot.com/en/docs/classic-ui/data/ai-catalog/catalog.html): Linked from this page.
- [Work with catalog assets](https://docs.datarobot.com/en/docs/classic-ui/data/ai-catalog/catalog-asset.html): Linked from this page.
- [Manage catalog assets](https://docs.datarobot.com/en/docs/classic-ui/data/ai-catalog/manage-asset.html): Linked from this page.
- [Schedule data snapshots](https://docs.datarobot.com/en/docs/classic-ui/data/ai-catalog/snapshot.html): Linked from this page.
- [Prepare data with SparkSQL](https://docs.datarobot.com/en/docs/classic-ui/data/ai-catalog/spark.html): Linked from this page.

## Documentation content

# AI Catalog

The AI Catalog is a centralized collaboration hub for working with data and related assets. It enables seamlessly finding, sharing, tagging, and reusing data, helping to speed time to production. The catalog provides easy access to the data needed to answer a business problem while ensuring security, compliance, and consistency.

The AI Catalog is comprised of three key functions:

- Ingest : Data is imported into DataRobot and sanitized for use throughout the platform.
- Storage : Reusable data assets are stored, accessed, and shared—allowing you to share data without sharing projects, decreasing risks and costs around data duplication.
- Data Preparation : Clean, blend, transform, and enrich your data by leveraging SQL scripts for pinpointed results.

The catalog also supports data security and governance, which reduces friction and speeds up model adoption, through selective addition to the catalog, role-based sharing, and an audit trail.

| Topic | Description |
| --- | --- |
| Import datasets |  |
| Import data and create projects | Import data into the AI Catalog and from there, create a DataRobot project. |
| Interact with catalog assets |  |
| Work with catalog assets | View and modify asset details, create snapshots, and create projects from a data entry. |
| Manage catalog assets | Share, delete, and download data assets. |
| Schedule data snapshots | Set up schedules for data snapshots in the AI Catalog to keep a dataset in sync with its source data. |
| Prepare data |  |
| Prepare data with SparkSQL | Enrich, transform, shape, and blend together datasets using Spark SQL queries within the AI Catalog. |