> ## Documentation Index
> Fetch the complete documentation index at: https://docs.cognite.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Data models

> Create and manage data models in Cognite Data Fusion (CDF).

Data models are top-level organizational structures that define how industrial data is shaped and connected within the CDF knowledge graph. A data model groups views and serves as the main interface for applications to access and interact with structured data. When you create a data model, you establish a coherent API contract for consuming data from your space.

For the conceptual overview, see [Data models](/cdf/dm/dm_concepts/dm_containers_views_datamodels#data-models).

## What are data models

A data model acts as a logical grouping of views that together represent a domain or use case. Each data model provides a stable, versioned interface for applications to query and write data. Data models are scoped to a space, which controls access and organization.

<Info>
  Data models support versioning. You can create new versions over time to evolve your schema while maintaining backward compatibility for existing consumers.
</Info>

## Creating and versioning

When you create a data model, you assign it to a space and optionally specify a version. New versions can be created as your data modeling requirements evolve. Versioning helps you manage breaking changes and allows applications to pin to specific versions.

## Key capabilities

* **Create and update** — Create new data models or update existing ones with new view references.
* **Delete** — Remove data models when they are no longer needed.
* **List** — List all data models in a space, optionally filtered by status or other criteria.
* **Retrieve** — Fetch a specific data model by ID or external ID to inspect its configuration and views.