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

# DATA EXPLORER

> Exploring & validating your datasets

After uploading or synthesizing a dataset, you should validate its structure and quality before using it in downstream workflows. <Tooltip headline="Data Explorer" tip="Oumi tool for browsing and analyzing datasets." cta="Full Definition" href="/reference/key-terms#data-explorer">Oumi’s Data Explorer</Tooltip> makes this easy by letting you review and refine your data within the same visual interface.

With Data Explorer, you can:

* Inspect input–output pairs
* Verify dataset integrity
* Review schemas and fields
* Export datasets for local editing
* Re-upload updated versions

Data Explorer provides a convenient way to spot-check your data and catch critical issues early.

## ACCESSING THE DATA EXPLORER

Go to the **Datasets** page and click the name of the dataset to explore. On the dataset’s overview page, click the `Data Explorer` button to launch the Data Explorer window.

<video autoPlay controls muted loop playsInline allowFullScreen className="w-full aspect-video rounded-xl" src="https://mintcdn.com/oumi/-C82V_kXqoBIcXEj/videos/data-explorer-new.mp4?fit=max&auto=format&n=-C82V_kXqoBIcXEj&q=85&s=fcff5817b08b3b8d86724664dd3b5c41" data-path="videos/data-explorer-new.mp4" />

### WHAT TO VALIDATE

When reviewing a dataset in Data Explorer, be sure to check for the following:

* The row count matches your expectations
* All required fields and labels are present
* The data quality is sufficient for training or evaluation

By surfacing data issues at this stage, you can ensure early on that your dataset is ready for use and minimize the risk of downstream errors.