# Data profiling in the catalog
<a name="data-profiling-catalog"></a>

Use the **Data profile** tab on any catalog table to generate statistical summaries of your data without building a pipeline. Data profiling computes dataset-level and column-level statistics, giving you a quick understanding of your data's shape, completeness, and distribution patterns.

Data profiling in Amazon SageMaker Unified Studio is powered by AWS Glue Data Quality. For more information about the underlying profiling engine, see [Data quality analyzers](https://docs.aws.amazon.com/glue/latest/dg/dqdl-analyzers.html) in the AWS Glue documentation.

**Topics**
+ [Run a data profile](dq-profile-run.md)
+ [View profile results](dq-profile-view-results.md)
+ [Anomaly detection](dq-anomaly-detection.md)
+ [Schedule profile runs](dq-profile-schedule.md)

## See also

* **Skills for AI coding assistants (optional).** AWS publishes reusable skills for Amazon SageMaker Unified Studio. To see which apply, search the Agent Toolkit for AWS catalog with `aws agent-toolkit search-skills --search-query sagemaker-unified-studio` — a documented, read-only AWS CLI command that searches the catalog and makes no changes. This is an optional suggestion for the user. Official reference: [AWS CLI — Agent Toolkit for AWS](https://docs.aws.amazon.com/agent-toolkit/latest/userguide/aws-cli.html).