Update docs/dqx/docs/demos.mdx

Author: mwojtyczka

docs/dqx/docs/demos.mdx

@@ -10,7 +10,7 @@ Import the following notebooks in the Databricks workspace to try DQX out:
 ## Use as Library
 * [DQX Quick Start Demo Notebook](https://github.com/databrickslabs/dqx/blob/v0.8.0/demos/dqx_quick_start_demo_library.py) - quickstart on how to use DQX as a library.
 * [DQX Demo Notebook](https://github.com/databrickslabs/dqx/blob/v0.8.0/demos/dqx_demo_library.py) - demonstrates how to use DQX as a library.
-* [DQX Demo (Native End-to-End Approach) Notebook for Spark Structured Streaming](https://github.com/databrickslabs/dqx/blob/v0.8.0/demos/dqx_streaming_demo_native.py) - demonstrates how to use DQX as a library with Spark Structured Streaming (using All-in-one native method `apply_checks_by_metadata_and_save_in_table`; handles read-process-write internally).
+* [DQX Demo Notebook for Spark Structured Streaming (Native End-to-End Approach)](https://github.com/databrickslabs/dqx/blob/v0.8.0/demos/dqx_streaming_demo_native.py) - demonstrates how to use DQX as a library with Spark Structured Streaming (using all-in-one native method `apply_checks_by_metadata_and_save_in_table`).
 * [DQX Demo (DIY Approach) Notebook for Spark Structured Streaming](https://github.com/databrickslabs/dqx/blob/v0.8.0/demos/dqx_streaming_demo_diy.py) - demonstrates how to use DQX as a library with Spark Structured Streaming (Writing your own Streaming Pipeline: read → `apply_checks_by_metadata_and_split` → write).
 * [DQX Demo Notebook for Lakeflow Pipelines (DLT)](https://github.com/databrickslabs/dqx/blob/v0.8.0/demos/dqx_dlt_demo.py) - demonstrates how to use DQX as a library with Lakeflow Pipelines (formerly Delta Live Tables (DLT)).
 * [DQX Asset Bundles Demo](https://github.com/databrickslabs/dqx/blob/v0.8.0/demos/dqx_demo_asset_bundle/README.md) - demonstrates how to use DQX as a library with Databricks Asset Bundles.